Copyright

4th Estate

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First published in Great Britain by 4th Estate in 2016

This 4th Estate paperback edition 2017

Copyright © Marcus du Sautoy 2016

Cover design © Jonathan Pelham

The right of Marcus du Sautoy to be identified as the author of this work has been asserted by him in accordance with the Copyright, Designs and Patents Act 1988

A catalogue record for this book is available from the British Library

All rights reserved under International and Pan-American Copyright Conventions. By payment of the required fees, you have been granted the non-exclusive, non-transferable right to access and read the text of this e-book on-screen. No part of this text may be reproduced, transmitted, down-loaded, decompiled, reverse engineered, or stored in or introduced into any information storage and retrieval system, in any form or by any means, whether electronic or mechanical, now known or hereinafter invented, without the express written permission of HarperCollins.

Source ISBN: 9780007576593

Ebook Edition © 2017 ISBN: 9780007576579

Version: 2019-11-29

Dedication

To my parents, who started me on my journey to the edges of knowledge

CONTENTS

Cover

Title Page

Copyright

Dedication

Edge Zero: The Known Unknowns

First Edge: The Casino Dice

Chapter 1

Chapter 2

Second Edge: The Cello

Chapter 3

Chapter 4

Third Edge: The Pot of Uranium

Chapter 5

Chapter 6

Fourth Edge: The Cut-Out Universe

Chapter 7

Chapter 8

Fifth Edge: The Wristwatch

Chapter 9

Chapter 10

Sixth Edge: The Chatbot App

Chapter 11

Chapter 12

Seventh Edge: The Christmas Cracker

Chapter 13

Chapter 14

Further Reading

Index

Acknowledgements

Illustration Credits

Also by Marcus du Sautoy

About the Publisher

EDGE ZERO: The Known Unknowns

Everyone by nature desires to know.

Aristotle, Metaphysics

Science is king.

Every week, headlines announce new breakthroughs in our understanding of the universe, new technologies that will transform our environment, new medical advances that will extend our lives. Science is giving us unprecedented insights into some of the big questions that have challenged humanity ever since we’ve been able to formulate those questions. Where did we come from? What is the ultimate destiny of the universe? What are the building blocks of the physical world? How does a collection of cells become conscious?

In the last ten years alone we’ve landed a spaceship on a comet, made robots that can create their own language, used stem cells to repair the pancreas of diabetic patients, discovered how to use the power of thought alone to manipulate a robotic arm, sequenced the DNA of a 50,000-year-old cave girl. Science magazines are bursting with the latest breakthroughs emerging from the world’s laboratories. We know so much. The advances of science are extremely intoxicating.

Science has given us our best weapon in our fight against fate. Instead of giving in to the ravages of disease and natural disaster, science has created vaccines to combat deadly viruses like polio and even ebola. Faced with an escalating world population, it is scientific advances that provide the best hope of feeding the 9.6 billion people who are projected to be alive in 2050. It is science that is warning us about the deadly impact we are having on our environment and giving us the chance to do something about it before it is too late. An asteroid might have wiped out the dinosaurs, but the science that humans have developed is our best shield against any future direct hits. In the human race’s constant battle with death, science is its best ally.

Science is king not only when it comes to our fight for survival but also in improving our quality of life. We are able to communicate with friends and family across vast distances. We have unparalleled access to the database of knowledge we have accumulated over generations of investigation. We have created virtual worlds that we can escape to in our leisure time. We can recreate in our living rooms the great performances of Mozart, Miles and Metallica at the press of a button.

That desire to know is programmed into the human psyche. Those early humans with a thirst for knowledge are those who have survived, adapted, transformed their environment. Those not driven by that craving were left behind. Evolution has favoured the mind that wants to know the secrets of how the universe works. The adrenaline rush that accompanies the discovery of new knowledge is nature’s way of telling us that the desire to know is as important as the drive to reproduce. As Aristotle articulated in the opening line of his book Metaphysics, understanding how the world works is a basic human need.

As a schoolkid, science very quickly drew me into its outstretched arms. I fell in love with its extraordinary power to tell us so much about the universe. The fantastic stories that my science teachers told seemed even more fanciful than the fiction I’d been reading at home. As it worked its spell on me I consumed every outlet of science I could get my hands on.

I persuaded my parents to buy me a subscription to New Scientist. I devoured Scientific American in our local library. I hogged the television each week to watch episodes of my favourite science programmes: Horizon and Tomorrow’s World. I was captivated by Jacob Bronowski’s Ascent of Man, Carl Sagan’s Cosmos, Jonathan Miller’s Body in Question. Every Christmas the Royal Institution Christmas Lectures provided a good dollop of science alongside our family turkey. My stocking was stuffed with books by Gamow and Feynman. It was a heady time, with new breakthroughs being announced each week.

Alongside reading these stories of the discovery of things we know, I began to get more fired up by the untold tales. What we knew lay in the past but what we didn’t yet know was the future, my future. I became obsessed with the puzzle books of mathematician Martin Gardner that my maths teacher gave me. The excitement of wrestling with a conundrum and the sudden release of euphoria as I cracked each puzzle got me addicted to the drug of discovery. Those puzzles were my training ground for the greater challenge of tackling questions that didn’t have an answer in the back of the book. It was the unanswered questions, the mathematical mysteries and scientific puzzles that no one had cracked that would become the fuel for my life as a scientist.

WHAT WE KNOW

If I look back to the Seventies when I was at school and compare the things that we knew then to what we know now, it is quite extraordinary how much more we have understood about the universe even in the half century that I’ve been alive. Technology has extended our senses so we can see things that were beyond the conception of the scientists who excited me as a kid.

The new range of telescopes that look out at the night sky have discovered planets like the Earth that could be home to intelligent life. They have revealed the amazing fact that three-quarters of the way into the lifetime of our universe the expansion of the universe started to accelerate. I remember reading as a kid that we were in for a big crunch, but now it seems that we have a completely different future waiting for us.

The particle colliders like the Large Hadron Collider at CERN (the European Organization for Nuclear Research in Switzerland) have allowed us to penetrate the inner workings of matter itself, revealing new particles – like the top quark discovered in 1994 and the Higgs boson discovered in 2012 – that were bits of speculative mathematics when I was reading my New Scientist at school.

And since the early Nineties the fMRI scanner has allowed us to look inside the brain and discover things that in the Seventies were frankly not even considered part of the remit of scientists. The brain was the preserve of philosophers and theologians, but today the technology can reveal when you are thinking about Jennifer Aniston or predict what you are going to do next even before you know.

Biology has seen an explosion of breakthroughs. In 2003 it was announced that scientists had mapped one whole human DNA sequence consisting of 3 billion letters of genetic code. In 2011 the complete neuronal network of the C. elegans worm was published, providing a complete picture of how the 302 neurons in the worm are connected.

Chemists too have been breaking new territory. A totally new form of carbon was discovered in 1985, which binds together like a football, and chemists surprised us again in 2003 by creating the first examples of graphene, showing how carbon can form a honeycomb lattice one atom thick.

And in my lifetime the subject to which I would eventually dedicate myself, mathematics, has seen some of the great enigmas finally resolved: Fermat’s Last Theorem and the Poincaré conjecture, two challenges that had outfoxed generations of mathematicians. New mathematical tools and insights have opened up hidden pathways to navigate the mathematical universe.

Keeping up with all these new advances, let alone making your own contribution, is a challenge in its own right.

THE KNOW-IT-ALL PROFESSORSHIP

A few years ago I got a new job title to add to my role as a professor of mathematics at the University of Oxford. It often makes me laugh: the Simonyi Professor for the Public Understanding of Science. There seems to be a belief that with such a title I should know it all. People ring me up expecting that I know the answers to every question of science. Shortly after I’d taken on the job, the Nobel Prize for medicine was announced. A journalist called, hoping for an explanation of the breakthrough that was being rewarded: the discovery of telomeres.

Biology has never been my strong point, but I was sitting in front of my computer screen and so I’m embarrassed to admit I got the Wikipedia page up on telomeres and, after a quick scan, proceeded to explain authoritatively that they are the bit of genetic code at the end of our chromosomes that controls ageing among other things. The technology we have at our fingertips has increased that sense that we have the potential to know anything. Just tap my question into a search engine and the device seems to predict, even before I’ve finished typing, what it is I want to know and provides a list of places to find the answer.

But understanding is different from a list of facts. Is it possible for any scientist to know it all? To know how to solve non-linear partial differential equations? To know how SU(3) governs the connection between fundamental particles? To know how cosmological inflation gives rise to the state of the universe? To know how to solve Einstein’s equations of general relativity or Schrödinger’s wave equation? To know how neurons and synapses trigger thought? Newton, Leibniz and Galileo were perhaps the last scientists to know all that was known.

I must admit that the arrogance of youth infused me with the belief that I could understand anything that was known. If someone’s human brain out there has found a way to navigate a path to new knowledge, then if the proof works in their brain it should work in mine. With enough time, I thought, I could crack the mysteries of mathematics and the universe, or at least master the current lie of the land. But increasingly I am beginning to question that belief, to worry that some things will forever remain beyond my reach. Often my brain struggles to navigate the science we currently know. Time is running out to know it all.

My own mathematical research is already pushing the limits of what my human brain feels capable of understanding. I have been working for over ten years on a conjecture that remains stubbornly resistant to my attempts to crack it. But my new role as the Professor for the Public Understanding of Science has pushed me outside the comfort zone of mathematics into the messy concepts of neuroscience, the slippery ideas of philosophy, the unfounded theories of physics. It has required a different way of thinking that is alien to my mathematical mode of thought, which deals in certainties, proofs and precision. My attempts to understand everything that is currently regarded as scientific knowledge has severely tested the limits of my own ability to understand.

The process of attaining knowledge necessarily relies on our standing on the shoulders of giants, as Newton famously declared about his own breakthroughs. And so my own journey to the edges of knowledge has involved reading how others have articulated the current state of knowledge, listening to lectures and seminars by those immersed in the field I’m trying to understand, talking to those pushing the boundaries, questioning contradictory stories, consulting the evidence and data recorded in the scientific journals that support a theory, even at times looking up an idea on Wikipedia. Although we teach students to question any information that pops up from a Google search, research has revealed that Wikipedia’s accounts of topics at the less controversial end of the scientific spectrum, like the theory of general relativity, are regarded as on a par with accounts in the scientific literature. Choose a more contested issue, like climate change, and the content might depend on what day you look.

This raises the question of how much can you trust any of these stories. Just because the scientific community accepts a story as the current best fit, this doesn’t mean it is true. Time and again, history reveals the opposite to be the case, and this must always act as a warning that current scientific knowledge is provisional. Mathematics perhaps has a slightly different quality, as I will discuss in the final two chapters. Mathematical proof provides the chance to establish a more permanent state of knowledge. But it’s worth noting that even when I am creating new mathematics, I will often quote results by fellow mathematicians whose proofs I won’t have checked myself. To do so would mean running in order to keep still.

And for any scientist the real challenge is not to stay within the secure garden of the known but to venture out into the wilds of the unknown. That is the challenge at the heart of this book.

WHAT WE DON’T KNOW

Despite all the breakthroughs made in science over the last centuries, there are still lots of deep mysteries waiting out there for us to solve. Things we don’t know. The knowledge of what we are ignorant of seems to expand faster than our catalogue of breakthroughs. The known unknowns outstrip the known knowns. And it is those unknowns that drive science. A scientist is more interested in the things he or she can’t understand than in telling all the stories we already know how to narrate. Science is a living, breathing subject because of all those questions we can’t answer.

For example, the stuff that makes up the physical universe we interact with seems to account for only 4.9% of the total matter content of our universe. So what is the other 95.1% of so-called dark matter and dark energy made up of? If our universe’s expansion is accelerating, where is all the energy coming from that is fuelling that acceleration?

Is our universe infinite? Are there infinitely many other infinite universes parallel to our own? If there are, do they have different laws of physics? Were there other universes before our own universe emerged from the Big Bang? Did time exist before the Big Bang? Does time exist at all or does it emerge as a consequence of more fundamental concepts?

Why is there a layer of fundamental particles with another two almost identical copies of this layer but with increasing mass, the so-called three generations of fundamental particles? Are there yet more particles out there for us to discover? Are fundamental particles actually tiny strings vibrating in 11-dimensional space?

How can we unify Einstein’s theory of general relativity, the physics of the very large, with quantum physics, the physics of the very small? This is the search for something called quantum gravity, an absolute necessity if we are ever going to understand the Big Bang, when the universe was compressed into the realm of the quantum.

And what of the understanding of our human body, something so complex that it makes quantum physics look like a high-school exercise. We are still trying to get to grips with the complex interaction between gene expression and our environment. Can we find a cure for cancer? Is it possible to beat ageing? Could there be someone alive today who will live to be a 1000 years old?

And what about where humans came from? Evolution is a process of random mutations, so would a different roll of the evolutionary dice still produce organisms with eyes? If we rewound evolution and pressed ‘play’, would we get intelligent life, or are we the result of a lucky roll of the dice? Is there intelligent life elsewhere in our universe? And what of the technology we are creating? Can a computer ever attain consciousness? Will I eventually be able to download my consciousness so that I can survive the death of my body?

Mathematics too is far from finished. Despite popular belief, Fermat’s Last Theorem was not the last theorem. Mathematical unknowns abound. Are there any patterns in prime numbers or are they outwardly random? Will we be able to solve the mathematical equations for turbulence? Will we ever understand how to factorize large numbers efficiently?

Despite so much that is still unknown, scientists are optimistic that these questions won’t remain unanswered forever. The last few decades give us reason to believe that we are in a golden age of science. The rate of discoveries in science appears to grow exponentially. In 2014 the science journal Nature reported that the number of scientific papers published has been doubling every nine years since the end of the Second World War. Computers too are developing at an exponential rate. Moore’s law is the observation that computer processing power seems to double every two years. Engineer Ray Kurzweil believes that the same applies to technological progress: that the rate of change of technology over the next 100 years will be comparable to what we’ve experienced in the last 20,000 years.

And yet can scientific discoveries maintain this exponential growth? Kurzweil talks about the Singularity, a moment when the intelligence of our technology will exceed our human intelligence. Is scientific progress destined for its own singularity? A moment when we know it all. Surely at some point we might actually discover the underlying equations that explain how the universe works. We will discover the final list of particles that make up the building blocks of the physical universe and how they interact with each other. Some scientists believe that the current rate of scientific progress will lead to a moment when we might discover a theory of everything. They even give it a name: ToE.

As Hawking declared in A Brief History of Time: ‘I believe there are grounds for cautious optimism that we may be near the end of the search for the ultimate laws of nature’, concluding dramatically with the provocative statement that then ‘we would know the mind of God’.

Is such a thing possible? To know everything? Would we want to know everything? Science would ossify. Scientists have a strangely schizophrenic relationship with the unknown. On the one hand, it is what we don’t know that intrigues and fascinates us, and yet the mark of success as a scientist is resolution and knowledge, to make the unknown known.

Could there be some quests that will never be resolved? Are there limits to what we can discover about our physical universe? Are some regions of the future beyond the predictive powers of science and mathematics? Is time before the Big Bang a no-go area? Are there ideas so complex that they are beyond the conception of our finite human brains? Can brains even investigate themselves, or does the analysis enter an infinite loop from which it is impossible to rescue itself? Are there mathematical conjectures that can never be proved true?

WHAT WE’LL NEVER KNOW

What if there are questions of science that can never be resolved? It seems defeatist, even dangerous, to admit there may be any such questions. While the unknown is the driving force for doing science, the unknowable would be science’s nemesis. As a fully signed-up member of the scientific community, I hope that we can ultimately answer the big open questions. So it seems important to know if the expedition I’ve joined will hit boundaries beyond which we cannot proceed. Questions that won’t ever get closure.

That is the challenge I’ve set myself in this book. I want to know if there are things that by their very nature we will never know. Are there things that will always be beyond the limits of knowledge? Despite the marauding pace of scientific advances, are there things that will remain beyond the reach of even the greatest scientists? Will there remain mysteries that will resist our attempts to lift the veils that currently mask our view of the universe?

It is, of course, very risky at any point in history to try to articulate Things We Cannot Know. How can you know what new insights are suddenly going to pull the unknown into the knowable? This is partly why it is useful to look at the history of how we know the things we do, because it reveals how often we’ve been at points where we think we have hit the frontier, only to find some way across.

Take the statement made by French philosopher Auguste Comte in 1835 about the stars: ‘We shall never be able to study, by any method, their chemical composition or their mineralogical structure.’ An absolutely fair statement given that this knowledge seemed to depend on our visiting the star. What Comte hadn’t factored in was the possibility that the star could visit us, or at least that photons of light emitted by the star could reveal its chemical make-up.

A few decades after Comte’s prophecy, scientists had determined the chemical composition of our own star, the Sun, by analysing the spectrum of light emitted. As the nineteenth-century British astronomer Warren de la Rue declared: ‘If we were to go to the Sun, and to bring some portions of it and analyse them in our laboratories, we could not examine them more accurately than we can by this new mode of spectrum analysis.’

Scientists went on to determine the chemical composition of stars we are unlikely ever to visit. As science in the nineteenth century continued to give us an ever greater understanding of the mysteries of the universe, there began to emerge a feeling that we might eventually have a complete picture.

In 1900 Lord Kelvin, regarded by many as one of the greatest scientists of his age, believed that moment had come when he declared to the meeting of the British Association of Science: ‘There is nothing new to be discovered in physics now. All that remains is more and more precise measurement.’ American physicist Albert Abraham Michelson concurred. He too thought that the future of science would simply consist of adding a few decimal places to the results already obtained. ‘The more important fundamental laws and facts of physical science have all been discovered … our future discoveries must be looked for in the sixth place of decimals.’

Five years later Einstein announced his extraordinary new conception of time and space, followed shortly after by the revelations of quantum physics. Kelvin and Michelson couldn’t have been more wrong about how much new physics there was still to discover.

What I want to try to explore is whether there are problems that we can prove will remain beyond knowledge despite any new insights. Perhaps there are none. As a scientist that is my hope. One of the dangers when faced with currently unanswerable problems is to give in too early to their unknowability. But if there are unanswerables, what status do they have? Can you choose from the possible answers and it won’t really matter which one you opt for?

Talk of known unknowns is not reserved to the world of science. The US politician Donald Rumsfeld strayed into the philosophy of knowledge with the famous declaration:

There are known knowns; there are things that we know that we know. We also know there are known unknowns; that is to say, we know there are some things we do not know. But there are also unknown unknowns, the ones we don’t know we don’t know.

Rumsfeld received a lot of stick for this cryptic response to a question fired at him during a briefing at the Department of Defense about the lack of evidence connecting the government of Iraq with weapons of mass destruction. Journalists and bloggers had a field day, culminating in Rumsfeld being given the Foot in Mouth award by the Plain English Campaign. And yet if one unpicks the statement, Rumsfeld very concisely summed up different types of knowledge. He perhaps missed one interesting category: The unknown knowns. The things that you know yet dare not admit to knowing. As the philosopher Slavoj Zizek argues, these are possibly the most dangerous, especially when held by those with political power. This is the domain of delusion. Repressed thoughts. The Freudian unconscious.

I would love to tell you about the unknown unknowns, but then they’d be known! Nassim Taleb, author of The Black Swan, believes that it is the emergence of these that are responsible for the biggest changes in society. For Kelvin it was relativity and quantum physics that turned out to be the unknown unknown that he was unable to conceive of. So in this book I can at best try to articulate the known unknowns and ask whether any will remain forever unknown. Are there questions that by their very nature will always be unanswerable, regardless of progress in knowledge?

I have called these unknowns ‘Edges’. They represent the horizon beyond which we cannot see. My journey to the Edges of knowledge to articulate the known unknowns will pass through the known knowns that demonstrate how we have travelled beyond what we previously thought were the limits of knowledge. This journey will also test my own ability to know, because it’s becoming increasingly challenging as a scientist to know even the knowns.

As much as this book is about what we cannot know, it is also important to understand what we do know and how we know it. My journey to the limits of knowledge will take me through the terrain that scientists have already mapped, to the very limits of today’s cutting-edge breakthroughs. On the way I will stop to consider those moments when scientists thought they had hit a wall beyond which progress was no longer possible, only for the next generation to find a way, and this will give us an important perspective on those problems that we might think are unknowable today. By the end of our journey I hope this book will provide a comprehensive survey not just of what we cannot know but also of the things we do know.

To help me through those areas of science that are outside my comfort zone, I have enlisted the help of experts to guide me as I reach each science’s Edge and to test whether it is my own limitations, or limitations inherent in the questions I am tackling, that make them unknowable.

What happens then if we encounter a question that cannot be answered? How does one cope with not knowing? Dare I admit to myself that some things will forever remain beyond my reach? How do we as a species cope with not knowing? That is a challenge that has elicited some interesting responses from humans across the millennia, not least the creation of an idea called God.

TRANSCENDENCE

There is another reason why I have been driven to investigate the unknowable, which is also related to my new job. The previous incumbent of the chair for the Public Understanding of Science was a certain Richard Dawkins. When I took over the position from Dawkins I braced myself for the onslaught of questions that I would get, not about science, but about religion. The publication of The God Delusion and his feisty debates with creationists resulted in Dawkins spending a lot of the later years of his tenure debating questions of religion and God.

So it was inevitable that when I took up the chair people would be interested in my stance on religion. My initial reaction was to put some distance between myself and the debate about God. My job was to promote scientific progress, and to engage the public in the breakthroughs happening around them. I was keen to move the debate back to questions of science rather than religion.

As a strategy to deflect the God questions I actually admitted that I was in fact a religious man. Before journalists got too excited, I went on to explain that my religion is the Arsenal. My temple is the Emirates (it used to be Highbury Stadium) in north London, and each Saturday I worship my idols and sing songs to them. And at the beginning of each season I reaffirm my faith that this will be the year we finally win some silverware. In an urban environment like London, football has taken over the role that religion played in society of binding a community together, providing rituals that they can share.

For me, the science that I began to learn as a teenager did a pretty good job of pushing out any vaguely religious thoughts I had had as a kid. I sang in my local church choir, which exposed me to the ideas that Christianity had to offer for understanding the universe. School education in the Seventies in the UK was infused with mildly religious overtones: renditions of ‘All Things Bright and Beautiful’ and the Lord’s Prayer in assemblies. Religion was dished up as something too simplistic to survive the sophisticated and powerful stories that I would learn in the science labs at my secondary school. Religion was quickly pushed out. Science … and football … were much more attractive.

Inevitably the questions about my stance on religion would not be fobbed off with such a flippant answer. I remember that during one radio interview on a Sunday morning on BBC Northern Ireland I was gradually sucked into considering the question of the existence of God. I guess I should have seen the warning signs. On a Sunday morning in Northern Ireland, God isn’t far from the minds of many listeners.

As a mathematician I am often faced with the challenge of proving the existence of new structures or coming up with arguments to show why such structures cannot exist. The power of the mathematical language to produce logical arguments has led a number of philosophers throughout the ages to resort to mathematics as a way of proving the existence of God. But I always have a problem with such an approach. If you are going to prove existence or otherwise in mathematics, you need a very clear definition of what it is that you are trying to prove exists.

So after some badgering by the interviewer about my stance on the existence of God, I pushed him to try to define what God meant for him so that I could engage my mathematical mind. ‘It is something which transcends human understanding.’ At first I thought: what a cop-out. You have just defined it as something which by its very nature I can’t get a handle on. But I became intrigued by this as a definition. Perhaps it wasn’t such a cop-out after all.

What if you define God as the things we cannot know. The gods in many ancient cultures were always a placeholder for the things we couldn’t explain or couldn’t understand. Our ancestors found volcanic eruptions or eclipses so mysterious that they became acts of gods. As science has explained such phenomena, these gods have retreated.

This definition has some things in common with a God commonly called the ‘God of the gaps’. This phrase was generally used as a derogatory term by religious thinkers who could see that this God was shrinking in the face of the onslaught of scientific knowledge, and a call went out to reject this kind of God. The phrase ‘God of the gaps’ was coined by the Oxford mathematician and Methodist church leader Charles Coulson, when he declared: ‘There is no “God of the gaps” to take over at those strategic places where science fails.’

But the phrase is also associated with a fallacious argument for the existence of God, one that Richard Dawkins spends some time shooting down in The God Delusion: if there are things that we can’t explain or know, there must be a God at work filling the gap. But I am more interested not in the existence of a God to fill the gap, but in equating God with the abstract idea of the things we cannot know. Not in the things we currently don’t know, but the things that by their nature we can never know. The things that will always remain transcendent.

Religion is more complex than the simple stereotype often offered up by modern society. For many ancient cultures in India, China and the Middle East, religion was not about worshipping a Supernatural Intelligence but precisely the attempt to appreciate the limits of our understanding and language. As the theologian Herbert McCabe declared: ‘To assert the existence of God is to claim that there is an unanswered question about the universe.’ Science has pushed hard at those limits. So is there anything left? Will there be anything that will always be beyond the limit. Does McCabe’s God exist?

This is the quest at the heart of this book. Can we identify questions or physical phenomena that will always remain beyond knowledge? If we can identify things that will remain in the gaps of knowledge, then what sort of God is this? What potency would such a concept have? Could the things we cannot know act in the world and affect our futures? Are they worthy of worship?

But first we need to know if in fact there is anything that will remain unanswered about the universe. Is there really anything we cannot know?

FIRST EDGE: THE CASINO DICE

1

The unpredictable and the predetermined unfold together to make everything the way it is. It’s how nature creates itself, on every scale, the snowflake and the snowstorm. It makes me so happy. To be at the beginning again, knowing almost nothing.

Tom Stoppard, Arcadia

There is a single red dice sitting on my desk next to me. I got the dice on a trip to Las Vegas. I fell in love with it when I saw it on the craps table. It was so perfectly engineered. Such precise edges coming to a point at the corners of the cube. The faces so smooth you couldn’t feel what number the face was representing. The pips are carved out of the dice and then filled with paint that has the same density as the plastic used to make the dice. This ensures that the face representing the 6 isn’t a touch lighter than the face on the opposite side with a single pip. The feeling of the dice in the hand is incredibly satisfying. It is a thing of beauty.

And yet I hate it.

It’s got three pips pointing up at me at the moment. But if I pick it up and let it fall from my hand I have no way of knowing how it is going to land. It is the ultimate symbol of the unknowable. The future of the dice seems knowable only when it becomes the past.

I have always been extremely unsettled by things that I cannot know. Things that I cannot work out. I don’t mind not knowing something provided there is some way ultimately to calculate what’s going on. With enough time. Is this dice truly so unknowable? Or with enough information can I actually deduce its next move? Surely it’s just a matter of applying the right laws of physics and solving the appropriate mathematical equations. Surely this is something I can know.

My subject, mathematics, was invented to give people a glimpse of what’s out there coming towards us. To look into the future. To become masters of fate, not its servants. I believe that the universe runs according to laws. Understand those laws and I can know the universe. Spotting patterns has given the human species a very powerful way to take control. If there’s a pattern then I have some chance to predict the future and know the unknowable. The pattern of the Sun means I can rely on it rising in the sky tomorrow or the Moon taking 28 sunrises before it becomes full again. It is how mathematics developed. Mathematics is the science of patterns. Being able to spot patterns is a powerful tool in the evolutionary fight for survival. The caves in Lascaux show how counting 13 quarters of the Moon from the first winter rising of the Pleiades will bring you to a time in the year when the horses are pregnant and easy to hunt. Being able to predict the future is the key to survival.

But there are some things which appear to have no pattern or that have patterns that are so complex or hidden that they are beyond human knowledge. The individual roll of the dice is not like the rising of the Sun. There seems to be no way to know which of the six faces will be pointing upwards once the cube finally comes to rest. It is why the dice has been used since antiquity as a way to decide disputes, to play games, to wager money.

Is that beautiful red cube with its white dots truly unknowable? I’m certainly not the first to have a complex relationship with the dynamics of this cube.

KNOWING THE WILL OF THE GODS

On a recent trip to Israel I took my children to an archaeological dig at Beit Guvrin. It was such a popular settlement in ancient times that the site consists of layer upon layer of cities built on top of each other. There is so much stuff in the ground that the archaeologists are happy to enlist amateurs like me and my kids to help excavate the site even if a few pots get broken along the way. Sure enough, we pulled out lots of bits of pottery. But we also kept unearthing a large number of animal bones. We thought they were the remains of dinner, but our guide explained that in fact they were the earliest form of dice.

Archaeological digs of settlements dating back to Neolithic times have revealed a disproportionately high density of heel bones of sheep or other animals among the shattered pottery and flints that are usually found in sites that humans once inhabited. These bones are in fact ancestors of my casino dice. When thrown, the bones naturally land on one of four sides. Often there are letters or numbers carved into the bones. Rather than gambling, these early dice are thought to have been used for divination. And this connection between the outcome of the roll of a dice and the will of the gods is one that has persisted for centuries. Knowledge of how the dice would land was believed to be something that transcended human understanding. Its outcome was in the lap of the gods.

Increasingly these dice assumed a more prosaic place as part of our world of leisure. The first cube-shaped dice like the one on my desk were found around Harappa in what is now northeast Pakistan, where one of the first urban civilizations evolved, dating back to the third millennium BC. At the same time, you find four-faced pyramid dice appearing in a game that was discovered in the city of Ur, in ancient Mesopotamia.

The Romans and Greeks were addicts of games of dice, as were the soldiers of the medieval era who returned from the Crusades with a new game called hazard, deriving from the Arabic word for a dice: al-zahr. It was an early version of craps, the game that was being played in the casino in Vegas where I picked up my dice.

If I could predict the fall of the dice, all the games that depend on them would never have caught on. The excitement of backgammon or hazard or craps comes from not knowing how the dice are going to land. So perhaps gamers won’t thank me as I try to predict the roll of my dice.

For centuries no one even thought that such a feat was possible. The ancient Greeks, who were among the first to develop mathematics as a tool to navigate their environment, certainly didn’t have any clue how to tackle such a dynamic problem. Their mathematics was a static, rigid world of geometry, not one that could cope with the dice tumbling across the floor. They could produce formulas to describe the geometric contours of the cube, but once the dice started moving they were lost.

What about doing experiments to get a feel for the outcomes? The anti-empiricist attitude of the ancient Greeks meant they had no motivation to analyse the data and try to make a science of predicting how the dice would land. After all, the way the dice had just landed was going to have no bearing on the next throw. It was random and for the ancient Greeks that meant it was unknowable.

Aristotle believed that events in the world could essentially be classified into three categories: ‘certain events’ that happen by necessity following the laws of nature; ‘probable events’ that happen in most cases but can have a few exceptions; and finally ‘unknowable events’ that happened by pure chance. Aristotle put my dice firmly in the last category.

As Christian theology made its impact on philosophy, matters worsened. Since the throw of the dice was in the hands of God, it was not something that humans could aspire to know. As St Augustine had it: ‘We say that those causes that are said to be by chance are not non-existent but are hidden, and we attribute them to the will of the true God.’

There was no chance. No free will. The unknowable was known by God, who determined the outcome of the dice. Any attempt to try to predict the roll was the work of a heretic, someone who dared to think they could know the mind of God. King Louis XI of France even went as far as prohibiting the manufacture of dice, believing that games of chance were ungodly. But the dice like the one I have on my desk eventually began to yield their secrets. It took till the sixteenth century before dice were wrestled out of the hands of God and their fate put in the hands, and minds, of humans.

FINDING THE NUMBERS IN THE DICE

I’ve put another two dice next to my beautiful Las Vegas dice. So here’s a question: if I throw all three dice, is it better to bet on a score of 9 or a score of 10 coming up? Prior to the sixteenth century there were no tools available to answer such a question. And yet anyone who had played for long enough would know that if I was throwing only two dice then it would be wise to bet on 9 rather than 10. After all, experience would tell you before too long that on average you get 9 a third more often than you get 10. But with three dice it is harder to get a feel for which way to bet, because 9 and 10 seem to occur equally often. But is that really true?

It was in Italy at the beginning of the sixteenth century that an inveterate gambler by the name of Girolamo Cardano first realized that there are patterns that can be exploited in the throw of a dice. They weren’t patterns that could be used on an individual throw. Rather, they emerged over the long run, patterns that a gambler like Cardano, who spent many hours throwing dice, could use to his advantage. So addicted was he to the pursuit of predicting the unknowable that on one occasion he even sold his wife’s possessions to raise the funds for the table stakes.

Cardano had the clever idea of counting how many different futures the dice could have. If I throw two dice, there are 36 different futures. They are depicted in the following diagram.

Only in three of them is the total 10, while four give you a score of 9. So Cardano reasoned that, in the case of two dice being thrown, it makes sense to bet on 9 rather than 10. It did not help in any individual game, but in the long run it meant that Cardano, if he stuck to his maths, would come out on top. Unfortunately, while a disciplined mathematician, he wasn’t very disciplined when it came to his gambling. He managed to lose all the inheritance from his father and would get into knife fights with his opponents when the dice went against him.

He was nevertheless determined to get one prophecy correct. He had apparently predicted the date of his death: 21 September 1576. To make sure he got this bet right he took matters into his own hands. He committed suicide when the date finally struck. As much as I crave knowledge, I think this is going a little far. Indeed, the idea of knowing the date of your death is something that most would prefer to opt out of. But Cardano was determined to win, even when he was dicing with Death.

Before taking his life, he wrote what many regard as the first book that made inroads into predicting the behaviour of the dice as it rolls across the table. Although written around 1564, Liber de Ludo Aleae didn’t see the light of day until it was eventually published in 1663.

It was in fact the great Italian physicist Galileo Galilei who applied the same analysis that Cardano had described to decide whether to bet on a score of 9 or 10 when three dice are thrown. He reasoned that there are 6 × 6 × 6 = 216 different futures the dice could take. Of these, 25 gave you a 9 while 27 gave you a 10. Not a big difference, and one that would be difficult to pick up from empirical data, but large enough that betting on 10 should give you an edge in the long run.

AN INTERRUPTED GAME

The mathematical mastery of the dice shifted from Italy to France in the mid-seventeenth century when two big hitters, Blaise Pascal and Pierre de Fermat, started applying their minds to predicting the future of these tumbling cubes. Pascal had become interested in trying to understand the roll of the dice after meeting one of the great gamblers of the day, Chevalier de Méré. De Méré had challenged Pascal with a number of interesting scenarios. One was the problem Galileo had cracked. But the others included whether it was advisable to bet that at least one 6 will appear if a dice is thrown four times, and also the now famous problem of ‘points’.

Pascal entered into a lively correspondence with the great mathematician and lawyer Pierre de Fermat in which they tried to sort out the problems set by de Méré. With the throw of four dice, one could consider the 6 × 6 × 6 × 6 = 1296 different outcomes and count how many include a 6, but that becomes pretty cumbersome.

Instead, Pascal reasoned that there is a ⁵⁄₆ chance that you won’t see a 6 with one throw. Since each throw is independent, that means there is a ⁵⁄₆ × ⁵⁄₆ × ⁵⁄₆ × ⁵⁄₆ = ⁶²⁵⁄₁₂₉₆ = 48.2% chance that you won’t get a 6 in four throws. Which means there is a 51.8% chance that you will see a 6. Just above an evens chance, so worth betting on.

The problem of ‘points’ was even more challenging. Suppose two players – let’s call them Fermat and Pascal – are rolling a dice. Fermat scores a point if the dice lands on 4 or higher; Pascal scores a point otherwise. Each, therefore, has a 50:50 chance of winning a point on any roll of the dice. They’ve wagered £64, which will go to the first to score 3 points. The game is interrupted, however, and can’t be continued, when Fermat is on 2 points and Pascal is on 1 point. How should they divide the £64?

Traditional attempts to solve the problem focused on what had happened in the past. Maybe, having won twice as many rounds as Pascal, Fermat should get twice the winnings. This makes no sense if, say, Fermat had won only one round before the game was interrupted. Pascal would get nothing but still has a chance of winning. Niccolò Fontana Tartaglia, a contemporary of Cardano, believed after much thought that it had no solution: ‘The resolution of the question is judicial rather than mathematical, so that in whatever way the division is made there will be cause for litigation.’

Others weren’t so defeated. Attention turned not to the past, but to what could happen in the future. In contrast to the other problems, they are not trying to predict the roll of the dice but instead need to imagine all the different future scenarios and to divide the spoils according to which version of the future favours which player.

It is easy to get fooled here. There seem to be three scenarios. Fermat wins the next round and pockets £64. Pascal wins the next round, resulting in a final round which either Pascal wins or Fermat wins. Fermat wins in two out of these three scenarios so perhaps he should get two-thirds of the winnings. It was the trap that de Méré fell into. Pascal argues that this isn’t correct. ‘The Chevalier de Méré is very talented but he is not a mathematician; this is, as you know, a great fault.’ A great fault, indeed!

Pascal, in contrast, was great on the mathematical front and argued that the spoils should be divided differently. There is a 50:50 chance that Fermat wins in one round, in which case he gets £64. But if Pascal wins the next round then they are equally likely to win the final round, so could divide the spoils £32 each. In either case Fermat is guaranteed £32. So the other £32 should be split equally, giving Fermat £48 in total.

Fermat, writing from his home near Toulouse, concurred with Pascal’s analysis: ‘You can now see that the truth is the same in Toulouse as in Paris.’

PASCAL’S WAGER

Pascal and Fermat’s analysis of the game of points could be applied to much more complex scenarios. Pascal discovered that the secret to deciding the division of the spoils is hidden inside something now known as Pascal’s triangle.

The triangle is constructed in such a way that each number is the sum of the two numbers immediately above it. The numbers you get are key to dividing the spoils in any interrupted game of points. For example, if Fermat needs 2 points for a win while Pascal needs 4, then you consult the 2 + 4 = 6th row of the triangle and add the first four numbers together and the last two. This is the proportion in which you should divide the spoils. In this case it’s a 1 + 5 + 10 + 10 = 26 to 1 + 5 = 6 division. So Fermat gets ²⁶⁄₃₂ × 64 = £52 and Pascal gets ⁶⁄₃₂ × 64 = £12. In general, a game where Fermat needs n points to Pascal’s m points can be decided by consulting the (n + m)th row of Pascal’s triangle.

There is evidence that the French were beaten by several millennia to the discovery that this triangle is connected to the outcome of games of chance. The Chinese were inveterate users of dice and other random methods like the I Ching to try to predict the future. The text of the I Ching dates back some 3000 years and contains precisely the same table that Pascal produced to analyse the outcomes of tossing coins to determine the random selection of a hexagram that would then be analysed for its meaning. But today the triangle is attributed to Pascal rather than the Chinese.

Pascal wasn’t interested only in dice. He famously applied his new mathematics of probability to one of the great unknowns: the existence of God.

‘God is, or He is not.’ But to which side shall we incline? Reason can decide nothing here. There is an infinite chaos which separated us. A game is being played at the extremity of this infinite distance where heads or tails will turn up … Which will you choose then? Let us see. Since you must choose, let us see which interests you least. You have two things to lose, the true and the good; and two things to stake, your reason and your will, your knowledge and your happiness; and your nature has two things to shun, error and misery. Your reason is no more shocked in choosing one rather than the other, since you must of necessity choose … But your happiness? Let us weigh the gain and the loss in wagering that God is … If you gain, you gain all; if you lose, you lose nothing. Wager, then, without hesitation that He is.

Called Pascal’s wager, he argued that the payout would be much greater if one opted for a belief in God. You lose little if you are wrong and win eternal life if correct. On the other hand, wager against the existence of God and losing results in eternal damnation, while winning gains you nothing beyond the knowledge that there is no God. The argument falls to pieces if the probability of God existing is actually 0, and even if it isn’t, perhaps the cost of belief might be too high when set against the probability of God’s existence.

The probabilistic techniques developed by mathematicians like Fermat and Pascal to deal with uncertainty were incredibly powerful. Phenomena that were regarded as beyond knowledge, the expression of the gods, were beginning to be within reach of the minds of men. Today these probabilistic methods are our best weapon in trying to navigate everything from the behaviour of particles in a gas to the ups and downs of the stock market. Indeed, the very nature of matter itself seems to be at the mercy of the mathematics of probability, as we shall discover in the Third Edge, when we apply quantum physics to predict what fundamental particles are going to do when we observe them. But for someone on the search for certainty, these probabilistic methods represent a frustrating compromise.

I certainly appreciate the great intellectual breakthrough that Fermat, Pascal and others made, but it doesn’t help me to know how many pips are going to be showing when I throw my dice. As much as I’ve studied the mathematics of probability, it has always left me with a feeling of dissatisfaction. The one thing any course on probability drums into you is that it doesn’t matter how many times in a row you get a 6: this has no influence on what the dice is going to do on the next throw.

So is there some way of knowing how my dice is going to land? Or is that knowledge always going to be out of reach? Not according to the revelations of a scientist across the waters in England.

THE MATHEMATICS OF NATURE

Isaac Newton is my all-time hero in my fight against the unknowable. The idea that I could possibly know everything about the universe has its origins in Newton’s revolutionary work Philosophiae Naturalis Principia Mathematica. First published in 1687, the book is dedicated to developing a new mathematical language that promised the tools to unlock how the universe behaves. It was a dramatically new model of how to do science. The work ‘spread the light of mathematics on a science which up to then had remained in the darkness of conjectures and hypotheses’, declared the French physicist Alexis Clairaut in 1747.

It is also an attempt to unify, to create a theory that describes the celestial and the earthly, the big and the small. Kepler had come up with laws that described the motions of the planets, laws he’d developed empirically by looking at data and trying to fit equations to create the past. Galileo had described the trajectory of a ball flying through the air. It was Newton’s genius to understand that these were examples of a single phenomenon: gravity.

Born on Christmas Day in 1643 in the Lincolnshire town of Woolsthorpe, Newton was always trying to tame the physical world. He made clocks and sundials, constructed miniature mills powered by mice, sketched countless plans for buildings and ships, and drew elaborate illustrations of animals. The family cat apparently disappeared one day, carried away by a hot-air balloon that Newton had made. His school reports, however, did not anticipate a great future, describing him as ‘inattentive and idle’.

Idleness is not necessarily such a bad trait in a mathematician. It can be a powerful incentive to look for some clever shortcut to solve a problem rather than relying on hard graft. But it’s not generally a quality that teachers appreciate.

Indeed, Newton was doing so badly at school that his mother decided the whole thing was a waste of time and that he’d be better off learning how to manage the family farm in Woolsthorpe. Unfortunately, Newton was equally hopeless at managing the family estate, so he was sent back to school. Although probably apocryphal, it is said that Newton’s sudden academic transformation coincided with a blow to the head that he received from the school bully. Whether true or not, Newton’s academic transformation saw him suddenly excelling at school, culminating in a move to study at the University of Cambridge.

When bubonic plague swept through England in 1665, Cambridge University was closed as a precaution. Newton retreated to the house in Woolsthorpe. Isolation is often an important ingredient in coming up with new ideas. Newton hid himself away in his room and thought.

Truth is the offspring of silence and meditation. I keep the subject constantly before me and wait ’til the first dawnings open slowly, by little and little, into a full and clear light.

In the isolation of Lincolnshire, Newton created a new language that could capture the problem of a world in flux: the calculus. This mathematical tool would be key to our knowing how the universe would behave ahead of time. It is this language that gives me any hope of gleaning how my casino dice might land.

MATHEMATICAL SNAPSHOTS

The calculus tries to make sense of what at first sight looks like a meaningless sum: zero divided by zero. As I let my dice fall from my hand, it is such a sum that I must calculate if I want to try to understand the instantaneous speed of my dice as it falls through the air.

The speed of the dice is constantly increasing as gravity pulls it to the ground. So how can I calculate what the speed is at any given instance of time? For example, how fast is the dice falling after one second? Speed is distance travelled divided by time elapsed. So I could record the distance it drops in the next second and that would give me an average speed over that period. But I want the precise speed. I could record the distance travelled over a shorter period of time, say half a second or a quarter of a second. The smaller the interval of time, the more accurately I will be calculating the speed. Ultimately, to get the precise speed I want to take an interval of time that is infinitesimally small. But then I am faced with calculating 0 divided by 0.

Calculus: making sense of zero divided by zero

Suppose that a car starts from a stationary position. When the stopwatch starts, the driver slams his foot on the accelerator. Suppose that we record that after t seconds the driver has covered t × t metres. How fast is the car going after 10 seconds? We get an approximation of the speed by looking at how far the car has travelled in the period from 10 to 11 seconds. The average speed during this second is (11 × 11 – 10 × 10)/1 = 21 metres per second.

But if we look at a smaller window of time, say the average speed over 0.5 seconds, we get:

(10.5 × 10.5 – 10 × 10)/0.5 = 20.5 metres per second.

Slightly slower, of course, because the car is accelerating, so on average it is going faster in the second half second from 10 seconds to 11 seconds. But now we take an even smaller snapshot. What about halving the window of time again:

(10.25 × 10.25 – 10 × 10)/0.25 = 20.25 metres per second.

Hopefully the mathematician in you has spotted the pattern. If I take a window of time which is x seconds, the average speed over this time will be 20 + x metres per second. The speed as I take smaller and smaller windows of time is getting closer and closer to 20 metres per second. So, although to calculate the speed at 10 seconds looks like I have to figure out the calculation ⁰⁄₀, the calculus makes sense of what this should mean.

Newton’s calculus made sense of this calculation. He understood how to calculate what the speed was tending towards as I make the time interval smaller and smaller. It was a revolutionary new language that managed to capture a changing dynamic world. The geometry of the ancient Greeks was perfect for a static, frozen picture of the world. Newton’s mathematical breakthrough was the language that could describe a moving world. Mathematics had gone from describing a still life to capturing a moving image. It was the scientific equivalent of how the dynamic art of the Baroque burst forth during this period from the static art of the Renaissance.

Newton looked back at this time as one of the most productive of his life, calling it his annus mirabilis. ‘I was in the prime of my age for invention and minded Mathematicks and Philosophy more than at any time since.’

Everything around us is in a state of flux, so it was no wonder that this mathematics would be so influential. But for Newton the calculus was a personal tool that helped him reach the scientific conclusions that he documents in the Principia, the great treatise published in 1687 that describes his ideas on gravity and the laws of motion.

Writing in the third person, he explains that his calculus was key to the scientific discoveries contained inside: ‘By the help of this new Analysis Mr Newton found out most of the propositions in the Principia.’ But no account of the ‘new analysis’ is published. Instead, he privately circulated the ideas among friends, but they were not ideas that he felt any urge to publish for others to appreciate.

Fortunately this language is now widely available and it is one that I spent years learning as a mathematical apprentice. But in order to attempt to know my dice I am going to need to mix Newton’s mathematical breakthrough with his great contribution to physics: the famous laws of motion with which he opens his Principia.

THE RULES OF THE GAME

Newton explains in the Principia three simple laws from which so much of the dynamics of the universe evolve.

Newton’s First Law of Motion: A body will continue in a state of rest or uniform motion in a straight line unless it is compelled to change that state by forces acting on it.

This was not so obvious to the likes of Aristotle. If you roll a ball along a flat surface it comes to rest. It looks like you need a force to keep it moving. There is, however, a hidden force that is changing the speed: friction. If I throw my dice in outer space away from any gravitational fields then the dice will indeed just carry on flying in a straight line at constant speed.

In order to change an object’s speed or direction you needed a force. Newton’s second law explained how that force would change the motion, and it entailed the new tool he’d developed to articulate change. The calculus has already allowed me to articulate what speed my dice is going at as it accelerates down towards the table. The rate of change of that speed is got by applying calculus again. The second law of Newton says that there is a direct relationship between the force being applied and the rate of change of the speed.

Newton’s Second Law of Motion: The rate of change of motion, or acceleration, is proportional to the force that is acting on it and inversely proportional to its mass.

To understand the motion of bodies like my cascading dice I need to understand the possible forces acting on them. Newton’s universal law of gravitation identified one of the principal forces that had an effect on, say, his apple falling or the planets moving through the solar system. The law states that the force acting on a body of mass m₁ by another body of mass m₂ which is a distance of r away is equal to

where G is an empirical physical constant that controls how strong gravity is in our universe.

With these laws I can now describe the trajectory of a ball flying through the air, or a planet through the solar system, or my dice falling from my hand. But the next problem occurs when the dice hits the table. What happens then? Newton has a third law which provides a clue:

Newton’s Third Law of Motion: When one body exerts a force on a second body, the second body simultaneously exerts a force equal in magnitude and opposite in direction to that of the first body.

Newton himself used these laws to deduce an extraordinary string of results about the solar system. As he wrote: ‘I now demonstrate the system of the World.’ To apply his ideas to the trajectory of the planets he began by reducing each planet to a point located at the centre of mass and assumed that all the planet’s mass was concentrated at this point. Then by applying his laws of motion and his new mathematics he successfully deduced Kepler’s laws of planetary motion.

He was also able to calculate the relative masses for the large planets, the Earth and the Sun. He explained a number of the curious irregularities in the motion of the Moon due to the pull of the Sun. He also deduced that the Earth isn’t a perfect sphere but should be squashed between the poles due to the Earth’s rotation causing a centrifugal force. The French thought the opposite would happen: that the Earth should be pointy in the direction of the poles. An expedition set out in 1733 which proved Newton – and the power of mathematics – correct.

NEWTON’S THEORY OF EVERYTHING

It was an extraordinary feat. The three laws were the seeds from which all motion of particles in the universe could potentially be deduced. It deserved to be called a Theory of Everything. I say ‘seeds’ because it required other scientists to grow these seeds and apply them to more complex settings than Newton’s solar system made up of point particles of mass. For example, in their original form the laws are not suited to describing the motion of less rigid bodies or bodies that deform. It was the great eighteenth-century Swiss mathematician Leonhard Euler who would provide equations that generalized Newton’s laws. Euler’s equations could be applied more generally to something like a vibrating string or a swinging pendulum.

More and more equations appeared that controlled various natural phenomena. Euler produced equations for non-viscous fluids. At the beginning of the nineteenth century French mathematician Joseph Fourier found equations to describe heat flow. Fellow compatriots Pierre-Simon Laplace and Siméon-Denis Poisson took Newton’s equations to produce more generalized equations for gravitation, which were then seen to control other phenomena like hydrodynamics and electrostatics. The behaviours of viscous fluids were described by the Navier–Stokes equations, and electromagnetism by Maxwell’s equations.

With the discovery of the calculus and the laws of motion, it seemed that Newton had turned the universe into a deterministic clockwork machine controlled by mathematical equations. Scientists believed they had indeed discovered the Theory of Everything. In his Philosophical Essay on Probabilities published in 1812, the mathematician Pierre-Simon Laplace summed up most scientists’ belief in the extraordinary power of mathematics to tell you everything about the physical universe.

We may regard the present state of the universe as the effect of its past and the cause of its future. An intellect which at a certain moment would know all forces that set nature in motion, and all positions of all items of which nature is composed, if this intellect were also vast enough to submit these data to analysis, it would embrace in a single formula the movements of the greatest bodies of the universe and those of the tiniest atom; for such an intellect nothing would be uncertain and the future just like the past would be present before its eyes.

This view that, in theory, the universe was knowable, both past and present, became dominant among scientists in the centuries following Newton’s great opus. It seemed as if any idea of God acting in the world had been completely removed. A God might be responsible for getting things up and running, but from that point on the equations of mathematics and physics took over.

So what of my lowly dice? Surely with the laws of motion at hand I can simply combine the geometry of the cube with the initial direction of motion and the subsequent interactions with the table to predict the outcome? I’ve written out the equations on my notepad and they look pretty daunting.

Newton too contemplated the problem of trying to predict the dice. Newton’s interest was prompted by a letter he received from Samuel Pepys. Pepys wanted Newton’s advice on which option he should back in a wager he was about to make with a friend:

(1) Throwing six dice and getting at least one 6

(2) Throwing twelve dice and getting at least two 6s

(3) Throwing eighteen dice and getting at least three 6s

Pepys was about to stake £10, the equivalent of £1000 in today’s money, and he was quite keen to get some good advice. Pepys’s intuition was that (3) was the more likely option, but Newton replied that the mathematics implied the opposite was true. He should put his money on the first option. However, it wasn’t his laws of motion and the calculus to which Newton resorted to solve the problem but the ideas developed by Fermat and Pascal.

But even if Newton could have solved the equations I’ve written out to describe the trajectory of the dice, there turned out to be another problem that could scupper any chance of knowing the future of my dice. Although Pascal was talking about his wager with God, there is an interesting line in his analysis which throws a spanner in the works when it comes to knowing the future: ‘Reason can decide nothing here. There is an infinite chaos which separated us.’

THE FATE OF THE SOLAR SYSTEM

If Newton is my hero, then French mathematician Henri Poincaré should be the villain in my drive to predict the future. And yet I can hardly blame him for uncovering one of the most devastating blows for anyone wanting to know what’s going to happen next. He was hardly very thrilled himself with the discovery, given that it cost him rather a lot of money.

Born a hundred years after Laplace, Poincaré believed, like his compatriot, in a clockwork universe, a universe governed by mathematical laws and utterly predictable. ‘If we know exactly the laws of nature and the situation of the universe at the initial moment, we can predict exactly the situation of the same universe at a succeeding moment.’

Understanding the world was Poincaré’s prime motivation for doing mathematics. ‘The mathematical facts worthy of being studied are those which, by their analogy with other facts, are capable of leading us to the knowledge of a physical law.’

Although Newton’s laws of motion had spawned an array of mathematical equations to describe the evolution of the physical world, most of them were still extremely complicated to solve. Take the equations for a gas. Think of the gas as made up of molecules crashing around like tiny billiard balls, and theoretically the future behaviour of the gas was bound up in Newton’s laws of motion. But the sheer number of balls meant that any exact solution was well beyond reach. Statistical or probabilistic methods were still by far the best tool to understand the behaviour of billions of molecules.

There was one situation where the number of billiard balls was reasonably small and a solution seemed tractable. The solar system. Poincaré became obsessed with the question of predicting what lay in store for our planets as they danced their way into the future.

Because the gravitational pull of a planet on another planet at some distance from the first planet is the same as if all the mass of the planet is concentrated at its centre of gravity, to determine the ultimate fate of the solar system one can consider planets as if they are just points in space, as Newton had done. This means that the evolution of the solar system can be described by three coordinates for each planet that locate the centre of mass in space together with three additional numbers recording the speed in each of the three dimensions of space. The forces acting on the planets are given by the gravitational forces exerted by each of the other planets. With all this information one just needs to apply Newton’s second law to map out the course of the planets into the distant future.

The only trouble is that the maths is still extremely tricky to work out. Newton had solved the behaviour of two planets (or a planet and a sun). They would follow elliptical paths, with their common focal point being the common centre of gravity. This would repeat itself periodically to the end of time. But Newton was stumped when he introduced a third planet. Trying to calculate the behaviour of a solar system consisting, say, of the Sun, the Earth and the Moon seemed simple enough, but already you are facing an equation in 18 variables: 9 for position and 9 for the speed of each planet. Newton conceded that ‘to consider simultaneously all these causes of motion and to define these motions by exact laws admitting of easy calculation exceeds, if I am not mistaken, the force of any human mind’.

The problem got a boost when King Oscar II of Norway and Sweden decided to mark his sixtieth birthday by offering a prize for solving a problem in mathematics. There are not many monarchs around the world who would choose maths problems as their way to celebrate their birthdays, but Oscar had always enjoyed the subject ever since he had excelled at it when he was a student at Uppsala University.

His majesty Oscar II, wishing to give a fresh proof of his interest in the advancement of mathematical science has resolved to award a prize on January 21, 1889, to an important discovery in the field of higher mathematical analysis. The prize will consist of a gold medal of the eighteenth size bearing his majesty’s image and having a value of a thousand francs, together with the sum of two thousand five hundred crowns.

Three eminent mathematicians convened to choose a number of suitable mathematical challenges and to judge the entries. One of the questions they posed was to establish mathematically whether the solar system was stable. Would it continue turning like clockwork, or, at some point in the future, might the Earth spiral off into space and disappear from our solar system?

To answer the question required solving the equations that had stumped Newton. Poincaré believed that he had the skills to win the prize. One of the common tricks used by mathematicians is to attempt a simplified version of the problem first to see if that is tractable. So Poincaré started with the problem of three bodies. This was still far too difficult, so he decided to simplify the problem further. Instead of the Sun, Earth and Moon, why not try to understand two planets and a speck of dust? The two planets won’t be affected by the dust particle, so he could assume, thanks to Newton’s solution, that they just repeated ellipses round each other. The speck of dust, on the other hand, would experience the gravitational force of the two planets. Poincaré set about trying to describe the path traced by the speck of dust. Some understanding of this trajectory would form an interesting contribution to the problem.

Although he couldn’t crack the problem completely, the paper he submitted was more than good enough to secure King Oscar’s prize. He’d managed to prove the existence of an interesting class of paths that would repeat themselves, so-called periodic paths. Periodic orbits were by their nature stable because they would repeat themselves over and over, like the ellipses that two planets would be guaranteed to execute.

The French authorities were very excited that the award had gone to one of their own. The nineteenth century had seen Germany steal a march on French mathematics, so the French academicians excitedly heralded Poincaré’s win as proof of a resurgence of French mathematics. Gaston Darboux, the permanent secretary of the French Academy of Sciences, declared:

From that moment on the name of Henri Poincaré became known to the public, who then became accustomed to regarding our colleague no longer as a mathematician of particular promise but as a great scholar of whom France has the right to be proud.

A SMALL MISTAKE WITH BIG IMPLICATIONS

Preparations began to publish Poincaré’s solution in a special edition of the Royal Swedish Academy of Science’s journal Acta Mathematica. Then came the moment every mathematician dreads. Every mathematician’s worst nightmare. Poincaré thought his work was safe. He’d checked every step in the proof. Just before publication, one of the editors of the journal raised a question over one of the steps in his mathematical argument.

Poincaré had assumed that a small change in the positions of the planets, a little rounding up or down here or there, was acceptable as it would result in only a small change in their predicted orbits. It seemed a fair assumption. But there was no justification given for why this would be so. And in a mathematical proof, every step, every assumption, must be backed up by rigorous mathematical logic.

The editor wrote to Poincaré for some clarification on this gap in the proof. But as Poincaré tried to justify this step, he realized he’d made a serious mistake. He wrote to Gösta Mittag-Leffler, the head of the prize committee, hoping to limit the damage to his reputation:

The consequences of this error are more serious than I first thought. I will not conceal from you the distress this discovery has caused me … I do not know if you will still think that the results which remain deserve the great reward you have given them. (In any case, I can do no more than to confess my confusion to a friend as loyal as you.) I will write to you at length when I can see things more clearly.

Mittag-Leffler decided he needed to inform the other judges:

Poincaré’s memoir is of such a rare depth and power of invention, it will certainly open up a new scientific era from the point of view of analysis and its consequences for astronomy. But greatly extended explanations will be necessary and at the moment I am asking the distinguished author to enlighten me on several important points.

As Poincaré struggled away he soon saw that he was simply mistaken. Even a small change in the initial conditions could result in wildly different orbits. He couldn’t make the approximation that he’d proposed. His assumption was wrong.

Poincaré telegraphed Mittag-Leffler to break the bad news and tried to stop the paper from being printed. Embarrassed, he wrote:

It may happen that small differences in the initial conditions produce very great ones in the final phenomena. A small error in the former will produce an enormous error in the latter. Prediction becomes impossible.

Mittag-Leffler was ‘extremely perplexed’ to hear the news.

It is not that I doubt that your memoir will be in any case regarded as a work of genius by the majority of geometers and that it will be the departure point for all future efforts in celestial mechanics. Don’t therefore think that I regret the prize … But here is the worst of it. Your letter arrived too late and the memoir has already been distributed.

Mittag-Leffler’s reputation was on the line for not having picked up the error before they’d publicly awarded Poincaré the prize. This was not the way to celebrate his monarch’s birthday! ‘Please don’t say a word of this lamentable story to anyone. I’ll give you all the details tomorrow.’

The next few weeks were spent trying to retrieve the printed copies without raising suspicion. Mittag-Leffler suggested that Poincaré should pay for the printing of the original version. Poincaré, who was mortified, agreed, even though the bill came to over 3500 crowns, 1000 crowns more than the prize he’d originally won.

In an attempt to rectify the situation, Poincaré set about trying to sort out his mistake, to understand where and why he had gone wrong. In 1890, Poincaré wrote a second, extended paper explaining his belief that very small changes could cause an apparently stable system suddenly to fly apart.

What Poincaré discovered, thanks to his error, led to one of the most important mathematical concepts of the last century: chaos. It was a discovery that places huge limits on what we humans can know. I may have written down all the equations for my dice, but what if my dice behaves like the planets in the solar system? According to Poincaré’s discovery, if I make just one small error in recording the starting location of the dice, that error could expand into a large difference in the outcome of the dice by the time it comes to rest on the table. So is the future of my Vegas dice shrouded behind the mathematics of chaos?

The chaotic path mapped out by a single planet orbiting two suns.

2

If nature were not beautiful it would not be worth knowing, and if nature were not worth knowing, life would not be worth living.

Henri Poincaré

I wasted a lot of time at university playing billiards in our student common room. I could have pretended that it was all part of my research into angles and stuff, but the truth is that I was procrastinating. It was a good way of putting off having to cope with not being able to answer that week’s set of problems. But in fact the billiard table hides a lot of interesting mathematics in its contours. Mathematics that is highly relevant to my desire to understand my dice.

If I shoot a ball round a billiard table and mark its path, then follow that by shooting another ball off in very nearly the same direction, the second ball will trace out a very similar path to the first ball. Poincaré had believed that the same principle applied to the solar system. Fire a planet off in a slightly different direction then the solar system will evolve in a very similar pattern. This is most people’s intuition: if I make a small change in the initial conditions of the planet’s trajectory it won’t alter the course of the planet much. But the solar system seems to be playing a slightly more interesting game of billiards than the one I played as a student.

Rather surprisingly, if I change the shape of the billiard table this intuition turns out to be wrong. For example, fire balls round a billiard table shaped like a stadium with semicircular ends but straight sides and the paths can diverge dramatically even though they started in almost the same direction. This is the signature of chaos: sensitivity to very small changes in the initial conditions.

Two quickly diverging paths taken by a billiard ball round a stadium-shaped billiard table.

So the challenge for me is to determine whether the fall of my dice is predictable, like a conventional game of billiards, or whether the dice is playing a game of chaotic billiards.

THE DEVIL IN THE DECIMALS

Despite Poincaré being credited as the father of chaos, it is striking that this sensitivity of many dynamical systems to small changes was not very well known for decades into the twentieth century. Indeed, it really took the rediscovery of the phenomenon by scientist Edward Lorenz, when he, like Poincaré, thought he’d made some mistake, before the ideas of chaos became more widely known.

While working as a meteorologist at MIT in 1963, Lorenz had been running equations for the change of temperature in a dynamic fluid on his computer when he decided he needed to rerun one of his models for longer. So he took some of the data that had been output earlier in the run and re-entered it, expecting to be able to restart the model from that point.

When he returned from coffee, he discovered to his dismay that the computer hadn’t reproduced the previous data but had generated very quickly a wildly divergent prediction for the change in temperature. At first he couldn’t understand what was happening. If you input the same numbers into an equation, you don’t expect to get a different answer at the other end. It took him a while to realize what was going on: he hadn’t input the same numbers. The computer printout of the data he’d used had only printed the numbers to three decimal places, while it had been calculating using the numbers to six decimal places.

Even though the numbers were actually different, they differed only in the fourth decimal place. You wouldn’t expect it to make that big a difference, but Lorenz was struck by the impact such a small difference in the numbers had on the resulting data. Here are two graphs created using the same equation but where the data that is put into the equations differ very slightly. One graph uses the input data 0.506127. The second graph approximates this to 0.506. Although the graphs start out following similar paths, they very quickly behave completely differently.

The model that Lorenz was running was a simplification of models for the weather that analysed how the flow of air behaves when subjected to differences in temperature. His rediscovery of how small changes in the way you start a system can have such a big impact on the outcome would have huge implications for our attempts to use mathematical equations to make predictions into the future. As Lorenz wrote:

Two states that were imperceptibly different could evolve to two considerably different states. Any error in the observation of the present state – and in a real system, this appears to be inevitable – may render an acceptable prediction of the state in the distant future impossible.

THE REVENGE OF THE GRASSHOPPER

When Lorenz explained his findings to a colleague, he received the reply: ‘Edward, if your theory is correct, one flap of a seagull’s wings could alter the course of history forever.’

The seagull would eventually be replaced by the now famous butterfly when Lorenz presented his findings in 1972 at the American Association for the Advancement of Science in a paper entitled: ‘Does the Flap of a Butterfly’s Wings in Brazil Set Off a Tornado in Texas?’

Curiously, both the seagull and the butterfly might have been pre-empted by the grasshopper. It seems that already in 1898 Professor W. S. Franklin had realized the devastating effect that the insect community could have on the weather. Writing in a book review, he believed:

An inﬁnitesimal cause may produce a ﬁnite effect. Long-range detailed weather prediction is therefore impossible, and the only detailed prediction which is possible is the inference of the ultimate trend and character of a storm from observations of its early stages; and the accuracy of this prediction is subject to the condition that the ﬂight of a grasshopper in Montana may turn a storm aside from Philadelphia to New York!

This is an extraordinary position to be in. The equations that science has discovered give me a completely deterministic description of the evolution of many dynamical systems like the weather. And yet in many cases I am denied access to the predictions that they might make because any measurement of the location or wind speed of a particle is inevitably going to be an approximation to the true conditions.

This is why the MET office, when it is making weather predictions, takes the data recorded by the weather stations dotted across the country and then, instead of running the equations on this data, the meteorologists do several thousand runs, varying the data over a range of values. The predictions stay close for a while, but by about five days into the future the results have often diverged so wildly that one set of data predicts a heat wave to hit the UK while a few changes in the decimal places of the data result in rain drenching the country.

Starting from nearly the same conditions, forecast A predicts strong wind and rain over the British Isles in 4 days’ time, while forecast B predicts incoming high pressure from the Atlantic.

The great Scottish scientist James Clerk Maxwell articulated the important difference between a system being deterministic yet unknowable in his book Matter and Motion, published in 1877: ‘There is a maxim which is often quoted, that “The same causes will always produce the same eﬀects.”’ This is certainly true of a mathematical equation describing a dynamical system. Feed the same numbers into the equation and you won’t get any surprises. But Maxwell continues: ‘There is another maxim which must not be confounded with this, which asserts that “Like causes produce like eﬀects.” This is only true when small variations in the initial circumstances produce only small variations in the ﬁnal state of the system.’ It is this maxim that the discovery of chaos theory in the twentieth century revealed as false.

This sensitivity to small changes in initial conditions has the potential to sabotage my attempts to use the equations I’ve written down to predict the outcome of my dice. I’ve got the equations, but can I really be sure that I’ve accurately recorded the angle at which the cube leaves my hand, the speed at which it is spinning, the distance to the table?

Of course, everything isn’t completely hopeless. There are times when small changes don’t alter the course of the equations dramatically, like the paths in the classical billiard table. What is important is to know when you cannot know. A beautiful example of knowing the point when you can’t know what is going to happen next was discovered by mathematician Robert May when he analysed the equations for population growth.

KNOWING WHEN YOU CAN’T KNOW

Born in Australia in 1938, May had originally trained as a physicist working on superconductivity. But his academic work took a dramatic turn when he was exposed in the late 1960s to the newly formed movement in social responsibility in science. His attention shifted from the behaviour of collections of electrons to the more pressing questions of the behaviour of population dynamics in animals. Biology at the time was not a natural environment for the mathematically minded, but following May’s work that would all change. It was this fusion of the hardcore mathematical training he’d received as a physicist combined with a new sensibility to biological issues that led to his great breakthrough.

In a paper in Nature called ‘Simple Mathematical Models with Very Complicated Dynamics’, published in 1976, May explored the dynamics of a mathematical equation describing population growth from one season to the next. He revealed how even a quite innocent equation can produce extraordinarily complex behaviour in the numbers. His equation for population dynamics wasn’t some complicated differential equation but a simple discrete feedback equation that anyone with a calculator can explore.

Feedback equation for population dynamics

Suppose I consider an animal population whose numbers can vary between 0 and some hypothetical maximum value that I will call N. Given some fraction Y (lying between 0 and 1) of that maximum, the equation determines what in the next season is the revised fraction of the population that survives after reproduction and competition for food. Let’s suppose that each season the reproduction rate is given by a number r. So that if the fraction of the maximum population that survived to the end of the season was Y, the next generation swells to r × Y × N.

But not all of these new animals will survive. The equation determines that the fraction that will not survive is also given by Y. So out of the r × Y × N animals that start the season, Y × (r × Y × N) die. So the total left at the end of the season is (r × Y × N) – (r × Y² × N) = [r × Y × (1 – Y)] × N, which means that the fraction of the maximum population that exists in the current season is r × Y × (1 – Y).

Essentially the model assumes that at the end of each season the surviving population gets multiplied by a constant factor, called r, the reproduction rate, to produce the number of animals at the beginning of the next season. But there aren’t enough resources for them all to survive. The equation then calculates how many of these animals will make it till the end of the season. The resulting number of animals that survive then gets multiplied by the factor r again for the next generation. The fascinating property of this equation is that its behaviour really depends only on the choice of r, the reproduction rate. Some choices of r lead to extremely predictable behaviours. I can know exactly how the numbers will evolve. But there is a threshold beyond which I lose control. Knowledge is no longer within reach because the addition of one extra animal into the mix can result in dramatically different population dynamics.

For example, May discovered that if r lies between 1 and 3 then the population eventually stabilizes. In this case it doesn’t matter what the initial conditions are, the numbers will gradually tend to a fixed value depending on r. It’s like playing billiards on a table where there is a sinkhole in the middle. However I shoot the ball off, it eventually finds its way to the bottom of the sinkhole.

For r above 3, I still see a region of predictable behaviour but of a slightly different character. With r between 3 and 1 +√6 (which is approximately 3.44949), the population dynamics eventually ping-pong between two values that depend on r. As r passes 1 +√6, we see the population dynamics changing character again. For r between 1 +√6 and 3.54409 (or more precisely the solution of a polynomial equation of degree 12), there are 4 values that the population periodically cycles through. As r gets bigger, I get 8 values, then 16, and so on. As r climbs, the number of different values doubles each time until I hit a threshold moment when the character of the dynamics flips from being periodic to chaotic.

When May first explored this equation, he admitted that he frankly hadn’t a clue what was going on beyond this point – he had a blackboard outside his office in Sydney on which he offered a prize of 10 Australian dollars to anyone who could explain the behaviour. As he wrote on the blackboard: ‘It looks like a mess.’

It was on a visit to Maryland that he got his answer and where the term ‘chaos’ was actually coined. In the seminar he gave, he explained the region in which the period doubles but admitted he’d hit a point beyond which he didn’t know what the hell was happening. In the audience was a mathematician who did know. Jim Yorke had never seen the doubling behaviour but he knew exactly what was going on in this higher region. And it was what he called chaos.

Beyond r = 3.56995 (or more precisely the limit point of the solutions of a system of equations of increasing degree), the behaviour becomes very sensitive to what the initial population looks like. Change the initial number of animals by a minute amount and a totally different result can ensue.

Two populations with r = 4 that start off with a difference of just one animal in a thousand. Although they start behaving similarly, by year 15 they are demonstrating very different behaviours.

But as I turn up the dial on r, there can still be pockets of regular behaviour, as Jim Yorke had discovered. For example, take r = 3.627 and the population becomes periodic again, bouncing around between 6 different values. Keep dialling r up and the 6 changes to 12 which becomes 24, doubling each time until chaos strikes again.

Bob May recognized just what a warning shot such a simple system was to anyone who thought they knew it all: ‘Not only in research, but in the everyday world of politics and economics, we would be better off if more people realized that simple systems do not necessarily possess simple dynamic properties.’

THE POLITICS OF CHAOS

Bob May is currently practising what he preaches. Or perhaps I should say Lord May of Oxford, as I was corrected by a man in a top hat who greeted me at the door to the peers’ entrance of the House of Lords. May has in recent years combined his scientific endeavours with energetic political activism. He now sits as a cross-party member of the House of Lords, which is where I popped in for lunch to find out how he was doing in his mission to alert politicians to the impact of chaotic systems on society.

Ushered through the peers’ entrance to the Lords by the man in the top hat and policemen with machine guns, I found May waiting for me on the other side of metal detectors and X-ray machines. May has no truck with all these formal titles and in his earthy Australian manner still insists on being called Bob. ‘I’m afraid I messed up and already ate lunch but I’ll come and eat cake while you get some lunch.’ As I ate fish he consumed an enormous piece of House of Lords chocolate cake. At 79, May is as energetic and engaged as ever and was rushing off after his second lunch to a select committee discussing the impact of a new rail link between London and the northwest of England.

Before joining the Lords, May was chief scientific adviser both to John Major’s Conservative government and then subsequently to Tony Blair’s Labour government. I wondered how tricky a balancing act such a political position is for a man who generally is not scared to tell it like it is.

‘At the interview I was told that there would be occasions where I would be called upon to defend the decisions of a minister and how would I feel about that? I said that I would never under any circumstances deny a fact. On the other hand, I’m fairly good at the kind of debating competition where you’re given a topic and according to a flip of a coin you’ve got to argue for either side of the debate. So I said I’d be happy explaining why the minister’s choice was arrived at. I simply wouldn’t agree to endorse it if it wasn’t right.’

A typical mathematical response. Set up the minister’s axioms and then demonstrate the proof that led to the conclusion. A judgement-free approach. That’s not to say that May isn’t opinionated and prepared to give his own views on the subject at hand.

I was curious how governments deal with the problems that chaos theory creates for anyone trying to make policy decisions. How do politicians cope with the challenges of predicting or manipulating the future, given that we can have only partial knowledge of the systems being analysed?

‘I think that’s rather a flattering account of what goes on here. With some notable exceptions it’s mostly a bunch of very egotistical people, very ambitious people, who are primarily interested in their own careers.’

What about May personally? What impact did the discoveries he’d made have on his view of science’s role in society?

‘It was weird. It was the end of the Newtonian dream. When I was a graduate student it was thought that with better and better computer power we would get better and better weather predictions because we knew the equations and we could make more realistic models of the Earth.’

But May is cautious not to let the climate change deniers use chaos theory as a way to undermine the debate.

‘Not believing in climate change because you can’t trust weather reports is a bit like saying that because you can’t tell when the next wave is going to break on Bondi beach you don’t believe in tides.’

May likes to quote a passage from Tom Stoppard’s play Arcadia to illustrate the strange tension that exists between the power of science to know some things with extraordinary accuracy and chaos theory, which denies us knowledge of many parts of the natural world. One of the protagonists, Valentine, declares:

We’re better at predicting events at the edge of the galaxy or inside the nucleus of an atom than whether it’ll rain on auntie’s garden party three Sundays from now.

May jokes that his most-cited works are not the high-profile academic papers he’s published in prestigious scientific journals like Nature, but the programme notes he wrote for Stoppard’s play when it was first staged at the National Theatre in London. ‘It makes a mockery of all these citation indexes as a way of measuring the impact of scientific research.’

THE HUMAN EQUATION

So what are the big open questions of science that May would like to know the answer to? Consciousness? An infinite universe?

‘I think I’d look at it in a less grand way, so I’d look at it more in terms of the things I am working on at the moment. Largely by accident I’ve been drawn into questions about banking.’

That was a surprise. The question of creating a stable banking system seemed very parochial, but May has recently been applying his models of the spread of infectious diseases and the dynamics of ecological food webs to understanding the banking crisis of 2008. Working with Andrew Haldane at the Bank of England, he has been considering the financial network as if it were an ecosystem. Their research has revealed how financial instruments intended to optimize returns to individual institutions with seemingly minimal risk can nonetheless cause instability in the system as a whole.

May believes that the problem isn’t necessarily the mechanics of the market itself. It’s the way small things in the market are amplified and perverted by the way humans interact with them. For him the most worrying thing about the banking mess is getting a better handle on this contagious spreading of worry.

‘The challenge is: how do you put human behaviour into the model? I don’t think human psychology is mathematizable. Here we are throwing dice with our future. But if you’re trying to predict the throw of the dice then you want to know the circumstance of who owns the dice.’

That was something I hadn’t taken into account in my attempts to predict the outcome of my casino dice. Perhaps I need to factor in who sold me my dice in the first place.

‘I think many of the major problems facing society are outside the realm of science and mathematics. It’s the behavioural sciences that are the ones we are going to have to depend on to save us.’

Looking round the canteen at the House of Lords, you could see the sheer range and complexity of human behaviour at work. It makes the challenge of mathematizing even the interactions in this tiny microcosm of the human population nigh impossible. As the French historian Fernand Braudel explained in a lecture on history he gave to his fellow inmates in a German prison camp near Lübeck during the Second World War: ‘An incredible number of dice, always rolling, dominate and determine each individual existence.’ Although each individual die is unpredictable, there are still patterns that emerge in the long-range behaviour of many throws of the dice. In Braudel’s view this is what makes the study of history possible. ‘History is indeed “a poor little conjectural science” when it selects individuals as its objects … but much more rational in its procedure and results when it examines groups and repetitions.’

But May believes that understanding the history and origins of the collection of dice that make up the whole human race is not as straightforward as Braudel makes out. For example, it’s not at all clear that we can unpick how we got to this point in our evolutionary journey.

‘I’ll tell you one of the questions that I think is a particularly interesting one: trying to understand our evolutionary trajectory as humans on our planet. Is the trajectory we seem to be on what happens on all or most planets, or is it the result of earlier fluctuations in the chaos which took us on this trajectory rather than another. Will we ever know enough to be able to ask whether the disaster we seem to be heading for is inevitable or whether there are lots of other planets where people are more like Mr Spock, less emotional, less colourful, but much more detached and analytical.’

Until we discover other inhabited planets and can study their trajectories, it’s difficult to assess whether evolution inevitably leads to mismanaged ecosystems based on just one dataset called Earth.

‘The question of whether where we’re heading is something that happens to all inhabited planets or whether there are other planets where it doesn’t happen is something I think we’ll never know.’

And with that May polished off the last few crumbs of his chocolate cake and plunged back into the chaos of the select committees and petty politics of Westminster.

May’s last point relates to the challenge that chaos theory poses for knowing something about the past as much as the future. At least with the future we can wait and see what the outcome of chaotic equations produces. But trying to work backwards and understand what state our planet was in to produce the present is equally if not more challenging. The past even more than the future is probably something we can never truly know.

LIFE: A CHANCE THROW OF THE DICE?

May’s pioneering research explored the dynamics of a population as it went from season to season. But what determines which animals survive and which die before reproducing? According to Darwin, this is simply down to a lucky roll of the evolutionary dice.

The model of the evolution of life on Earth is based on the idea that once you have organisms with DNA, then the offspring of these organisms share the DNA of their parent organisms. But parts of the genetic code in the DNA can undergo random mutations. These are essentially down to the chance throw of the evolutionary dice. But there is a second important strand to Darwin’s proposal, which is the idea of natural selection.

Some of those random changes will give the offspring an increased chance of survival, while other changes will result in a disadvantage. The point of evolution by natural selection is that it is more likely that the advantageous change will survive long enough to reproduce.

Suppose, for example, that I start with a population of giraffes that have short necks. The environment of the giraffes changes such that there is more food in the trees, so that any giraffe born with a longer neck is going to have a better chance of survival. Let’s suppose that I throw my Vegas dice to determine the chance of a mutation for each giraffe born in the next generation following this environmental change. A roll of a 1, 2, 3, 4 or 5 condemns the giraffe to a neck of the same size or shorter, while a throw of a 6 corresponds to a chance mutation which causes a longer neck. The lucky longer-necked giraffes get the food and the shorter-necked giraffes don’t survive to reproduce. So it is just the longer-necked giraffes that get the chance to pass on their DNA.

In the next generation the same thing happens. Roll a 1, 2, 3, 4 or 5 on the dice and the giraffe doesn’t grow any taller than its parents. But another 6 grows the giraffe a bit more. The taller giraffes survive again. The environment favours the giraffes that have thrown a 6. Each generation ends up a bit taller than the last generation until there comes a point where it is no longer an advantage to grow any further.

It’s the combination of chance and natural selection that results in us seeing more giraffes with ancestors that all threw 6s. In retrospect it looks like amazing chance that you see so many 6s in a row. But the point is that you don’t see any of the other rolls of the dice because they don’t survive. What looks like a rigged game is just the result of the combination of chance and natural selection. There is no design or fixing at work. The run of consecutive 6s isn’t a lucky streak but is actually the only thing we would expect to see from such a model.

It’s a beautifully simple model, but, given the complexity of the changes in the environment and the range of mutations that can occur, this simple model can produce extraordinary complexity, which is borne out by the sheer variety of species that exist on Earth. One of the reasons I never really fell in love with biology is that there seemed to be no way to explain why we got cats and zebras out of this evolutionary model and not some other strange selection of animals. It all seemed so arbitrary. So random. But is that really fair?

There is an interesting debate going on in evolutionary biology about how much chance there is in the outcomes we are seeing. If we rewound the story of life on Earth to some point in the past and threw the dice again, would we see very similar animals appearing or could we get something completely different? It is the question that May raised at the end of our lunch.

It does appear that some parts of evolution seem inevitable. It is striking that throughout evolutionary history the eye evolved independently 50 to 100 times. This is strong evidence for the fact that the different rolls of the dice that have occurred across different species seem to have produced species with eyes regardless of what is going on around them. Lots of other examples illustrate how some features, if they are advantageous, seem to rise to the top of the evolutionary swamp. This is illustrated every time you see the same feature appearing more than once in different parts of the animal kingdom. Echolocation, for example, is used by dolphins and bats, but they evolved this trait independently at very different points on the evolutionary tree.

But it isn’t clear how far these outcomes are guaranteed by the model. If there is life on another planet, will it look anything like the life that has evolved here on Earth? This is one of the big open questions in evolutionary biology. As difficult as it may be to answer, I don’t believe it qualifies as something we can never know. It may remain something we will never know, but there is nothing by its nature that makes it unanswerable.

WHERE DID WE COME FROM?

Are there other great unsolved questions of evolutionary biology that might be contenders for things we can never know? For example, why, 542 million years ago, at the beginning of the Cambrian period, was there an explosion of diversity of life on Earth? Before this moment life consisted of single cells that collected into colonies. But over the next 25 million years, a relatively short period on the scale of evolution, there is a rapid diversification of multicellular life that ends up resembling the diversity that we see today. An explanation for this exceptionally fast pace of evolution is still missing. This is in part due to lack of data from that period. Can we ever recover that data, or could this always remain a mystery?

Chaos theory is usually a limiting factor in what we can know about the future. But it can also imply limits on what we can know about the past. We see the results, but deducing the cause means running the equations backwards. Without complete data the same principle applies backwards as forwards. We might find ourselves at two very divergent starting points which can explain very similar outcomes. But we’ll never know which of those origins was ours.

One of the big mysteries in evolutionary biology is how life got going in the first place. The game of life may favour runs of 6s on the roll of the evolutionary dice, but how did the game itself evolve? Estimates have been made for the chances of everything lining up to produce molecules that replicate themselves. In some models of the origins of life it is equivalent to nature having to throw 36 dice and get them all to land on 6. For some this is proof of needing a designer to rig the game. But this is to misunderstand the huge timescale that we are working on.

Miracles do happen … given enough time. Indeed, it would be more striking if we didn’t get these strange anomalies happening. The point is that the anamolies often stick out. They get noticed, while the less exciting rolls of the dice get ignored.

The lottery is a perfect test bed for the occurrence of miracles in a random process. On 6 September 2009 the following six numbers were the winning numbers in the Bulgarian state lottery:

4, 15, 23, 24, 35, 42

Four days later the same six numbers came up again. Incredible, you might think. The government in Bulgaria certainly thought so and ordered an immediate investigation into the possibility of corruption. But what the Bulgarian government failed to take into account is that each week, across the planet, different lotteries are being run. They have been running for decades. If you do the mathematics, it would be more surprising not to see such a seemingly anomalous result.

The same principle applies to the conditions for producing self-replicating molecules in the primeval soup that made up the Earth before life emerged. Mix together plenty of hydrogen, water, carbon dioxide and some other organic gases and subject them to lightning strikes and electromagnetic radiation and already experiments in the lab show the emergence of organic material found only in living things. No one has managed to spontaneously generate anything as extraordinary as DNA in the lab. The chances of that are very small.

But that’s the point, because given the billion billion or so possible planets available in the universe on which to try out this experiment, together with the billion or so years to let the experiment run, it would be more striking if that outside chance of creating something like DNA didn’t happen. Keep rolling 36 dice on a billion billion different planets for a billion years and you’d probably get one roll with all 36 dice showing 6. Once you have a self-replicating molecule it has the means to propagate itself, so you only need to get lucky once to kick off evolution.

Our problem as humans, when it comes to appreciating the chance of a miracle such as life occurring, is that we have not evolved minds able to navigate very large numbers. Probability is therefore something we have little intuition for.

THE FRACTAL TREE OF LIFE

But it’s not only the mathematics of probability that is at work in evolution. The evolutionary tree itself has an interesting quality that is similar to the shapes that appear in chaos theory, a quality known as fractal.

The fractal evolutionary tree.

The evolutionary tree is a picture of the evolution of life on Earth. Making your way through the tree corresponds to a movement through time. Each time the tree branches, this represents the evolution of a new species. If a branch terminates, this means the extinction of that species. The nature of the tree is such that the overall shape seems to be repeated on smaller and smaller scales. This is the characteristic feature of a shape mathematicians call a fractal. If you zoom in on a small part of the tree it looks remarkably like the large-scale structure of the tree. This self-similarity means that it is very difficult to tell at what scale we are looking at the tree. This is the classic characteristic of a fractal.

Fractals are generally the geometric signature of a chaotic system, so it is suggestive of chaotic dynamics at work in evolution: the small changes in the genetic code that can result in huge changes in the outcome of evolution. This model isn’t necessarily a challenge to the idea of convergence, as there can still be points in chaotic systems towards which the model tends to evolve. Such points are called attractors. But it certainly questions whether if you reran evolution it would look anything like what we’ve got on Earth today. The evolutionary biologist Stephen Jay Gould has contended that if you were to rerun the tape of life that you would get very different results. This is what you would expect from a chaotic system. Just as with the weather, very small changes in the initial conditions can result in a dramatically different outcome.

Gould also introduced the idea of punctuated equilibria, which captures the fact that species seem to remain stable for long periods and then undergo what appears to be quite rapid evolutionary change. This has also been shown to be a feature of chaotic systems. The implications of chaos at work in evolution are that many of the questions of evolutionary biology could well fall under the umbrella of things we cannot know because of their connections to the mathematics of chaos.

For example, will we ever know whether humans were destined to evolve from the current model of evolution? An analysis of DNA in different animals has given us exceptional insights into the way animals have evolved in the past. The fossil record, although incomplete in places, has also given us a way to know our origins. But given the time scales involved in evolution it is impossible to experiment and rerun the tape of life evolving on Earth and see if something different could have happened. As soon as we find life on other planets (if we do), this will give us new sample sets to analyse. But until then all is not lost. Just as the MET office doesn’t have to run real weather to make predictions, computer models can illustrate different possible outcomes of the mechanism of evolution, speeding up time. But the model will only be as good as the hypotheses we have made on the model. If we’ve got the model wrong, it won’t tell us what is really happening in nature.

It’s such computer models that are at the heart of trying to answer the question Poincaré first tackled when he discovered chaos: will there even be a stable Earth orbiting the Sun for evolution to continue playing its game of dice? How safe is our planet from the vagaries of chaos? Is our solar system stable and periodic, or do I have to worry about a grasshopper disrupting our orbit around the Sun?

A BUTTERFLY CALLED MERCURY

Poincaré wasn’t able to answer the King of Sweden’s question about the solar system: whether it would remain in a stable equilibrium or might fly apart in a catastrophic exhibition of chaotic motion. His discovery that some dynamical systems can be sensitive to small changes in data opened up the possibility that we may never know the precise fate of the solar system much in advance of any potentially devastating scenario unfolding.

It is possible that, like population dynamics with a low reproductive rate, the solar system is in a safe predictable region of activity. Unfortunately, the evidence suggests that we can’t console ourselves with this comforting mathematical hope. Recent computer modelling has provided new insights which reveal that the solar system is indeed within a region dominated by the mathematics of chaos.

I can measure how big an effect a small change will have on the outcome using something called the Lyapunov exponent. For example, in the case of billiards played on differently shaped tables, I can give a measure of how catastrophic a small change will be on the evolution of a ball’s trajectory. If the Lyapunov exponent of a system is positive, it means that if I make a small change in the initial conditions then the distance between the paths diverges exponentially. This can be used as a definition of chaos.

With this measure several groups of scientists have confirmed that our solar system is indeed chaotic. They have calculated that the distance between two initially close orbital solutions increases by a factor of ten every 10 million years. This is certainly on a different timescale to our inability to predict the weather. Nevertheless, it means that I can have no definite knowledge of what will happen to the solar system over the next 5 billion years.

If you’re wondering in despair whether we can know anything about the future, then take heart in the fact that mathematics isn’t completely hopeless at making predictions. There is an event that the equations guarantee will occur if we make it to 5 billion years from now, but it’s not good news: the mathematics implies that at this point the Sun will run out of fuel and evolve into a red giant engulfing planet Earth and the other planets in our solar system in the process. But until this solar blowout engulfs the solar system, I am faced with trying to solve chaotic equations if I want to know which planets will still be around to see that red giant.

This means that, like the predictions of the weather, if I want to know what is going to happen, I am reduced to running simulations in which I vary the precise locations and speeds of the planets. The forecast is in some cases rather frightening. In 2009 French astronomers Jacques Laskar and Mickael Gastineau ran several thousand models of the future evolution of our solar system. And their experiments have identified a potential butterfly: Mercury.

The simulations start by feeding in the records we have of the positions and velocities of the planets to date. But it is difficult to know these with 100% accuracy. So each time they run the simulation they make small changes to the data. Because of the effects of chaos theory, just a small change could result in a large deviation in the outcomes.

For example, astronomers know the dimensions of the ellipse of Mercury’s orbit to an accuracy of several metres. Laskar and Gastineau ran 2501 simulations where they varied these dimensions over a range of less than a centimetre. Even this small perturbation resulted in startlingly different outcomes for our solar system.

You might expect that if the solar system was going to be ripped apart it would have to be one of the big planets like Jupiter or Saturn that would be the culprit. But the orbits of the gas giants are extremely stable. It’s the rocky terrestrial planets that are the troublemakers. In 1% of simulations that they ran, it was tiny Mercury that posed the biggest risk. The models show that Mercury’s orbit could start to extend due to a certain resonance with Jupiter, with the possibility that Mercury could collide with its closest neighbour, Venus. In one simulation, a close miss was enough to throw Venus out of kilter, with the result that Venus collides with Earth. Even close encounters with the other planets would be enough to cause such tidal disruption that the effect would be disastrous for life on our planet.

This isn’t simply a case of abstract mathematical speculation. Evidence of such collisions has been observed in the planets orbiting the binary star Upsilon Andromedae. Their current strange orbits can be explained only by the ejection of an unlucky planet sometime in the star’s past. But before we head for the hills, the simulations reveal that it will take several billion years before Mercury might start to misbehave.

INFINITE COMPLEXITY

What of my chances to predict the throw of the dice that sits next to me? Laplace would have said that, provided I can know the dimensions of the dice, the distribution of the atoms, the speed at which it is launched, its relationship to its surrounding environment, theoretically the calculation of its resting point is possible.

The discoveries of Poincaré and those who followed have revealed that just a few decimal places could be the difference between the dice landing on a 6 or a 2. The dice is designed to have only six different outcomes, yet the input data ranges over a potentially continuous spectrum of values. So there are clearly going to be points where a very small change will flip the dice from landing on a 6 to a 2. But what is the nature of those transitions?

Computer models can produce very good visual representations that give me a handle on the sensitivity of various systems to the starting conditions. Next to my Vegas dice I’ve got a classic desktop toy that I can play with for hours. It consists of a metal pendulum that is attracted to three magnets, coloured white, black and grey. Analysis of the dynamics of this toy has led to a picture that captures the ultimate outcome of the pendulum as it starts over each point in the square base of the toy. Colour a point white if starting the pendulum at this point results in it ending at the white magnet. Similarly, colour the point grey or black if the ultimate destination is grey or black. This is the picture you get:

As in the case of population dynamics, there are regions which are entirely predictable. Start close to a magnet and the pendulum will just be attracted to that magnet. But towards the edges of the picture I find myself in far less predictable terrain. Indeed, the picture is now an example of a fractal.

There are regions where there isn’t a simple transition from black to white. If I keep zooming in, the picture never becomes just a region filled with one colour. There is complexity at all scales.

A one-dimensional example of such a picture can be cooked up as follows. Draw a line of unit length and begin by colouring one half black and the other white. Then take half the line from the point 0.25 to 0.75 and flip it over. Now take the half in between that and flip it over again. If we keep doing this to infinity then the predicted behaviour around the point at 0.5 is extremely sensitive to small changes. There is no region containing the point 0.5 which has a single colour.

There is a more elaborate version of this picture. Start again with a line of unit length. Now rub out the middle third of the line. You are left with two black lines with a white space in between. Now rub out the middle third of each of the two black lines. Now we have a black line of length ¹⁄₉, a white line of length ¹⁄₉, a black line of length ¹⁄₉, then the white line of length ¹⁄₃ that was rubbed out on the first round, and then a repeat of black–white–black.

You may have guessed what I am going to do next. Each time rub out the middle third of all the black lines that you see. Do this to infinity. The resulting picture is called the Cantor set, after the German mathematician Georg Cantor, whom we will encounter in the last Edge, when I explore what we can know about infinity. Suppose this Cantor set was actually controlling the outcome of the pendulum in my desktop toy. If I move the pendulum along this line, I find that this picture predicts some very complicated behaviour in some regions.

A rather strange calculation shows that the total length of the line that has been rubbed out is 1. But there are still black points left inside: ¹⁄₄ is a point that is never rubbed out, as is ³⁄₁₀. These black points, however, are not isolated. Take any region round a black point and you will always have infinitely many black and white points inside the region.

What do the dynamics of my dice look like? Are they fractal and hence beyond my knowledge? My initial guess was that the dice would be chaotic. However, recent research has turned up a surprise.

KNOWING MY DICE

A Polish research team has recently analysed the throw of a dice mathematically, and by combining this with the use of high-speed cameras they have revealed that my dice may not be as chaotic and unpredictable as I first feared. The research group consists of father-and-son team Tomasz and Marcin Kapitaniak together with Jaroslaw Strzalko and Juliusz Grabski, and they are based in Lódź. In their paper in the journal Chaos, published in 2012, the team draw similar pictures to those for the magnetic pendulum, but the starting positions are more involved than just two coordinates because they have to give a description of the angle at which the cube is launched and also the speed. The dice will be predictable if for most points in this picture when I alter the starting conditions a little the dice ends up falling on the same side. I can think of the picture being coloured by six colours corresponding to the six sides of the dice. The picture is fractal if however much I zoom in on the shape I still see regions containing at least two colours. The dice is predictable if I don’t see this fractal quality.

The model the Polish team considered assumes the dice is perfectly balanced like the dice I brought back from Vegas. Air resistance, it turns out, can be ignored as it has very little influence on the dice as it tumbles through the air. When the dice hits the table a certain proportion of the dice’s energy is dissipated, so that after sufficiently many bounces the dice has lost all kinetic energy and comes to rest.

Friction on the table is also key, as the dice is likely to slide in the first few bounces but won’t slide in later bounces. However, the model explored by the Polish team assumed a frictionless surface as the dynamics get too complicated to handle when friction is present. So imagine throwing the dice onto an ice rink.

I’d already written down equations based on Newton’s laws of motion for the dynamics of the dice as it flies through the air. In the hands of the Polish team they turn out not to be too complicated. It is the equations for the change in dynamics after the impact with the table that are pretty frightening, taking up ten lines of the paper they wrote.

They discovered that if the amount of energy dissipated on impact with the table is quite high, the picture of the outcome of the dice does not have a fractal quality. This means that if one can settle the initial conditions with appropriate accuracy, the outcome of the throw of my dice is predictable and repeatable. This predictability implies that, more often than not, the dice will land on the face that was lowest when the dice is launched. A dice that is fair when static may actually be biased when one adds in its dynamics.

But as the table becomes more rigid, resulting in less energy being dissipated and hence the dice bouncing more, I start to see a fractal quality emerging.

Moving from (a) to (d), the table dissipates less energy, resulting in a more fractal quality for the outcome of the dice.

This picture looks at varying two parameters: the height from which the dice is launched and variations in the angular velocity around one of the axes. The less energy that is dissipated on impact with the table, the more chaotic its resulting behaviour and the more it seems that the outcome of my dice recedes back into the hands of the gods.

DOES GOD PLAY DICE?

What of the challenge to define God as the things we cannot know? Chaos theory asserts that I cannot know the future of certain systems of equations because they are too sensitive to small inaccuracies. In the past gods weren’t supernatural intelligences living outside the system but were the rivers, the wind, the fire, the lava – things that could not be predicted or controlled. Things where chaos lay. Twentieth-century mathematics has revealed that these ancient gods are still with us. There are natural phenomena that will never be tamed and known. Chaos theory implies that our futures are often beyond knowledge because of their dependence on the fine-tuning of how things are set up in the present. Because we can never have complete knowledge of the present, chaos theory denies us access to the future. At least until that future becomes the present.

That’s not to say that all futures are unknowable. Very often we are in regions which aren’t chaotic and small fluctuations have little effect on outcomes. This is why mathematics has been so powerful in helping us to predict and plan. Here we have knowledge of the future. But at other times we cannot have such control, and yet this unknown future will certainly impact on our lives at some point.

Some religious commentators who know their science and who try to articulate a scientific explanation for how a supernatural intelligence could act in the world have intriguingly tried to use the gap that chaos provides as a space for this intelligence to affect the future.

One of these religious scientists is the quantum physicist John Polkinghorne. Based at the University of Cambridge, Polkinghorne is a rare mind who combines both the rigours of a scientific education with years of training to be a Christian priest. I will be meeting Polkinghorne in person in the Third Edge when I explore the unknowability inherent in his own scientific field of quantum physics. But he has also been interested in the gap in knowledge that the mathematics of chaos theory provides as an opportunity for his God to influence the future course of humanity.

Polkinghorne has proposed that it is via the indeterminacies implicit in chaos theory that a supernatural intelligence can still act without violating the laws of physics. Chaos theory says that we can never know the set-up precisely enough to be able to run deterministic equations, and hence there is room in Polkinghorne’s view for divine intervention, to tweak things to remain consistent with our partial knowledge but still influence outcomes.

Polkinghorne is careful to stress that to use infinitesimal data to effect change requires a complete holistic top-down intervention. This is not a God in the detail but by necessity an all-knowing God. Given that chaos theory means that even the location of an electron on the other side of the universe could influence the whole system, we need to have complete, holistic knowledge of the whole system – the whole universe – to be able to steer things. We cannot successfully isolate a part of the universe and hope to make predictions based on that part. So it would require knowledge of the whole to act via this chink in that which is unknown to us.

Chaos theory is deterministic, so this isn’t an attempt to use the randomness of something like quantum physics as a way to have influence. Polkinghorne’s take on how to square the circle of determinism and influence the system is to use the gap between epistemology and ontology, between what we know and what is true. Since we cannot know a complete description of the state of the universe at this moment in time, this implies that from our perspective there is no determinacy. There are many different scenarios that coincide with our impartial description of what we currently know about how the universe is set up. Polkinghorne’s contention is that at any point in time this gives a God the chance to intervene and shift the system between any of these scenarios without us being aware of the shift. But, as we have seen, chaos theory means that these small shifts can still have hugely different outcomes. Polkinghorne is careful to assert that you allow shifts between systems where there is change only in information, not energy. The rule here is not to violate any rules of physics. As Polkinghorne says: ‘The succession of the seasons and the alternations of day and night will not be set aside.’

Even if you think this is rather fanciful (which I certainly do), a similar principle is probably key to our own feeling of agency in the world. The question of free will is related ultimately to questions of a reductionist philosophy. Free will describes the inability to make any meaningful reduction in most cases to an atomistic view of the world. So it makes sense to create a narrative in which we have free will because that is what it looks like on the level of human involvement in the universe. If things were so obviously deterministic, with little variation to small undetectable changes, we wouldn’t think that we had free will.

It is striking that Newton, the person who led us to believe in a clockwork deterministic universe, also felt that there was room in the equations for God’s intervention. He wrote of his belief that God would sometimes have to reset the universe when things looked like they were going off course. He got into a big fight with his German mathematical rival Gottfried Leibniz, who couldn’t see why God wouldn’t have set it up perfectly from the outset:

Sir Isaac Newton and his followers have also a very odd opinion concerning the work of God. According to their doctrine, God Almighty wants to wind up his watch from time to time: otherwise it would cease to move. He had not, it seems, sufficient foresight to make it a perpetual motion.

ON THE EDGE OF CHAOS

Newton and his mathematics gave me a feeling that I could know the future, that I could shortcut the wait for it to become the present. The number of times I have heard Laplace’s quote about ultimately being able to know everything thanks to the equations of motion is testament to a general feeling among scientists that the universe is theoretically knowable.

The mathematics of the twentieth century revealed that theory doesn’t necessarily translate into practice. Even if Laplace is correct in his statement that complete knowledge of the current state of the universe together with the equations of mathematics should lead to complete knowledge of the future, I will never have access to that complete knowledge. The shocking revelation of twentieth-century chaos theory is that even an approximation to that knowledge won’t help. The divergent paths of the chaotic billiard table mean that since we can never know which path we are on, our future is not predictable.

Chaos theory implies that there are things we can never know. The mathematics in which I had placed so much faith to give me complete knowledge has revealed the opposite. But it is not entirely hopeless. Many times the equations are not sensitive to small changes and hence give me access to predictions about the future. After all, this is how we landed a spaceship on a passing comet. Not only that: as Bob May’s work illustrates, the mathematics can even help me to know when I can’t know.

But a discovery at the end of the twentieth century even questions Laplace’s basic tenet of the theoretical predictability of the future. In the early 1990s a PhD student by the name of Zhihong Xia proved that there is a way to configure five planets such that when you let them go, the combined gravitational pull causes one of the planets to fly off and reach an infinite speed in a finite amount of time. No planets collide, but still the equations have built into them this catastrophic outcome for the residents of the unlucky planet. The equations are unable to make any prediction of what happens beyond this point in time.

Xia’s discovery is a fundamental challenge to Laplace’s view that Newton’s equations imply that we can know the future if we have complete knowledge of the present, because there is no prediction even within Newton’s equations for what happens next for that unlucky planet once it hits infinite speed. The theory hits a singularity at this point, beyond which prediction makes no sense. As we shall see in later Edges, considerations of relativity will limit the physical realization of this singularity since the unlucky planet will eventually hit the cosmic speed limit of the speed of light, at which point Newton’s theory is revealed to be an approximation of reality. But it nevertheless reveals that equations aren’t enough to know the future.

It is striking to listen to Laplace on his deathbed. As he sees his own singularity heading towards him with only a finite amount of time to go, he too admits: ‘What we know is little, and what we are ignorant of is immense.’ The twentieth century revealed that, even if we know a lot, our ignorance will remain immense.

But it turns out that it is isn’t just the outward behaviour of planets and dice that is unknowable. Probing deep inside my casino dice reveals another challenge to Laplace’s belief in a clockwork deterministic universe. When scientists started to look inside the dice to understand what it is made of, they discovered that knowing the position and the movement of the particles that make up the dice may not even be theoretically possible. As I shall discover in the next two Edges, there might indeed be a game of dice at work that controls the behaviour of the very particles that make up my red Las Vegas cube.

SECOND EDGE: THE CELLO

3

Everyone takes the limits of his own vision for the limits of the world.

Arthur Schopenhauer

When I started at my comprehensive school, I remember my music teacher asking the class if there was anyone who wanted to learn a musical instrument. Three of us put up our hands. The teacher led us into the storeroom cupboard to see what instruments were available. The cupboard was bare except for three trumpets stacked up on top of each other.

‘It looks like you’re learning the trumpet.’

I don’t regret the choice (even if there wasn’t one). I had a great time playing in the local town band and larking around in the brass section of the county orchestra as we counted bars rest. But I used to look over with a little envy at the strings who seemed to be playing all the time, getting all the good tunes. A few years ago, during a radio interview, I was asked what new musical instrument I would choose to learn, given the opportunity, and which piece of music I would aspire to play.

‘The cello. Bach’s suites.’

The question has been nagging at the back of my mind since that interview: could I learn to play those beautiful cello suites? Perhaps it was too late to pick up such new skills, but I needed to know. So I bought a cello.

It sits behind me as I write about trying to predict the outcome of the dice. When I need a break from analysing the equations that control the fall of the red cube on my desk, I massacre one of the gigues from the first suite for cello. I can feel Bach turning in his grave but I am enjoying myself.

One of the fun things about the cello is the possibility of sliding your finger up the string to create a continuous glissando of notes. Not something I can do on my trumpet, which is an instrument of discrete notes corresponding to the different combinations of fingers I put down. It turns out that this tension between the continuous glissando of the cello and the discrete notes of the trumpet is relevant to my attempts to predict the behaviour of my dice.

ZOOMING IN

To predict how the dice might land I need to know what my cube is made from. Denser acetate in one corner of the shape will lead to one side of the dice being favoured over the others. So if I am going to attempt to apply Newton’s laws to my dice as it tumbles through the air, I need to know how my dice is put together. Is it a continuous structure, or, if I look closely, is it made up of discrete pieces?

If I accept the limits of my own vision, as Schopenhauer’s quote at the beginning of this Edge suggests I tend to, then I can’t see anything other than the clear red acetate that makes up the dice. But with an optical microscope I can magnify the dice by a factor of 1500, which would scale my dice up to the size of a large building. Peering inside this huge dice still won’t reveal much about the secrets of how it is built. Everything still looks pretty smooth and continuous.

In the twentieth century microscopes exploiting different bits of the electromagnetic spectrum have allowed scientists to create images which magnify things a further 1000 times. Now my dice will span from one side of London to the other. At this magnification the dice is looking grainier. The sense of the continuous structure is giving way to something more discrete. Current electron microscopes allow me to zoom in another 10 times closer, at which point I might start to see the carbon and oxygen atoms that I know are some of the ingredients of the acetate from which my dice is made.

The intriguing thing is that scientists had already formulated an atomic view of matter long before I could actually see these atoms under the modern microscopes in the labs across the road from the mathematics department. And it is a combination of a mathematical and theoretical perspective with a physical vision that is the best tool for knowing what my dice is made from.

But atoms like oxygen and carbon turned out not to be as atomic as the name suggests. Beyond the atomic structure revealed by current electron microscopes, I know that there is more internal structure. Atoms give way to electrons, protons and neutrons. Protons and neutrons in turn give way to quarks. In 2013 quantum microscopes even captured pictures of electrons orbiting the nucleus of a hydrogen atom. But is there a theoretical limit to how far I can dig down inside my dice?

What happens, for example, if I take my dice and keep dividing it in half? Just how far can I go? The mathematical side of me says: no problem. If I have a number I can keep dividing it by two:

There is no point mathematically where I have to stop. Yet if I start trying to do the same thing with the physical dice sitting on my desk and cut it in half, then in half again, just how far can I keep going?

The tension between the continuous versus the discrete nature of matter, between what is possible mathematically versus the limits placed by physical reality, has been raging for millennia. Is the universe dancing to the sound of my trumpet or shimmying to the glissando of my cello?

THE MUSIC OF THE SPHERES

How did I personally come to know about these electrons and quarks that are believed to be the last layer of my dice? I’ve never seen them. If I actually ask myself how I know about them, the answer is that I’ve been told and read about them so many times that I’ve actually forgotten why or how I know. Or, come to think of it, was I ever told how we know? Is it a bit like the way I know Everest is the tallest mountain? I know that only because I’ve been told it enough times. So before I ask whether there is anything beyond this layer, I need to know how we got to these building blocks.

Reading through the history, I am surprised that it is only just over a hundred years ago that convincing evidence was provided for the fact that things like my dice are made of discrete building blocks called atoms and are not just continuous structures. Despite being such a relatively recent discovery, the hunch that this was the case goes back thousands of years. In India it was believed that matter was made from basic atoms corresponding to taste, smell, colour and touch. They divided atoms into ones that were infinitesimally small and took up no space, and others that were ‘gross’ and took up finite space – an extremely prescient theory, as you will see once I explain our current model of matter.

In the West it was the ancient Greeks who first proposed an atomistic philosophy of nature, advocating the reductionist view that physical reality could be reduced to fundamental units that made up all matter. These atoms could not be broken down into anything smaller, and their properties should not depend on some further complex inner structure. One of the seeds for this belief in a universe made from indivisible building blocks was the Pythagorean philosophy that number is at the heart of explaining the secrets of the universe.

The conviction in the power of whole numbers had its origins in a rather remarkable discovery attributed to Pythagoras: namely, that number is the basis of the musical harmony that both my cello and my trumpet exploit. The story has it that inspiration struck when he passed a blacksmith and heard the hammers banging out a combination of harmonious notes. (We can’t be sure whether this and similar stories told about Pythagoras are true, or even whether he really existed and wasn’t an invention of later generations used to promote new ideas.)

This story goes that he went home and experimented with the notes made by a stringed instrument. If I take the vibrating string on my cello then I can produce a continuous sequence of notes by gradually pushing my finger up towards the bridge of the cello, making a sound called a glissando (although the question of whether this is truly producing a continuous sequence of notes will be challenged in the next Edge). If I stop at the positions that produce notes that sound harmonious when combined with the open vibrating string, it turns out that the lengths of the strings are in a perfect whole-number ratio with each other.

For example, if I place my finger at the halfway point along the vibrating string I get a note which sounds almost like the note I started with. The interval is called the octave, and to the human ear the note sounds so similar to the note on the open string that in the musical notation that emerged we give these notes the same names. If I place my finger a third of the distance from the head of the cello, I get a note which sounds particularly harmonious when combined with the note of the open string. Known as the perfect fifth, what our brains are responding to is a subliminal recognition of this whole-number relationship between the wavelengths of the two notes.

Having found that whole numbers were at the heart of harmony, the Pythagoreans began to build a model of the universe that had these whole numbers as the fundamental building blocks of everything they saw or heard around them. Greek cosmology was dominated by the idea of a mathematical harmony in the skies. The orbits of the planets were believed to be in a perfect mathematical relationship to each other, giving rise to the idea of the music of the spheres.

More importantly for understanding the make-up of my dice, it was also believed that discrete numbers rather than a continuous glissando were the key to understanding what constituted matter. The Pythagoreans proposed the idea of fundamental atoms that, like numbers, could be added together to get new matter. The Greek philosopher and mathematician Plato developed the Pythagorean philosophy and makes these atoms into discrete pieces of geometry.

Plato believed the atoms were actually bits of mathematics: triangles and squares. These were the building blocks for the shapes that he believed were the key to the ingredients of Greek chemistry: the elements of fire, earth, air and water. Each element, Plato believed, had its own three-dimensional mathematical shape.

Fire was the shape of a triangular-based pyramid, or tetrahedron, made from 4 equilateral triangles. Earth was cube-shaped like my Vegas dice. Air was made from a shape called an octahedron, constructed from 8 equilateral triangles. It is a shape that looks like two square-based pyramids fused together along the square faces. Finally, water corresponded to the icosahedron, a shape made from 20 equilateral triangles. Plato believed that it was the geometrical interaction of these basic shapes that gave rise to the chemistry of the elements.

The atomistic view of matter was not universally held across the ancient world. After all, there was no evidence for these indivisible bits. You couldn’t see them. Aristotle was one of those who did not believe in the idea of fundamental atoms. He thought that the elements were continuous in nature, that you could theoretically keep dividing my dice up into smaller and smaller pieces. He believed that fire, earth, air and water were elemental in the sense that they could not be divided into ‘bodies different in form’. If you kept dividing, you would still get water or air. If you take a glass of water then to the human eye, it appears to be a continuous structure which can theoretically be infinitely divided. If I take a piece of rubber then I can stretch it in a smooth manner making it appear continuous in nature. The stage was set for the battle between the continuous and discrete models of matter. The glissando versus the discrete notes of the musical scale. The cello versus the trumpet.

Intriguingly, it was a discovery credited to the Pythagoreans that would threaten the atomistic view and which turned the tide for many years in favour of the belief that matter could be divided infinitely.

NUMBERS AT THE EDGE

From the atomistic point of view, if I draw two lines on the page then each line will be made from a certain number of these indivisible atoms and hence their lengths would be in a ratio of whole numbers corresponding to the number of atoms making up each line. But things didn’t turn out to be so orderly. In fact, it was Pythagoras’ own theorem about right-angled triangles that revealed that the world of geometry could give rise to lines whose relative lengths could not be captured by simple fractions.

The dimensions of my dice already have hidden in them a challenge to this atomistic view of nature. Take two of the edges of the cube at 90 degrees to each other. They have equal length. Now consider the diagonal line across the face of the cube that completes the triangle made up from the two edges of equal length. How long is this diagonal line relative to the shorter sides?

Pythagoras’ theorem about right-angled triangles says that the square of the length of the diagonal is equal to the sum of the squares of the lengths of the two shorter sides. If I set the length of the sides of my dice as 1, then Pythagoras’ theorem implies that the length of the diagonal across the face of my dice is a number which, when you square it, is equal to 2. So what is this number?

The Babylonians had been fascinated by the challenge of calculating this length. Dating back to the Old Babylonian period (1800–1600 BC), a tablet housed at Yale University has an estimate for the distance. Written using the sexagesimal system, or base 60, they got the length to be:

which in decimal notation comes out at 1.41421296296 …, where the 296 repeats itself infinitely often. It is true of all fractions that when written as decimals they repeat themselves after some point. Indeed, any decimal expansion which does repeat itself can always be written as a fraction. The Babylonian calculation is quite a feat. It is correct to six decimal places. But when you square that fraction it just misses being 2. What the ancient Greeks discovered is that however hard the Babylonian scribes tried, they would always find that their fractions just missed squaring to 2.

It was one of Pythagoras’ followers, Hippasus, who is credited with the discovery that the Babylonians were doomed to failure. He proved that the length of this diagonal across the side of my dice could never be expressed as a fraction.

Pythagoras’ theorem about right-angled triangles implied that this long side had length the square root of 2 times the length of the short sides. But Hippasus could prove that there was no fraction whose square was exactly 2. The proof uses one of the classic tools in the mathematician’s arsenal: proof by contradiction. Hippasus began by assuming there was a fraction whose square was 2. By some deft manipulation this always led to the contradictory statement that there was a number that was both odd and even. The only way to resolve this contradiction was to realize that the original assumption must have been false: there can be no fraction whose square is 2.

His fellow Pythagoreans were reputed to be dismayed by the revelation that their beautiful right-angled triangles could produce such inharmonic lengths. The sect took a vow of silence, but when Hippasus let the discovery out of the bag, the story goes that he was drowned at sea for revealing such disharmony in the physical world. But these new numbers, called irrational numbers because they are not ratios of whole numbers, were not so easily silenced.

Irrational lengths inside the cube.

I certainly have the feeling that this length exists. I can see it on a ruler held up against the long side of the triangle. It is the distance between two opposite corners of any side of my dice. Yet try to write down the number as an infinite decimal and I can never capture it. It begins 1.414213562 … and then continues to infinity never repeating itself.

IRRATIONAL EXUBERANCE

The discovery by the ancient Greeks that there were lengths that couldn’t be expressed as simple ratios of whole numbers led the mathematicians of the time to create new mathematics, the mathematics of irrational numbers, in order to truly take the measure of the universe. Other basic lengths like π, the circumference of a circle of unit diameter, also turned out to be irrational and not captured by ratios of whole numbers. Although the ancient Greeks knew 2000 years ago about the irrationality of the square root of 2, it took till the eighteenth century for Swiss mathematician Johann Heinrich Lambert to prove that no fraction could capture π.

Despite my aversion to things we cannot know, reading about numbers that can’t be captured using simple whole-number ratios or fractions was one of the defining moments that sparked my love affair with mathematics. The same year that my music teacher introduced me to the trumpet in the storeroom cupboard, my maths teacher introduced me to the proof of the irrationality of the square root of 2. The proof was contained in one of the books my maths teacher recommended to me to ignite the mathematical fire in me. It worked. I was amazed to find that you could prove with a finite logical argument that only the infinite could articulate what a length such as the diagonal across a square measured. If I couldn’t write out this length, the next best thing was knowing why I couldn’t know this number.

Since reading that proof as a schoolkid I have learnt about alternative ways to explore these irrational numbers – so perhaps these are numbers we can know. There are infinite expressions with patterns that make the number less mysterious. For example,

The discovery of these expressions pulls these irrational numbers into the known. A fraction is a number whose decimal expansion repeats itself from some point. Couldn’t I regard these expressions as a pattern, not too dissimilar from the repeating pattern of the decimal expansion of the fraction? The repeating pattern of the fraction means that there are two numbers whose ratio captures the number, while in the case of √2 and π I am resigned to needing infinitely many numbers to pin down these lengths. The question of whether something has to be finite to be known will haunt me continually throughout my journey to the frontiers of the unknown.

Of course, for any practical application of these numbers, I could probably get away with an approximation which is a fraction. Most engineers are happy to use the estimate ²²⁄₇ for π that Archimedes got by approximating a circle with a 96-sided figure. In fact, I need only know 39 digits of π to be able to calculate the circumference of a circle the size of the observable universe to a precision comparable to the size of a hydrogen atom. There even exists a formula that can tell me what the millionth digit of π is without calculating all the intervening digits. Not something that I’m desperate to know. But this formula will only ever give me finite knowledge of a number that necessitates the infinite to fully embrace it.

The discovery of these numbers seemed to imply an infinite divisibility of space. Only by dividing space infinitely would I be able to measure the precise dimensions of my simple cube. The discovery meant that in the West Aristotle’s continuous view of matter would remain dominant until the Renaissance.

THE HARMONY OF TINY SPHERES

With the insights of the science of Newton’s generation and beyond, the tide would turn in favour of the view that the universe is indeed made from basic building blocks. Newton’s contemporary, Robert Boyle, was perhaps the first to question the Aristotelian view of matter, which had dominated for nearly 2000 years. In his book The Sceptical Chymist, Boyle challenged the idea that matter was made up of the four elements of fire, earth, air and water. These might be good descriptions of the states of matter but not of the constituents.

Instead, he argued for a new list of chemical elements. Not only that, he made what at the time was rather a heretical statement. He believed that these elements would be minute bodies or atoms differing only in ‘bulk, figure, texture and motion’. This was regarded as theologically dangerous: a materialistic godless view of the world in the eyes of the Church, which had always favoured the Aristotelian view. Some have declared Boyle the Galileo of the chemical revolution.

Although Newton would concur with Boyle’s proposal for a material world made from indivisible units, the mathematical tools that Newton developed at the same time as Boyle’s work relied heavily on time and space being infinitely divisible. The calculus that allowed one to take a snapshot of a universe in constant flux made sense only as a process in which space is divided up into ever smaller pieces and then interpreting what happens in the limit as the pieces become infinitesimally small.

The question of the infinite divisibility of time and space had fuelled philosophical argument since the ancient Greek thinker Zeno of Elea came up with paradoxes that seemed to arise from this cutting up of space. For example, Zeno proposed that an arrow can never hit its target because it must first cover half the distance to the target, then half the distance again, and then half again, requiring infinitely many moves if it is ever going to make it to the target. The success of Newton’s calculus reignited the debate. There were still those who considered such infinite divisibility as almost heretical.

Bishop Berkeley dedicated a whole treatise called The Analyst to arguing that trying to make sense of dividing by zero was absurd, which the subtitle made clear: it was ‘Addressed to an Infidel MATHEMATICIAN’.

While most infidel mathematicians quickly latched on to the power of the calculus, Newton’s other breakthroughs supported a view that, although space and time could be infinitely divided, matter could not. His idea of a world made up of indivisible matter would in time become the prevalent theory of the universe. But at this point it was still very much a theory without a great deal of evidence.

His theory of forces acting on large objects like planets and apples had been so successful that Newton believed that if the ideas worked on the very large and the medium sized then why not on the very small. Why should there be a change in the way the laws of motion dictate the behaviour of the universe as we zoom in on my dice? The success of his calculus when applied to the movement of the planets depended on regarding them as single points with the mass concentrated at a point corresponding to the centre of gravity of the body. Maybe all matter consisted of particles like tiny planets whose behaviour was determined by his laws of motion. In his Principia he stated his belief that by applying his ideas to these individual particles one could predict the behaviour of all material things.

Newton’s theory of light also contributed to the growing feeling that an atomistic perspective was the best way to understand the world. Regarding light as a particle seemed the easiest way to describe the phenomena he documented in his book Opticks. The way that light reflected seemed to mimic the behaviour of a billiard ball as it bounced off the sides of the table. But from a scientific point of view there was no empirical evidence for this model of a universe made from indivisible particles.

Even with the microscopes that were emerging in the seventeenth century, you couldn’t see anything to justify this atomistic model. Even if you could see discrete objects, it wouldn’t prove anything about their indivisibility. But we can judge that the tide was turning by the fact that the atomistic view of matter made it into the popular culture of the time. Nicholas Brady’s ‘Ode to Saint Cecilia’, set to music by Purcell in 1691, talks of seeds of matter:

Soul of the World! Inspir’d by thee,

The jarring Seeds of Matter did agree,

Thou didst the scatter’d Atoms bind,

Which, by thy Laws of true proportion join’d,

Made up of various Parts one perfect Harmony.

The best evidence for an atomistic view of matter came a hundred years later from experiments that showed how matter combined to make new materials. And it was full of perfect harmony, as Brady had intimated.

ATOMIC ALGEBRA

It was the work of the English chemist John Dalton at the beginning of the nineteenth century that provided the first real experimental justification for thinking of matter as made of indivisible atoms. His discovery that compounds seemed to be made up of substances that were combined in fixed whole-number ratios was the breakthrough, and it led to the scientific consensus that these substances really did come in discrete packages.

For example: ‘The elements of oxygen may combine with a certain portion of nitrous gas or with twice that portion, but with no intermediate quantity.’ It certainly didn’t constitute a proof that matter was discrete, and it was not strong enough to knock the belief of those who favoured a continuous model of matter. But it was highly suggestive. There had to be some explanation for the way these substances were combining.

The notation developed to express these reactions added to the atomistic view. The combination of nitrogen and oxygen could be expressed algebraically as N + O or N + 2O. There was nothing in between. It seemed that all compounds came in proportions that were whole-number ratios. For example, aluminium sulphide was given algebraically as 2Al + 3S = Al2S3, elements combining in a 2-to-3 ratio. Elements never combined in a non-whole-number relationship. It was like musical harmony at the heart of the chemical world. The music of tiny spheres.

The Russian scientist Dmitri Mendeleev is remembered for laying out this growing list of molecular ingredients in such a way that a pattern began to emerge, a pattern based on whole numbers and counting. It seemed that the Pythagorean belief in the power of number was making a comeback. Like several scientists before him, Mendeleev arranged them in increasing relative weight, but he realized that to get the patterns he could see emerging he needed to be flexible.

He’d written the known elements down on cards and was continually placing them on his desk in a game of chemical patience, trying to get them to yield their secrets. But nothing worked. It was driving him crazy. Eventually he collapsed in exhaustion and the secret emerged in a dream that, when he woke, gave him the pattern for laying out the cards. One of the important points that led to his successful arrangement was the realization that he needed to leave some gaps – that some of the cards from the pack were missing.

The key to his arrangement was something called the atomic number, which depended on the number of protons inside the nucleus rather than the combination of protons and neutrons that gave rise to the overall weight. But since no one had any clue yet about these smaller ingredients, Mendeleev was guessing somewhat at the underlying reason for his arrangement.

It was a bit like recognizing that a conventional pack of cards can be laid out in suits, but also that across those suits there are cards that are of equal value. A periodicity of eight seemed to underlie the elements, so that elements eight along seemed to share very similar properties. Eight on from lithium was sodium, followed after another eight by potassium. All soft shiny highly reactive metals. Similar patterns matched up gases with related properties.

This rule of eight had been picked up before Mendeleev’s breakthrough and was called the law of octaves. It was compared to the musical octave: if I play the eight notes of a major scale on my cello, the top and bottom notes sound very similar and are given the same letter names. When this law of atomic octaves was proposed by its originator John Newlands, it was laughed out of the Royal Society. ‘Next you’ll be trying to tell us that the elements can be understood by putting them in alphabetical order,’ joked one Fellow. Mendeleev’s arrangement confirmed to a certain extent the veracity of this law of octaves. It was this idea of repeating or periodic patterns that led to Mendeleev’s arrangement being called the periodic table.

Mendeleev’s genius was to realize that if sometimes the elements didn’t quite match up, it perhaps indicated a missing element. The gaps in his table were probably his most insightful contribution. The fact that there was a hole in the 31st place of his table, for example, led Mendeleev to predict in 1871 the existence and properties of a new substance that would later be called gallium. Four years later French chemist Lecoq de Boisbaudran isolated the first samples of this new atom, predicted thanks to the mathematical patterns discovered by Mendeleev.

RECIPE FOR MAKING A DICE

Here then was a list of the atoms that were meant to make up all of matter. For example, my dice is made from putting together carbon atoms, oxygen atoms and hydrogen atoms into a structure called cellulose acetate. My own body is predominantly made up of combinations of these atoms but with a different structure. The cellulose acetate is a homogeneous structure free from bubbles, which makes it more likely to be fair. The more antique dice were made from a nitrate-based cellulose concocted by John Wesley Hyatt in 1868. His cocktail of nitric acid, sulphuric acid, cotton fibres and camphor produced an impressive substance with great tensile strength that resisted the effects of water, oils and even diluted acids.

Hyatt’s brother named it celluloid and it became a highly cost-effective substitute for objects that had previously been carved out of ivory or horn. Billiard balls and removable collars, piano keys and even my dice were made from this synthetic plastic. The dice that were made from cellulose nitrate were the industry standard in the early twentieth century, but after several decades of use they would almost instantaneously crystallize and decompose, crumbling in on themselves and releasing nitric acid gas.

The real collectors’ dice are those Vegas dice made from cellulose nitrate in the late Forties that avoided this crystallization. My dice won’t suffer the same fate. Here is a picture of how the atoms are put together inside my dice.

The identification of these elements was not a proof of a discrete model of matter. There was no reason that this picture of the ingredients of my dice couldn’t be a formula for the way a continuous structure combines. Although the chemists were tending towards an atomistic view of the universe, this was far from the case in the physics community. Those, like the German physicist Ludwig Boltzmann, who proposed atomic models of matter were laughed out of the lab.

Boltzmann believed that this atomic theory was a powerful way to interpret the concept of heat based on the idea that a gas was made up of tiny molecules bashing around like a huge game of micro-billiards. Heat was just the combined kinetic energy of these tiny moving balls. Using this model, combined with ideas of probability and statistics, he was successfully able to explain the large-scale behaviour of a gas. But most physicists were still committed to a continuous view of matter and were very dismissive of Boltzmann’s ideas.

Boltzmann was so ridiculed that he was forced to retreat from his belief that this billiard-ball theory of matter represented a true picture of reality, and instead was obliged to refer to it as a heuristic model if he wanted to get his ideas in print. As Ernst Mach, his great nemesis in the debate about the reality of atoms, declared mockingly: ‘Have you ever seen an atom?’

Boltzmann was plagued by fits of depression, and there is evidence that he was in fact bipolar. The rejection of his ideas by the scientific community is believed to have contributed to the depression that struck in 1906 and that led to him hanging himself during a holiday with his family near Trieste while his daughter and wife were out swimming.

It was a tragic end, not least because the most convincing evidence that he was right was just emerging. And it was one of the big names of physics who produced ideas that supported the atomistic view and were very hard to ignore. The work that Einstein and others did on Brownian motion would prove extremely difficult to explain for those who, like Mach, believed in a continuous view of the world.

POLLEN PING-PONG

Although conventional microscopes don’t allow one to see individual atoms, they did allow scientists in the nineteenth century to see the effect that these atoms were having on their surroundings. It’s called Brownian motion after Robert Brown, who in 1827 noticed the random behaviour of small particles of pollen floating on the surface of water. Since pollen was organic, Brown’s first thought was that it might be exhibiting signs of life as it jumped around the surface. A similar random behaviour of coal dust floating on alcohol had also been observed by Dutch scientist Jan Ingenhousz in 1785. When Brown saw the pollen’s behaviour replicated by inorganic matter, he was rather stumped as to what was causing the jittery motion.

It’s striking that the idea that it might be invisible atoms bashing into the larger visible material had been suggested by the Roman poet Lucretius in his didactic poem On the Nature of Things:

Observe what happens when sunbeams are admitted into a building and shed light on its shadowy places. You will see a multitude of tiny particles mingling in a multitude of ways … their dancing is an actual indication of underlying movements of matter that are hidden from our sight … It originates with the atoms which move of themselves. Then those small compound bodies that are least removed from the impetus of the atoms are set in motion by the impact of their invisible blows and in turn cannon against slightly larger bodies. So the movement mounts up from the atoms and gradually emerges to the level of our senses, so that those bodies are in motion that we see in sunbeams, moved by blows that remain invisible.

This was written in 60 BC, but it would take Einstein’s mathematical analysis of the motion to confirm this atomic explanation of the random movement in Lucretius’ sunbeams and Brown’s pollen.

The goal is to provide some model that will produce the strange motion exhibited by the small pieces of pollen on the surface of the water. If you divide the surface into a grid, there seems to be an equal probability that the pollen will move left–right–up–down. It is similar to the motion of a drunken man who randomly makes steps according to the toss of a four-sided dice. The picture below shows the paths of various particles of pollen as plotted by the French physicist Jean Baptiste Perrin, who took up the challenge of explaining the pollen’s motion in his book Les Atomes.

The proposal emerged at the beginning of the twentieth century that scientists were observing the pollen being buffeted by the motion of much smaller molecules of water.

It was Einstein’s mathematical brilliance that allowed him to analyse this model in which a large object was subjected to the impact of much smaller objects that were moving randomly. He proved that the model predicted precisely the observed behaviour. Think of an ice rink with a large puck sitting in the middle of the rink and then introduce a whole system of tiny pucks that are set off in random directions at particular speeds. Every now and again the tiny pucks will hit the large puck, causing it to move in one direction. The skill was to assess how many small pucks you would need, and their relative size, in order to produce the observed behaviour of the larger puck.

Einstein’s success in producing such a mathematical model that replicated the motion of the pollen was a devastating blow to anyone who believed that a liquid like water was a continuous substance. It was very hard for anyone who still believed in Aristotle’s view of matter to come up with a comparably convincing explanation.

The calculations allowed one to estimate how small the molecules of water were in comparison with the pollen they were knocking around. Although it was convincing evidence that matter came in discrete pieces, it did not answer the question of whether you could still infinitely divide these pieces into ever smaller parts.

Indeed, the indivisible atoms turned out to be far from indivisible with the discovery of smaller constituents that made up atoms of carbon or oxygen. The next layer down revealed that an atom is made up of even tinier pucks called electrons, protons and neutrons, the first of which had already come to light some eight years before Einstein’s theoretical breakthrough.

PULLING APART THE ATOM

The way science works is that you can hang on to your model of the universe until something pops up that doesn’t fit: something new that you can’t seem to explain with the current model. The realization that the atom might be made up of smaller bits emerged out of experiments that revealed something particle-like but much tinier than the atoms that made up the periodic table.

This tiny particle-like object materialized from the British physicist J. J. Thomson’s experiments at the end of the nineteenth century to understand electricity. He had been investigating how electricity was conducted through a gas. Early experiments took a glass tube with two electrodes at either end, and by applying a high voltage between the electrodes an electric current was produced. The strange thing was that he seemed to be able to actually see the current because an arc of light appeared between the two electrodes.

Things became even stranger when he removed the gas completely from the tube and applied the voltage across a vacuum. The arc of light disappeared. But, bizarrely, the glass at the end of one tube was found to fluoresce. Stick a metal cross in the tube and a cross-shaped shadow appeared in the middle of the glowing fluorescent patch.

Electrons emitted from the cathode that hit the opposite wall cause the glass to fluoresce.

The shadow always appeared opposite the negative electrode, otherwise known as the cathode. The best explanation was that the cathode was emitting some sort of ray that interacted with matter and made it glow – either the gas in the tube or, in the case of the vacuum, the glass of the tube itself.

These ‘cathode rays’ were something of a mystery. They were found to pass right through thin sheets of gold when they were placed in the way. Were they some sort of wave-like phenomenon like light? Others thought they were made up of negatively charged particles spat out by the negative electrode and then attracted to the positive electrode. But how could these particles pass through solid gold?

If they were negatively charged particles, then, Thomson believed, he should be able to change their path through the tube by applying a magnetic field. The German physicist Heinrich Hertz had already tried this and failed, but Hertz hadn’t removed enough gas, which interfered with the experiment. With the gas removed, things worked just as Thomson had hoped. Apply a magnetic field to the rays and sure enough the shadow shifted. The rays were being bent by the magnet.

The real surprise came when Thomson made a mathematical calculation of what the mass of these charged particles must be. If you apply a force to a mass then, as Newton’s laws of motion state, the amount you’ll be able to move it will depend on the mass. So the amount of deflection that a magnetic field will cause will have encoded in it information about the mass of this proposed particle.

The calculation also depends on the charge on the particle, and once this was determined in a separate experiment Thomson could work out the mass. The answer was startling. It was nearly 2000 times smaller than the mass of a hydrogen atom, the smallest atom in the periodic table.

That these particles seemed to originate from the metal making up the electrode led to the hunch that these particles were actually smaller constituents of the atom. The atom wasn’t indivisible after all. There were smaller bits. They were called electrons, the name originating from the Greek word for amber, the first substance to exhibit a charge.

The discovery that atoms are made up of even smaller constituents was a shock to many scientists’ view of the world. After Thomson gave a lecture on his findings:

I was told long afterwards by a distinguished physicist who had been present at my lecture that he thought I had been pulling their leg.

THE NEXT LAYER

Even when Thomson used a different metal, the masses of particles emitted by the metal didn’t change. It seemed like every atom had these particles as constituents. The first thought was that a hydrogen atom, given that it is 2000 times heavier than this new electron, might be made up of 2000 or so of these electrons. But a helium atom was roughly four times the mass of a hydrogen atom. Why would the number of electrons jump from 2000 to 4000 with nothing in between? This whole-number ratio between masses of atoms in the periodic table had been one of the reasons for supposing they were truly atomic. So what could account for these discrete steps in mass? Furthermore, atoms were electrically neutral. So were there other particles that cancelled out the charge on the electron? Could you get atoms to emit positive particles to counter these negative electrons?

There was actually evidence in the experiments for a positive ray of particles running in the opposite direction. When a magnetic field was applied, they were much harder to deflect, implying that they were more massive than the electrons. The curious feature this time was that the masses of these particles seemed to vary according to the gas that was being used to fill the tubes. For hydrogen the mass was essentially the mass of the atom you started with. It seemed that the hydrogen atoms in the tube were having their electrons stripped off, leaving a large positive particle that was then attracted to the opposite electrode.

Thomson managed to achieve a similar effect with other gases: helium, nitrogen, oxygen. The masses were all whole-number multiples of the positive particle produced by the hydrogen atom. Atomic harmony yet again. As yet, there was no reason to believe that there weren’t just many sorts of positive particles, just as there were many sorts of atoms. Thomson had suggested a model of the atom known as the plum pudding. The positively charged part of the atom, which was more massive than the negative electron, formed the pudding making up the bulk of the atom, while the electrons were the tiny fruit inside.

Then the age of the bombardment of the atom began which would eventually lead to the ultimate atom smasher: the Large Hadron Collider at CERN. The New Zealand-born British physicist Ernest Rutherford is generally credited with the discovery of the proton, the particle that was the building block for all these positive particles that Thomson had investigated.

Rutherford became fascinated by the new subject of radioactivity. Uranium atoms seemed to be spitting out particles that could be picked up by photographic plates. There appeared to be two types of radiation, and these became known as alpha particles and beta particles. The alpha particles were more easily detected. Rutherford found that using a magnetic field he could deflect these alpha rays in the same way that Thomson had deflected the negative particles. Calculations showed that they had the same mass as the stripped helium atoms. Their hunch that the alpha rays being emitted by the uranium were actually bits of helium atoms was confirmed when the alpha rays were combined with a shower of electrons, which resulted in a stable gas being formed. Chemical analysis soon confirmed that the gas was indeed helium.

TISSUE PAPER BALLISTICS

It was when Rutherford’s student Hans Geiger placed a thin sheet of gold foil between a stream of alpha particles and the plate detecting the particles that the evidence once again contradicted the theoretical model of the atom. In the model of the atom which has positive charge distributed evenly like a pudding, positive alpha particles passing through the metal would be repelled by the positive charge in the atom. Given that the charge is distributed over the full extent of the atom, you wouldn’t expect much deflection.

Alpha particles being deflected by the nuclei of atoms of gold.

Geiger found that, on the contrary, some of the alpha particles were deflected wildly, to the extent that some bounced back off the gold foil in the direction they’d been fired from. Rutherford was staggered: ‘It was as if you fired a 15-inch shell at a piece of tissue paper and it came back and hit you.’

Again it was mathematical calculations that gave rise to a new model. By counting how many alpha particles were deflected, and by how much, they discovered that the data was consistent with the charge and mass being concentrated in a tiny centre of the atom, which became known as the nucleus. It still wasn’t clear whether this nucleus was indivisible or not.

When Rutherford bombarded lighter atoms with alpha particles evidence emerged that the nucleus wasn’t a single entity but made up of constituent particles. Tracing the paths of the alpha particles in a cloud chamber, he detected paths that were four times longer than they should be. It was as if another particle four times as light was being kicked out of the nucleus by the impact of the alpha particles. Different gases produced the same result. Indeed, Rutherford found that pure nitrogen was being converted into oxygen by the impact. Knock out one of these particles and the element changed.

Here was evidence for a building block from which all nuclei of atoms were built. It behaved just like the hydrogen atom with its electron stripped off. Rutherford had discovered the proton. The nuclei of atoms were built by taking multiples of this proton. The only trouble was that the charge on the atom didn’t make sense. Helium had a nucleus that was four times as heavy as the hydrogen atom, yet the charge was only twice as big. Perhaps there were electrons in the nuclei attached to protons, cancelling out the charge. But the physics being developed to explain the behaviour of these particles precluded electrons and protons in such close proximity, so that couldn’t be the answer.

This led Rutherford in the 1920s to guess that there might be a third constituent, which he called a neutron, with the same ball-park mass as the proton but no charge. Producing evidence for this particle proved very tricky. He used to discuss with his colleague James Chadwick crazy ways by which they might reveal the neutron. Experiments conducted in the 1930s in Germany and France eventually picked up particles being emitted when various nuclei were bombarded with alpha particles, and, unlike the proton, these particles did not seem to possess any charge. But the experimenters mistakenly believed it was some sort of electromagnetic radiation, like the high-frequency gamma rays that had been discovered by French physicist Paul Villard at the beginning of the century.

Chadwick, though, was convinced that these particles must be the neutrons he’d discussed with Rutherford. Further experiments revealed that they had mass just slightly bigger than the proton, and without charge this new particle was the missing ingredient that made sense of the numbers. With Chadwick’s discovery it seemed as if the building blocks of matter had been revealed.

It was a very attractive model. Fire, earth, air and water, the four elements of Aristotle, had been reduced to three particles: the electron, proton and neutron. With these three building blocks scientists believed they could build all matter. Oxygen: 8 protons, 8 neutrons and 8 electrons. Sodium: 11 protons, 12 neutrons and 11 electrons. It was as if the music of the spheres was singing out and the foundations of matter were these notes: protons, electrons and neutrons. All matter seemed to be made up of whole-number combinations of these three particles. Why would you expect these particles to be made up of smaller entities? If they were, you might expect to see fractional pieces between the elements in the periodic table.

Except the dividing didn’t stop there. It turned out that there were experimentally and mathematically very robust reasons to think that protons and neutrons were not indivisible. But the building blocks of the proton and neutron have a strange property: they don’t like to be seen in isolation. They only come in groups, making up something like a proton or a neutron. Safety in numbers. So if they have never been seen on their own, why do scientists think there are even smaller bits into which we can divide protons and neutrons?

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