Every world in a grain of sand: John Nash’s astonishing geometry

(Published at The Conversation.)

As has been widely reported, John Forbes Nash Jr died tragically in a car accident on May 23 of this year. Many tributes have been paid to this great mathematician, who was made famous by Sylvia Nasar’s biography A Beautiful Mind and the subsequent movie based on that book.

Much has been said about Nash’s work on game theory. But less has been said about Nash’s other mathematical achievements. Many mathematicians who understand Nash’s work would agree, I think, that although his work in game theory had the most impact on other fields, Nash made other breakthroughs which were even more impressive.

Apart from game theory, Nash worked in fields as diverse as algebraic geometry, topology, partial differential equations and cryptography.

But perhaps Nash’s most spectacular results were in geometry. To honour Nash’s life, I would like to try to give a flavour of some of this work.

John Nash and pure mathematics

A great deal of Nash’s work was in the field of geometry. But this kind of geometry – differential geometry – is very different from the geometry learned at high school. It is not about trigonometry or Pythagoras, as found in secondary maths textbooks. Rather, it is about topics like surfaces, curvature and smoothness.

Like all pure mathematicians, Nash proved theorems: logical statements that are rigorous, precise and absolutely true, with no tolerance for vagueness. The world of pure mathematics is austere and often abstruse, but its claims to truth are eternal and absolute.

Well, that’s the theory at least. Breakthroughs in pure mathematics are often at the very limits of human understanding. It takes time, even for those in the field, to fully comprehend new developments.

Nash’s work was an extreme case. His papers could be chaotically presented, hard to follow and his approaches to problems were often unlike anything that had come before him, bamboozling students and experts alike. But he was almost otherworldly in his creativity.

While mathematical arguments are tightly constrained by the rigorous requirements of logic, Nash’s constructions and methods were wild. And nowhere was this more so than in his work on geometry.

Nash’s geometry

Take a flat sheet of paper. You can bend it, but without ripping it or creasing it, what shapes can you make? You can’t make a sphere, or even a section of a sphere, because a sphere is curved, while the paper is flat.

But you can make a cylinder. And even a cone, as you’ll know if you’ve ever seen a dunce’s hat. (This fact is also useful for making waffle cones, as shown below.)

Waffle cones start off as flat surfaces. Source: Gotham3 on Imgur.

As it turns out, even though a cylinder or a cone looks curved, it is intrinsically flat. In an undergraduate course on differential geometry (such as the one I teach at Monash), one studies this intrinsic curvature, and it turns out that there are lots of flat surfaces.

This surface might not look flat, but it is. Source: Richard Morris on Wikipedia.

These ideas were around for hundreds of years before Nash, but Nash took them much further.

The embedding problem

Nash took up the idea of “embedding” a surface: placing it into space without tearing, creasing or crossing itself. An embedding which does not distort the surface’s intrinsic geometry is “isometric”. In other words, the surfaces above are “isometric embeddings” of the plane into 3-dimensional space.

The isometric embedding question can be asked not just for the plane, but for any possible surface: spheres, donuts (which mathematicians call tori to try to sound respectable) and many others.

As it turns out, there are surfaces that are so strongly curved or tangled up that they cannot be embedded into 3-dimensional space at all. In fact, they can’t even be embedded into 4-dimensional space.

But Nash showed that any surface can be embedded into 17-dimensional space. Extra dimensions, far from making the problem even more difficult, actually make it easier – giving you more room to embed your surface! Later on, Nash’s work was improved by others, and we now know that any surface can be embedded into 5-dimensional space.

However, surfaces are only 2-dimensional. And Nash was interested in surfaces of any possible dimension. These higher dimensional analogues of surfaces are known as “manifolds”.

Nash proved that you can always embed a manifold into space of some dimension, without distorting its geometry. With this momentous result, he solved the isometric embedding problem.

Nash’s proof of the isometric embedding problem came as a complete surprise to much of the mathematical community. His methods were revolutionary. The great mathematician Mikhail Gromov said that Nash’s work on the embedding problem struck him to be “as convincing as lifting oneself by the hair”. But after great effort, Gromov finally understood Nash’s proof: at the end of Nash’s lengthy argument, Gromov said, Nash “miraculously, did lift you in the air by the hair”!

Isometric embedding in action

Gromov went on to develop his own ideas, inspired by Nash’s work. He wrote a book – similarly renowned among mathematicians for its incomprehensibility, just like Nash’s work – in which he developed a method called “convex integration”.

Gromov’s method had several advantages. One is that it is easier to draw pictures of an embedding made with his convex integration method. Prior to Gromov, we knew isometric embeddings existed, and had wonderful properties, but had a very tough time trying to visualise them, not least because they were often in higher dimensions.

In 2012, a team of French mathematicians produced computer graphics of isometric embeddings using Gromov’s convex integration methods. They are extremely intricate, almost fractal-like, yet smooth. Some are shown below.

The world in a grain of sand

Nash’s work on the isometric embedding problem has many facets and has led to huge amounts of subsequent research.

One particularly amazing aspect is how isometric embeddings are constructed. Nash’s work, combined with subsequent work by Nicolaas Kuiper, showed that if you wanted to isometrically embed a surface in 3-dimensional space, it’s enough to be able to shrink it.

If you have a “shrunken” embedding of your surface – that is, with all lengths decreased – then Nash and Kuiper show how you can obtain an isometric embedding of your surface just by adjusting your shrunken version a bit.

This sounds ridiculous. For instance, take a sphere – say the surface of a tennis ball – and imagine shrinking it down to have a nanometre radius. Nash and Kuiper show that by “ruffling” the surface sufficiently (but always smoothly; no creasing or folding or ripping or tearing allowed!) you can have an isometric copy of your original tennis ball, all contained within this nanometre radius. This type of “ruffling” of the surface was reproduced in the French team’s computer graphics.

The French team considered taking a flat square piece of paper. Glue the top side to the bottom side, to get a cylinder. Now glue the left side to the right side. If you think about it, you might be able to see that you get a donut. But you’ll find the paper is now creased or distorted.

Can you embed it into 3-dimensional space without distortion? Nash and Kuiper say “yes”. Gromov says “use convex integration”. And the French mathematicians say “this is what it looks like”!

Isometric embedding of the square flat torus in ambient space. Hevea Project, CC BY-SA.

More pictures are available at the Project’s website.

But the mathematical theorem doesn’t just apply to tennis balls or donuts: the theorem holds for any manifold of any dimension. Any world can be contained in a grain of sand.

How did he do it?

Nash had a rare combination of genius and hard work. In her biography of Nash, Sylvia Nasar details his formidable intensity and effort spent working on the problem.

As is well known from the movie, Nash came to believe in outlandish conspiracy theories involving aliens and supernatural beings, as a result of his schizophrenia. When later asked why he, an extremely intelligent scientist, could believe in such things, he said those ideas “came to me the same way that my mathematical ideas did. So I took them seriously”.

And frankly, if my head told me ideas as accurate and as insightful as those needed to prove the isometric embedding theorem, I’d likely trust it on aliens and the supernatural too.

The A-polynomial, symplectic geometry, and quantisation, May 2015

On 15 May, 2015 I gave a talk at the University of Melbourne, in the Moduli Spaces seminar.

Title: The A-polynomial, symplectic geometry, and quantisation

Abstract: The A-polynomial is a knot invariant based on the SL(2) representation theory of a knot group. It has long been known to have close connections to hyperbolic geometry, but it has returned with a vengeance in recent years, appearing in various guises from physics, and motivating mathematical statements such as the AJ conjecture. In this talk I’ll outline the A-polynomial and some work of Dimofte in which he considered its relation to Chern-Simons theory. In particular, I’ll talk about methods to calculate the classical A-polynomial, and its quantisation, via symplectic geometry.

Paranoid defence controls could criminalise teaching encryption

(A version of this article was also published at The Conversation.)

You wouldn’t think that academic computer science courses could be classified as an export of military technology.

But unfortunately, under recently passed laws, there is a real possibility that innocuous educational and research activities could fall foul of Australian defence export control laws.

Under these laws, despite recent amendments, such “supplies of technology” — and possibly a wide range of other benign activities — come under a censorship regime involving criminal penalties of up to 10 years imprisonment.

The Defence and Strategic Goods List

How could this be?

The story begins with the Australian government’s list of things it considers important to national defence and security. It’s called the Defence and Strategic Goods List (DSGL). Goods on this list are tightly controlled.

Regulation of military weapons is not a particularly controversial idea. But the DSGL covers much more than munitions. It includes many “dual use” goods – goods with both military and civilian uses – including for instance substantial sections on chemicals, electronics, and telecommunications.

Disturbingly, the DSGL veers wildly in the direction of over-classification, covering activities that are completely unrelated to military or intelligence applications. To illustrate, I will focus on the university sector, and one area of interest to mathematicians like myself — encryption — which raises these issues particularly acutely. But similar considerations apply to a wide range of subject material, and to commerce, industry and government.

Encryption: An essential tool for privacy

Encryption is the process of encoding a message, so that it can be sent privately; decryption is the process of decoding it, so that it can be read. Encryption and decryption are two aspects of cryptography, the study of secure communication.

As with many technologies subject to “dual use” regulation, the first question is whether encryption should be covered at all.

Once the preserve of spies and governments, encryption algorithms have now become an essential part of modern life. We use them almost every time we go online. Encryption is used routinely by consumers to guard against identity theft; by businesses to ensure the security of transactions; by hospitals to ensure the privacy of medical records; and much more. Given that email has about as much security as a postcard, encryption is the electronic equivalent of an envelope.

Encryption is perhaps “dual use” in the narrow sense that it is useful to both military/intelligence agencies as well as civilians; but so are other “dual use” technologies like cars.

Moreover, while States certainly spy on each other, essentially everyone with an internet connection is known to be spied on. Since the Snowden revelations — and much earlier for those who were paying attention — we know about mass surveillance by the NSA, along with its Five Eyes partners, which include Australia.

While States have no right to privacy — this is the whole point of Freedom of Information laws — an individual’s right to privacy is a fundamental human right. And in today’s world, encryption is essential for citizens to safeguard this human right. Strict control of encryption as dual-use technology, then, would not only be a misuse of State power, but the curtailment of a fundamental freedom.

How the DSGL covers encryption

Nonetheless, let’s assume for the purposes of argument that there is a justification for regarding at least some aspects of cryptography as “dual use”. (Let’s also put aside the efforts of government, stretching back over decades now, to weaken cryptographic standards and harass researchers.)

The DSGL contains detailed technical specifications covering encryption. Very roughly, it covers encryption above a certain “strength” level, as measured by technical parameters such as “key length” or “field size”.

The practical question is how high the bar is set: how powerful must encryption be, in order to be classified as “dual use”?

The bar is set low. For instance, software engineers debate whether they should use 2048 or 4096 bits for the RSA algorithm, but the DSGL classifies anything over 512 as “dual-use”. It’s probably more accurate to say that the only cryptography not covered by the DSGL is cryptography so weak that it would be foolish to use.

Moreover, the DSGL doesn’t just cover encryption software: it also covers systems, electronics and equipment used to implement, develop, produce or test it.

In short, the DSGL casts an extremely wide net, potentially catching open source privacy software, information security research and education, and the entire computer security industry, in its snare. This is typical of its approach.

Most ridiculous, however, are some badly flawed technicalities. As I have argued elsewhere, the specifications are so poorly written that they potentially include a little algorithm you learned at primary school called division. If so, then division has become a weapon, and your calculator (or smartphone, or computer, or any electronic device) is a delivery system for it.

These issues are not unique to Australia: the DSGL encryption provisions are copied almost verbatim from the Wassenaar Arrangement, an international arms control agreement. What is unique to Australia is the harshness of the law relating to the list.

Criminal offences for research and teaching?

The Australian Defence Trade Controls Act (DTCA) regulates the list, and enacts a censorship regime with severe criminal penalties.

The DTCA prohibits the “supply” of DSGL technology to anyone outside Australia without a permit. The “supply” need not involve money, and can consist of merely providing access to technology. It also prohibits the “publication” of DSGL technology, but after recent amendments, it only applies to half the DSGL: munitions only, not dual-use technologies.

What is a “supply”? The law does not define the word precisely, but the Department of Defence seems to think that merely explaining an algorithm would be an “intangible supply”. If so, then surely teaching DSGL material, or collaborating on research about it, would be covered.

University education is a thoroughly international and online affair — not to mention research — so any such supply, on any DSGL topic, is likely to end up overseas on a regular basis.

Outside of academia, what about programmers working on international projects like Tor, providing free software so citizens can enjoy their privacy rights online? Network security professionals working with overseas counterparts? Indeed, the entire computer security industry?

Examples of innocuous, or even admirable, activities potentially criminalised by this law are easily multiplied. Such activities must seek government approval or face criminal charges — an outrageous attack on academic freedom, chilling legitimate enquiry, to say the least.

To be sure, there are exceptions in the law, which have been expanded under recent amendments. But they are patchy, uncertain and dangerously limited.

For instance, public domain material and “basic scientific research” are not regarded as DSGL technology. However, researchers by definition create new material not in the public domain; and “basic scientific research” is a narrow term which excludes research with practical objectives. Lecturers, admirably, often include new research in teaching material. In such circumstances none of these provisions will be of assistance.

Another exemption covers supplies of dual-use technology made “preparatory to publication”, apparently to protect researchers. But this exemption will provide little comfort to researchers aiming for applications or commercialisation; and none at all to educators or industry. A further exemption is made for oral supplies of DSGL technology, so if computer science lecturers can teach without writing (giving a whole new meaning to “off the books”!) they might be safe.

Unlike the US, there is no exception for education; none for public interest material; and indeed, the Explanatory Memorandum makes clear that the government envisions universities seeking permits to teach students DSGL material – and, by implication, criminal charges if they do not.

On a rather different note, the DTCA specifically enables the Australian and US militaries to freely share technology.

Thus, an Australian professor emailing an international collaborator or international postgraduate student about a new applied cryptography idea, or explaining a new variant on a cryptographic algorithm on a blackboard in a recorded lecture viewed overseas — despite having nothing to do with military or intelligence applications — may expose herself to criminal liability. At the same time, munitions flow freely across the Pacific. Such is Australia’s military export control regime.

Now, there is nothing wrong in principle with government regulation of military technology. But when the net is cast as broadly as the DSGL — especially as with encryption — and the regulatory approach is censorship with criminal penalties — as with the DTCA’s permit regime — then the result is a vast overreach. Even if the Department of Defence did not exercise its censorship powers, the mere possibility is enough for a chilling effect stifling the free flow of ideas and progress.

The DTCA was passed in 2012, with the criminal offences schedule to come into effect in May 2015. Thankfully, emergency amendments in April 2015 have provided some reprieve.

Despite those amendments, the laws remain paranoid. The DSGL vastly over-classifies technologies as dual-use, including essentially all sensible uses of encryption. The DTCA potentially criminalises an enormous range of legitimate research and development activity as a supply of dual-use technology, dangerously attacking academic freedom — and freedom in general — in the process.

This story illustrates just one of many ways in which basic freedoms are being eroded in the name of national security.

Unless further changes are made, criminal penalties of up to 10 years prison will come into effect on 2 April 2016.

The day after April fool’s day. Jokes should be over by then.

The CIA 119

Years and years on, abuses continue.

The Bureau of investigative Journalism, together with the Rendition Project, is still trying to piece together the CIA’s kidnapping (“rendition”) and torture programme.

Only in December 2014 did the US Senate Intelligence Committee release its <summary of its report into the programme — a programme which, at least according to this report summary, effectively ended in 2006.

It took nearly ten years after the fact for an official report to arrive.

And this report, despite arriving so late on the scene, had only its summary published — the rest of the report is still classified to this day — and even the summary was the subject of bitter controversy among politicians. (Though what counts as controversial among US mainstream politicians is not a very good guide as to what matters are deserving of controversy: take global warming, for instance.)

Only with this report, well over a decade after most of the facts, only then did we learn the most basic facts about the program, like the number of people captured under it. The answer to that question, at least according to the report, is 119. They appear to have included people from dangerous terrorists, through to innocents sold to the CIA for profit.

The Bureau’s report begins to pull together the evidence to find out what happened to them. They were disappeared from their lives, disappeared into unaccountable captivity, disappeared into a legal black hole — and, in several cases, disappeared from history. The Bureau was unable to determine the fate of 39 of the abductees.

It is a story of no accountability, brutality and incompetence. To be sure, it apprehended some terrorists — though it appears that following a proper legal process, in every case, would have led to better results in terms of security and preventing terrorism, as well as, of course, following the law and abusing human rights. But other cases are ridiculous.

There is Laid Saidi, who was tortured by submersion in a bathtub of icy water and interrogated about a conversation in which he talked about aeroplanes (as if that were a crime) — except it turns out, thanks to faulty translation, he was talking about tyres. Saidi was later released — except he was released to the wrong country, so had to be taken back into custody and released again months later.

There is Khaled el Masri, who was detained by Macedonian authorities and held in a hotel in Skopje, then handed over to the CIA and taken to Afghanistan. There he was tortured by beatings, solitary confinement, and sodomy. His crime? Having a name similar to that of an alleged terrorist. He eventually won damages from Macedonia in the European Court of Human Rights, but his case is unusual in having won some recompense.

Of course, this is only one of many programs of the CIA as part of the “War on Terror” — a “war” which, for the most part, appears to have consisted of terror. And the CIA is only one of numerous US government agencies to have engaged in abuses. And, the United States is only one of many nations to have engaged in abuses — indeed, they all do, though the US still reigns supreme in its ability to project force around the globe. Australia has assisted many of these abuses.

Almost fourteen years after September 11 2001, more than ten years after most of the kidnappings, the struggle remains ongoing to find out what happened and why. These events offer not just a window into a particular time and circumstances, but the institutional circumstances in which unaccountable force is used and unpunished (or even “legal”) crimes are committed.

In Australia we have heard a lot recently about “lest we forget”. We should above all remember the abuses perpetrated by ourselves and our allies — lest we forget them, and in so doing enable them to happen again. The struggle of people against power has always been the struggle of memory against forgetting.

There is also the constructive question, in examining abusive organisations and programmes like this one, to identify what factors caused, or at least allowed, such horrors to happen. What better set of institutions can we build to ensure that similar abuses never happen again — and maintain peace and security for all?

The lower classes of things

Everything is free to move across borders, except… some lesser things.

It’s a long-standing principle of law, in the “developed” world at least, that “freedom” means the ability to move across borders without hindrance or restriction. This is commonly called “globalization”. Borders fade away and become irrelevant; non-discrimination becomes a defining, enlightened principle; and the world becomes one cosmopolitan village. Except, of course, that this otherwise laudable, advanced, cosmopolitan version of “freedom” applies only to inanimate material objects. To be fair, it does also apply to immaterial objects such as transfers of capital that exist only as abstract ideas, entries in spreadsheets or bits of information.

But one only needs to try to catch a boat from Indonesia to Australia to find out how much this well-established “freedom” and crowning glory of inanimate objects applies to living, breathing, feeling, thinking human beings.

Nonetheless, though it may be a great hypocrisy, this “freedom” of inanimate objects to move across borders is well-established. Such is the world we live in, where consumer goods such as cars and washing machines have advanced rights that humans do not have. This principle is enshrined in international treaties such as the General Agreement on Tariffs and Trade, and the various protocols adhered to be all member States of the World Trade Organisation.

However, this glorious liberty granted to inanimate objects, and even abstract objects, does not quite apply to all objects. Exceptions can be made, provided there is a special reason for it.

And, our world, divided into nation-states, is so organised that the highest decision-making authorities in the world pertain to geographic regions established largely by war, conquest and colonisation. So there is no more sanctified reason to limit freedoms than the military interests of States. In particular, weapons of war have much less freedom to flow across borders. The flow of weapons is tightly regulated — or at least, when it suits a State’s interest to do so.

Such is the idiosyncrasy and backwardness of human civilization in the early 21st century. Rights are given to inanimate objects — even abstract immaterial objects — but not sentient beings. Power lies with a tumultuous collection of clashing commonwealths, whose military interests are the highest good. Destructive weapons plague the world, but weapons are almost alone among inanimate objects in being subject to regulation.

Weapons are deprived of the rights accorded to other inanimate objects, and in this lie with other lower classes of things, such as hazardous waste, disease carriers, dangerous chemicals, plants, animals, and human beings.

Why your calculator (and computer, and phone…) is a weapon

The Australian government may have classified your calculator — and phone, and computer, and every electronic device you own — as military weapons.

You wouldn’t think your phone, or calculator, or laptop computer, is a weapon on par with tanks, rockets, and missiles. But the Australian government may well have classified it as one, thanks to a very interesting display of scientific and mathematical ignorance.

Now, most people, I think, wouldn’t have too much of a problem with the government sensibly regulating things like munitions, artillery, and weapons of mass destruction. But if that regulation were not sensible, then there might be a problem. And if that regulation extended to include things like your iPad, then there might be a big problem. Unfortunately, the Australian government has quite possibly done precisely that.

The Australian government maintains a list of all the things it considers important to national defence and security. It’s called the Defence and Strategic Goods List. Goods on this list are tightly controlled: there are heavy penalties for proliferating them.

Now, to be fair, compiling such a list is not easy. The list needs to remain current with science and technology, which in many fields is rapidly advancing. Moreover, defining what is and isn’t a military-grade weapon may be a bit more difficult than you think. Some objects have dangerous military uses as well as safe civilian uses.

Nonetheless, there is very little to indicate that the Defence and Strategic Goods List has been designed with the requisite degree of diligence.

Others have raised issues about the List: for instance, the National Tertiary Education Union (NTEU) is running a campaign on the issue and has set up a very informative website about it. Even the Senate Foreign Affairs Defence and Trade Committee report on the topic concluded that the law “would benefit from further scrutiny”, with half the committee describing it as “a complex and flawed piece of legislation”.

That’s not to mention the specific issues have raised about its effects on various research fields. For instance, my colleague Kevin Korb at Monash has calculated that 18 out of 61 masters level courses in the Faculty of Information Technology would fall under the strict controls of the List.

As a mathematician, I want to focus on one particular part of the list: encryption. And this particular part of the list, properly understood, overreaches enormously into everyday life.

Encryption: for people, not the State

But before going into the details of the List‘s definitions, it’s worth considering: why should encryption be regarded as a weapon in the first place?

Encryption is not a physical thing; messages and information are encrypted by algorithms running in programs on computers or other devices. An algorithm is a procedure, or recipe, that can be implemented on a computer; it’s an abstraction, an idea. Can an abstraction really be regarded as a weapon, or a “strategic good”?

Even if it can, encryption is by its nature not a uniquely military or intelligence thing. Anyone who wants to send a private communication on the internet does it by encryption. It’s a “dual use” technology, in the sense that it has both military and civilian uses. But there are dual use technologies like gas centrifuges, which have a small number of specific usages: gas centrifuges can be used for civilian nuclear reactors, and alternatively for nuclear weapons development. On the other hand, there are “dual use” technologies like cars, which are general purpose objects, used by almost everybody, for a wide variety of uses, but which nonetheless can also be useful to military and intelligence agencies. Encryption is much more like a car than a gas centrifuge.

Military and intelligence services may well use encryption so that their enemies can’t read their messages. But you and I also use encryption so that eavesdroppers can’t read our messages. Everyday users of the internet use encryption to safeguard their privacy. Consumers use encryption to guard against identity theft. Banks use encryption to assure customers of the integrity of financial transactions. Businesses use encryption to ensure the security of online transactions. Hospitals use encryption to ensure the privacy of patient medical records.

Basically, any time anything is done electronically with a need for privacy, encryption is used, and must be used. In a modern technologically advanced society, almost everybody uses it, whether they know it or not. It is far from the unique province of national security, military or intelligence agencies; it has become an essential and routine part of modern life.

When we don’t want our messages to be read by others, we can encrypt them; everybody needs to do this, should do this, and often does do this. So can the military; so can intelligence. What’s the difference?

Well, there is an important difference: ordinary people face highly technologically sophisticated adversaries.

On the one hand, recent military engagements have been fought in weak States such as Iraq, East Timor and Afghanistan. Those wars which have been fought in our name, when not killing hundreds of thousands of civilians, have been fought primarily against weak militaries and relatively unsophisticated armed groups (though, to be sure, these armed groups have sometimes possessed dangerous and lethal weapons, and effective organisation).

On the other hand, since the Snowden revelations — and much earlier for those who were paying attention — essentially all internet users have at least one known adversary snooping on their communications, which is extremely well financed, resourced, and technologically sophisticated: the NSA, along with its Five Eyes partners, which include Australia. Governments might rightly suspect that other governments are spying on them, but we know the NSA engages in mass surveillance of essentially the whole world; as such, citizens are arguably entitled to at least as much self-defence over their information, in the form of encryption, as States. Indeed, States have no inherent right to privacy — the whole point of Freedom of Information laws is that they should be transparent in their operations unless they have good reason — while an individual’s right to privacy is a fundamental human right.

As the comedian John Oliver pointed out in his recent interview with Edward Snowden, many people might not purport to care about surveillance, if they think they’re doing “nothing wrong”. But if it is made clear that mass surveillance means that the NSA has copies of your most private and embarrassing communications — because the nature of mass surveillance is to collect everything — then they might have a different view. Very few people would agree that the government should have copies of dick pics. And more people have sent dick pics than you might think.

Nonetheless, let’s assume for the purposes of argument that there is a justification for regarding at least some aspects of cryptography as “defence” or “strategic goods”. After all, there’s more to cryptography than encoding and decoding messages; encrypted messages can also be analysed, attacked, hacked; and some cryptographic algorithms are more secure than others. (Let’s also put aside the efforts of government, stretching back over decades now, to weaken cryptographic standards and harass researchers in the field.) If the Defence and Strategic Goods List only purported to regulate a truly ultra-secure encryption system, which was out of the reach of individual citizens, and hence was irrelevant to the everyday lives of ordinary people, it might not be quite as bad as if it covered encryption algorithms widely used and available to all.

Which it does. And much, much more — like calculators. But we might need to look at some mathematics in order to understand why.

Encryption in the Defence and Strategic Goods List

Section 5A002.a.1.b.3 of the List (yes, it really has sub-sub-sub-sub-sections) declares certain things to be subject to its control:

5A002 “Information security” systems, equipment and components therefor, as follows:
a. Systems [and] equipment… for “information security”, as follows…
1. Designed or modified to use “cryptography” employing digital techniques performing any cryptographic function other than authentication or digital signature and having any of the following:
b. An “asymmetric algorithm” where the security of the algorithm is based on any of the following:
3. Discrete logarithms in a group… in excess of 112 bits

This definition appears extremely technical and advanced. But when those words are understood, your calculator — indeed any technology that can do multiplication and division — has just been described as a weapon.

Let’s see why.

A little pure mathematics — groups

In pure mathematics — specifically, in abstract algebra — there are things called groups. Many of the things that scientists, engineers and students do every day involve groups. Like many concepts in pure mathematics, they are abstract objects: they are defined in terms of axioms, and anything that satisfies the axioms is a group. Many objects that engineers, scientists, and programmers work with every day are groups, and much of the arithmetic everyone knows from primary school can be understood as a special case of group theory.

Roughly speaking, a group — I’ll call it \(G \) — is a set containing certain elements, with a certain operation. The operation could be anything, provided it satisfies the axioms. The operation gives you a way to take two elements \(a,b \) of \(G \) and get a third element \(c \). You can denote the operation by a dot, as in

\(\displaystyle a \cdot b = c. \)

However, the operation must satisfy some requirements, such as: there must be an identity element that “does nothing”; and each element must have an inverse element that “undoes” it.

Sound confusing? Well, it’s an advanced concept and I don’t have space here to give you an abstract algebra course! But here are some examples.

For instance, the group \(G \) could be the integers, or whole numbers (often written as \(\mathbb{Z} \) ), and the operation could be addition \(+ \). Well then, when you put 2 and 2 together, you get 4. (See, abstract algebra is as easy as putting 2 and 2 together! Maybe.) When you put 7 and 2 together, you get 9. When you put 7 and -2 together, you get 5. When you put 0 and 11 together, you get 11. In fact, when you put 0 and any integer \(n \) together, you get \(n \), so 0 “does nothing”: 0 is the identity. And when you put 3 and -3 together, you get 0. When you put 7 and -7 together, you get 0. Each integer \(n \) has an inverse, which is the negative \(-n \) of that number. We can write these facts as

\(\displaystyle 2 \cdot 2 = 4, \; 7 \cdot 2 = 9, \; 7 \cdot (-2) = 5, \; 0 \cdot 11 = 11, \; 0 \cdot n = n, \; 3 \cdot (-3) = 0, \; 7 \cdot (-7) = 0, \; n \cdot (-n) = 0. \)

(Usually at school we reserve the dot symbol for multiplication! And, admittedly, mathematicians use the \(+ \) symbol for some types of groups too. But it’s important for our purposes to emphasise the group operation, so, despite being possibly confusing, I will always write it with a dot.)

For another example, the group \(G \) could be the positive numbers (often written as \( \mathbb{R}_+ \) ), and the operation could be multiplication \( \times \). When you put 2 and 2 together, you again get 4! (Again, as easy as putting 2 and 2 together! Again, maybe.) But now when you put 7 and 2 together, you get 14. When you put 2 and \(\frac{1}{3} \) together, you get \(\frac{2}{3} \). When you put 3 and \(1.4 \) together, you get \(4.2 \). When you put 1 and 17 together, you get 17. In fact, when you put 1 and any positive number \(x \) together, you get \(x \), so 1 “does nothing”: now 1 is the identity. When you put together 3 and \( \frac{1}{3} \), you get 1; when you put together 7 and \( \frac{1}{7} \), you get 1; and in general the inverse of each positive number \(x \) is its reciprocal \( \frac{1}{x} \).

\(\displaystyle 2 \cdot 2 = 4, \; 2 \cdot \frac{1}{3} = \frac{2}{3}, \; 3 \cdot 1.4 = 4.2, \; 1 \cdot 17 = 17, \; 1 \cdot x = x, \; 3 \cdot \frac{1}{3} = 1, \; 7 \cdot \frac{1}{7} = 1, \; x \cdot \frac{1}{x} = 1. \)

Is this reminding you of primary school arithmetic or high school algebra? Good, because you’ll need it to understand why your calculator has just been criminalised.

One last example is one you know intuitively when you tell the time. Let’s say we tell the time on a 12 hour clock. What time is it, 4 hours after 11 o’clock? It’s 3 o’clock. This means that, in clock arithmetic, \(11 + 4 = 3 \). When we add 11 and 4 in this way, we perform addition as usual but then take the remainder upon division by 12. This kind of arithmetic is known as “modular arithmetic” and it defines for us another group, often written \( \mathbb{Z}_{12} \). This group consists of 12 elements, namely the numbers from 1 to 12, and the operation is “clock addition”, which amounts to adding the numbers and then taking the remainder upon division by 12. You can check that 12 is the identity.

OK, enough abstract algebra for now.

Returning to the DSGL definition, you’ll see that it refers to a

group… in excess of 112 bits.

What does this mean? Nothing, it’s nonsense! Groups don’t have bits in them, they have elements in them. It goes to show that you shouldn’t get people who don’t understand what they’re talking about to write laws.

But what I think the authors of the DSGL meant, was a group that requires more than 112 bits to describe an element: that is, a group with more than \( 2^{112} \) elements.

Now, \(2^{112} \) is a rather enormous number. But it’s not so enormous you can’t write it down:

\(\displaystyle 2^{112} = 5,192,296,858,534,827,628,530,496,329,220,096. \)

Know any groups bigger than that? I do, and I just told you two of them. OK, the clock group \( \mathbb{Z}_{12} \) only has 12 elements, which is slightly less than \( 2^{112} \). But how many elements are there in the group \(\mathbb{Z} \) of integers? Or, how many elements are there in the group \( \mathbb{R}_+ \) of positive numbers? Infinitely many — staggeringly more than \(2^{112} \). Indeed, compared to infinity, any finite number is basically nothing. So actually, when the DSGL refers to a “group… in excess of 112 bits”, it could be referring to… well, you know, just your usual number systems, and addition or multiplication.

Discrete logarithms

Now, the next phrase to understand in the DSGL is “discrete logarithm” — something that sounds truly scary. Who even remembers what logarithms are, and what on earth are “discrete” ones?

Well, I’ll try to remind you of some high school algebra. Think back to when you learned about powers: for instance, \(2^5 \) usually means to multiply 2 together with itself 5 times. So, if you were asked to find \(2^5 \), you would do some repeated multiplication and get 32.

But suppose you were asked the reverse question: how many times do you need to multiply 2 by itself in order to get 32? What power of 2 gives you 32? From above, we know the answer is 5. And that is just another way of saying that the logarithm of 32 to base 2 is 5.

\(\displaystyle 32 = 2^5 \; \text{means the same as} \; \log_2 32 = 5. \)

That is, the logarithm of 32 to base 2 is the power to which you need to raise 2 in order to get 32. And more generally, the logarithm of \(a \) to base \(b \) is the power to which you need to raise \(b \) in order to get \(a \). Written in terms of equations,

\(\displaystyle a = b^x \; \Leftrightarrow \; \log_b a = x. \)

What does this have to do with groups? Well, just as we usually write an exponential like \(2^5 = 2 \cdot 2 \cdot 2 \cdot 2 \cdot 2 \) to mean the you multiply 5 twos together, we can do the same in any group. Instead of repeated multiplication, we now do the group operation repeatedly. So we write, for instance,

\(\displaystyle g^5 = g \cdot g \cdot g \cdot g \cdot g \)

to indicate that you do the group operation on 5 \(g \)’s together.

This leads to some rather strange-looking results. For instance, let’s consider what exponentials mean in the group \(\mathbb{Z} \) of integers with addition. Remember that in this group, the operation \(\cdot \) means addition. So, for instance,

\(\displaystyle 3^6 = 18, \)

because you do the group operation — addition — on 3, 6 times, and \(3+3+3+3+3+3 = 18 \).

On the other hand, in the group \(\mathbb{R}_+ \) of positive numbers with multiplication, the group operation is multiplication. So in this group

\(\displaystyle 3^6 = 729, \)

which is a more standard notation! This is what you would normally mean by \(3^6 \); you multiply it together 6 times.
Finally, in the “clock arithmetic” group \(\mathbb{Z}_{12} \),

\(\displaystyle 3^6 = 6. \)

Why? Because you add 3 to itself 6 times to get “18 o’clock”, which is 6 o’clock on a 12-hour clock.

Now, just as we can write exponentials, we can also write logarithms. Above, we wrote that, in the groups \( \mathbb{Z} \), \( \mathbb{R}_+ \) and \( \mathbb{Z}_{12} \) respectively,

\(\displaystyle 3^6 = 18, \; 3^6 = 729, \; 3^6 = 6.\)

Using the logarithm just how we did above, this means that, in the groups \( \mathbb{Z} \), \( \mathbb{R}_+ \) and \( \mathbb{Z}_{12} \) respectively,

\(\displaystyle \log_3 18 = 6, \; \log_3 729 = 6 \; \text{and} \; \log_3 6 = 6. \)

When you do a logarithm like this in a group, the exponent is always a whole number, and for this reason it’s called a discrete logarithm. (Well, there are some technicalities, but this is the gist of it.) And that is what the List is referring to.

Actually, the discrete logarithm in the group \( \mathbb{Z} \) with addition is just a ridiculously fancy way of describing something you learned in primary school. What does

\(\displaystyle \log_3 18\)

mean in the group \(\mathbb{Z} \)? It’s asking: how many times do you have to add 3 to itself to get 18? The answer, as we wrote above, is 6. And this is all a very roundabout way of saying that 18 divided by 3 is 6.

So, when you’re talking about the group \(\mathbb{Z} \) with addition, the “discrete logarithm” is just a ridiculously fancy way of talking about division: dividing one number by another.

And when the DSGL mentions “discrete logarithms in a group… in excess of 112 bits [sic]”, it covers the division of whole numbers. Therein lies the beginning of a serious problem.

Recall, the List (now annotated) refers to:

b. An “asymmetric algorithm” where the security of the algorithm is based on any of the following:
3. Discrete logarithms in a group… in excess of 112 bits division

You’d better hope there aren’t any asymmetric algorithms, where the security of the algorithm is based on division!

In the next section, I will show you an asymmetric algorithm where the security of the algorithm is based on division.

Cryptographic algorithms

Now finally, we get to cryptography. The DSGL refers to an “asymmetric algorithm”. Helpfully, the DSGL has a definition section, which defines this phrase as meaning

a cryptographic algorithm using different, mathematically related keys for encryption and decryption.

Well, let’s start with what an algorithm is: an algorithm is just a clear, well-defined procedure that tells you how to do something. It’s like a recipe, except it’s a recipe so precise that it can be implemented on a computer.

A cryptographic algorithm is an algorithm that, as you might surmise, involves cryptography. When you want to send a message, and don’t want it to be read by eavesdroppers, you encrypt it: you apply some procedure to it, called an encryption algorithm. The data is then written in code, or encrypted, and can’t be read by anyone unless they have a secret key to decrypt it. When they do, they use the key on the encrypted message, applying a decryption algorithm, to recover the original message. Taken together, this encryption-and-decryption protocol forms a cryptographic algorithm.

Now, the encryption of a message usually uses a key, and the decryption of a message also uses a key. This key can be a message, a password, a number, or a chunk of data, or something else, but whatever it is, it involves some extra information that goes into the encryption or decryption, in addition to the message itself.

If the key is the same for both encryption and decryption, then the algorithm is called symmetric. If the encryption and decryption keys are different, then the algorithm is called asymmetric.

Now, there are some extraordinarily clever and elegant cryptographic algorithms out there. In one common type of asymmetric algorithm, called public key cryptography, the encryption key is made fully public and open to everyone to see, while the decryption key is kept secret. For instance, on my website you can get my public key, so if you want to send me a secret message you can encrypt it with that public key; but only I have the decryption key, (unless the NSA or ASIO has been snooping into my stuff), so only I can decrypt it.

But there are also some very basic cryptographic algorithms.

For instance, suppose I want to send you a message:

The arc of the moral universe is long, but it bends towards justice.

One of the simplest cryptographic algorithms is known as the Caesar cypher, so-called because Suetonius wrote that it was used by Julius Caesar. This algorithm just shifts every letter along the alphabet a fixed number of places. So, for instance, we might shift every letter three places, as Caesar did: so A becomes D, B becomes E, and so on, up to W becomes Z. Then the alphabet “cycles” so that X becomes A, Y becomes B and Z becomes C. The encrypted message is then

Wkh duf ri wkh prudo xqlyhuvh lv orqj, exw lw ehqgv wrzdugv mxvwlfh.

To decrypt the message, you just shift each letter back by 3!

In a certain sense, the Caesar cypher is based on addition and subtraction: in the above example, we “added 3” to each letter to encrypt, and “subtracted 3” to each letter to decrypt. We could say that the encryption key was 3, and the decryption key was -3.

What I’d like to do now is describe to you a similar idea based on multiplication and division.
The first step in this encryption algorithm — like most encryption algorithms used today — is to convert the message into a number using a standard encoding scheme. Hexadecimal numbers are usually used, because they work well with computers. When I convert my message above to numbers, using a standard scheme, and putting some spaces in, I obtain

54 68 65 20 61 72 63 20 6f 66 20 74 68 65 20 6d 6f 72 61 6c 20 75 6e 69 76 65 72 73 65 20 69 73 20 6c 6f 6e 67 2c 20 62 75 74 20 69 74 20 62 65 6e 64 73 20 74 6f 77 61 72 64 73 20 6a 75 73 74 69 63 65 2e

Importantly, although this number is s written in hexadecimal, this is just a number. In decimal it is (with spaces inserted)

18 987 169 229 968 478 188 669 534 957 610 737 354 921 264 295 841 525 766 864 288 444 422 566 874 896 162 027 606 162 208 969 778 556 762 033 277 602 447 021 524 083 143 238 081 863 623 539 907 326 688 954 151 036 206.

Now, I’m going to perform an encryption algorithm by choosing a secret key. My secret key will be the number 6. (Well, the key’s not so secret now…) There are many reasons to like the number 6.

My encryption algorithm will multiply the message by the key, because, why not. Multiplication is, after all, the name of the game. So I multiply my message by the key (6), and it becomes, in hexadecimal,

1f a7 25 ec 24 8a e5 2c 29 c6 4c 2b a7 25 ec 29 09 ca e4 88 8c 2c 09 67 8c 66 0a eb 45 ec 27 8b 2c 28 a9 c9 66 b0 8c 24 ec 0b 8c 27 8b 8c 24 e6 09 65 ab 2c 2b a9 cc c4 8a e5 ab 2c 27 ec 0b 4b a7 85 45 f1 4

If you try to convert that to text, you’ll get something completely unintelligible: it renders on my computer as

?%?$??,)?L+?%?) ??, g?f
?E?’?,(??f??$? ?’??$? e?,+????,’? K??E?

This is the encrypted message. Although the encryption is just based on a simple multiplication, this message is certainly encrypted, and most people would be unable to decrypt it.

Now when you receive the message, you have your own secret key, which you are going to multiply by. Your secret key is \( \frac{1}{6} \). This number is chosen because when you multiply a number by 6 — as I have, to encrypt the message — and then you multiply by \( \frac{1}{6} \) — as you will, to decrypt it — you get the number you started with.

So, you take the unintelligible message, convert to hexadecimal, multiply by \( \frac{1}{6} \), back to text, and obtain the original message.

Now, I definitely do not recommend you use this algorithm! It is far too simple and easily broken! But it is not so different in flavour from algorithms that are actually used.

In the famous RSA scheme, for instance, rather than multiplying by the encryption key to encrypt the message, you raise the message to the power of the encryption key, and reduce like clock arithmetic. (However, rather than dealing with a 12-hour clock, the “clock” in RSA has an enormous number of “hours”. The number of hours is the product of two large prime numbers.) And rather than multiplying the encrypted message by the decryption key to decrypt, you raise the encrypted message to the power of the decryption key, and reduce. The encryption and decryption keys in RSA, however, are reciprocals: they are chosen to multiply together to 1 — once reduced like clock arithmetic (again, using a “clock” with an enormous number of “hours”).

So the idea I’ve described above is a bona fide cryptographic algorithm, similar in several essential ways to the widely used RSA algorithm, just much much weaker: it will not be decipherable by most people, but will be mincemeat in the hands of the NSA. It is an asymmetric algorithm, because it involves different keys for encryption and decryption (like 6 and \(\frac{1}{6} \) respectively), in a similar way to RSA.

And, disturbingly, my cryptographic algorithm is based on using whole numbers, i.e. the group \(\mathbb{Z} \) with addition. The encryption algorithm involves multiplication, which is just repeated addition. Indeed, in the (rather strange) notation we used above, just as \(3^6 = 18 \),

\(\displaystyle (\text{original message})^{(\text{encryption key})} = (\text{encrypted message}). \)

If you followed the discussion of logarithms above, you might remember that any time we consider powers in a group, we can alternatively consider logarithms. Indeed, the above equation is equivalent to

\(\displaystyle (\text{encryption key}) = \log_{(\text{original message})} (\text{encrypted message}). \)

Now I’ve told you how to break my cryptographic algorithm. If you know an original message and an encrypted message, you can work out the encryption key by doing a discrete logarithm — also known as division.

In other words, the security of this algorithm is based on discrete logarithms in the group \( \mathbb{Z} \). And, as we’ve discussed, the group \(\mathbb{Z} \) of integers is a group “in excess of 112 bits” [sic].

We have now come under the terms of the List.

The weaponisation of division

Having described a weak-but-bona-fide asymmetric encryption algorithm, let’s recall the definition in the DSGL:

5A002 “Information security” systems, equipment and components therefor, as follows:
a. Systems [and] equipment… for “information security”, as follows…
1. Designed or modified to use “cryptography” employing digital techniques performing any cryptographic function other than authentication or digital signature and having any of the following:
b. An “asymmetric algorithm” where the security of the algorithm is based on any of the following:
3. Discrete logarithms in a group… in excess of 112 bits

Well, I’m afraid everything I’ve just told you is certainly “cryptography, employing digital techniques to perform cryptographic
functions”. (It’s not authentication or digital signature; those are different things.) It uses an asymmetric algorithm. And the security is based on discrete logarithms in the discrete group \( \mathbb{Z} \) of whole numbers, which is infinite, with far more than “112 bits [sic]”.

And the “cryptography” I’ve just told you involves only two mathematical operations: multiplication and division. The “digital techniques” used to perform cryptographic functions are the good old \( \times \) and \( \div \) you learned in primary school. We described it in fancy language like “discrete logarithms”, but that’s only because the List uses this obfuscatory language.

So, the cryptographic algorithm I just described above is certainly covered by the List. But unfortunately the List covers more than just the algorithm itself. It also covers “systems” or “equipment.

Now a calculator is certainly a “system” or “equipment”. It is “designed” to do things like multiplication and division, and hence to do the “cryptography” described above. It employs “digital techniques” performing the “cryptographic functions” of multiplication and division. You “modify” the calculator to use this “cryptography” by typing the numbers and multiplying them. It has the “asymmetric algorithm” of multiplication and division built right into its hardware.

Your computer has a calculator on it. So do your smartphone and tablet, if you’ve ever looked. Indeed, any “equipment” you have that can do multiplication and division, is likely covered by this definition.

In the most generous reading, the List only covers your computer when you use it to actually perform the cryptographic algorithm. But it seems to me that the most natural reading of the List covers any computer which “has” the asymmetric algorithm of multiplication and division built into its hardware or software. That is, every computer.

The DSGL turns division into a weapon, and your computer into a delivery system for that weapon.

Now, I think that education can be a “weapon” used in self-defence against propaganda, and that mathematical fluency can be a very powerful “weapon” in understanding, and perhaps even changing, the world. But this is ridiculous!

The criminalisation of division

If you were accused of violating the List‘s controls on cryptographic technology by using your calculator, you could argue that section 5A002.a.1.b.3 should be read only to apply to you when you actually implement multiplication and division in an encryption algorithm. (Some also argue that “discrete logarithms” only exist in finite groups, effectively exempting the group of whole numbers \(\mathbb{Z}\).)

But that sort of legalistic reasoning, searching for loopholes, is not exactly an argument on which you would want to hang your freedom, when faced with criminal charges.

And criminal charges there are.

Section 10 of the Defence Trade Controls Act (DTCA) makes it a criminal offence to “supply DSGL technology” — that is, things on the List — to anyone outside Australia, unless you get a special permit from the Minister.

Now, to be fair, the DSGL and DTCA make many exceptions. It’s just that none of them apply to multiplication and division.

For instance:

  • There is an exception (Note 2) which states that the DSGL “does not control products when accompanying their user for the user’s personal use”. So if you are carrying your calculator and laptop and smartphone with you, you might have an excuse; but if you leave one of them at home, perhaps not. And if you are using it to send, say, messages about human rights activism which displeases the government, do you expect the government to regard that as your “personal use”?
  • There is another exception (Note 3) stating that the DSGL does not control goods that meet 4 conditions. Unfortunately, one of these conditions is that “The cryptographic functionality cannot easily be changed by the user”. I’m afraid that your calculator has a highly adaptable interface that allows you to enter any numbers you please as encryption and decryption keys, and multiply and divide as you need. The functionality is easily changed to fit new keys.
  • Under recent (April 2015) amendments to the DSGL, “basic scientific research” is not regarded as DSGL technology. Are you really going to claim that my woefully insecure “encryption algorithm” rises to the level of “basic scientific research”? I’m not.
  • Under the same amendments, technology in the public domain is not regarded as DSGL technology. Is my multiplication-and-division encryption algorithm in the public domain? While multiplication and division are certainly publicly known, for the algorithm described here it is not so clear. By publishing it here, where you’re reading it, I suppose I am putting it in the public domain; though you’ll see a Creative Commons “some rights reserved” sign below. And moreover, isn’t the act of publishing this actually my “supply” of it to you? Again, I wouldn’t be relying on this defence.
  • Also in April 2015, the DTCA was amended so that supplies of dual-use technology made “preparatory to publication” are exempt. Sadly, I fear my bona fide woeful encryption algorithm is not exactly publishable in a reputable scientific journal.
  • At the same time, an exemption was introduced for supplies of technology made orally. Alas, I’ve now written all this down…
  • I could rely upon the exemption for educational activity or public interest material. Oh, except there isn’t one.
  • Finally, I could rely on the blanket exemption granted to munitions supplies between the Australian and US militaries. Apart from the slight problem that I’m a civilian and my algorithm is only a dual use technology, not technically a munition. It works well to exempt actual weapons from control though!

So, if you are not in Australia, then by explaining to you a very bad but nonetheless bona fide asymmetric encryption algorithm now, I have arguably breached this section of the law.

Well, perhaps because you didn’t pay me for the information, it wasn’t a “supply”? No, the Act makes clear that a “supply” need not be for payment.

The penalty? Ten years’ imprisonment, or a fine of $425,000.

And, just in case our lawmarkers were afraid they didn’t cover every possibility, they also included in the same Act a section 14A which makes it a criminal offence to “publish” or “otherwise disseminate DSGL technology to the public, or to a section of the public, by electronic or other means”. Again, a penalty of 10 years in jail or $425,000 fine applies. However, there is an exception to this one, if the technology has already been lawfully made available to the public.

Luckily, multiplication and division have already been made available to the public. Times tables are not yet illegal… I hope. (And in recent amendments in April 2015, this offence was limited to munitions; it no longer applies to dual use technologies. Phew!)

Other concerns about cryptography

Now, the idea of turning multiplication and division into weapons and criminalising their use is so ridiculous that it’s almost impossible to imagine the List being interpreted that way — despite the fact that, taken at face value, this is exactly what it says.

But there are other, even greater concerns with the definition of cryptography in the List. Again, we put aside the question of whether it is legitimate to control cryptography at all.

I only quoted one sub-sub-sub-sub-section of the List. The section on cryptography covers much more. It essentially covers any sufficiently “strong” cryptography, including symmetric algorithms with key lengths over 56 bits, and RSA with integers over “512 bits”. Now what is a strong key and what isn’t changes rapidly as technology advances. And I don’t think many in the field would say that these prescribed key lengths are so overwhelmingly ultra-secure that they should only be left to military or intelligence agencies. In fact, keys of this length are widely regarded as very weak. For instance, software engineers debate whether they should use 2048 or 4096 bits, well over the prescribed 512.

It’s probably more accurate to say that the only cryptography not covered by the List is cryptography so weak that it would be foolish for anyone to use. Supplying it to someone outside Australia is again made into a crime with punishment of 10 years prison or a $425,000 fine.

Broader concerns

Concerns over the contents of the list are not limited to cryptography: problems have been raised regarding its impact on various fields, including pharmaceuticals, and science generally.

The law which introduced the crimes of supplying and publishing DSGL technology is the Defence Trade Controls Act, passed in 2012. However, the criminal offences were not due to come into effect until 16 May 2015. With a deadline looming that could criminalise vast amounts of scientific research — including research which is entirely non-military-related — the law was amended and the changes came into effect on 2 April 2015.

These new changes do little to alleviate any of the concerns raised here. They do however provide a year of breathing room: the crimes of supplying and publishing DSGL technology now will not come into effect until 2 April 2016.

Now, while the criminal offences in the Defence Trade Controls Act are unique to Australia, the listing of “weapons” in the Defence and Strategic Goods List is not. Much of the List is based on the Wassenaar Arrangement, an international arms control agreement between 41 countries.

The section of the Australian List on cryptography is copied verbatim from the Wassenaar control list on “Information Security”.

So the criticisms of cryptography in the Australian List are not unique to Australia — they are common to any of the 41 States in the Wassenaar Arrangement.

Yes, that’s right — calculators, computers and phones are covered by international arms control treaties. The madness is worldwide; your calculator is part of the global arms trade.

The Lost Art of Integration Impossibility

Integration is hard.

When we learn calculus, we learn to differentiate before we can integrate. This is despite the fact that, arguably, integration is an “easier” concept. To my mind at least, when I am given a curve in the plane, the notion of an area bounded by this curve is a very straightforward, intuitive thing; while the notion of its “gradient” or “slope” at a point is a much more subtle, or at least less intuitive idea.

But whether these ideas are natural or not, one is certainly mathematically and technically more difficult than the other. Integration is much more subtle and difficult.

These difficulties highlight the extent to which integration is less a science and more an art form. And in my experience, those difficulties are seen very rarely in high school or undergraduate mathematics, even as students take course after course about calculus and integration. So it high time we shed some light on this lost art.

Really existing differentiation

In order to see just how hard integration is, let’s first consider how we learn, and apply, the ideas of differentiation.

When we learn differentiation, we first learn a definition that involves limits and difference quotients — the old chestnut \( \lim_{h \rightarrow 0} \frac{ f(x+h) – f(x) }{ h } \). We pass through a discussion of chords and tangents — perhaps even supplemented with some physical intuition about average and instantaneous velocity. From this we have a “first principles” approach to calculus, using the formula \( f'(x) = \lim_{h \rightarrow 0} \frac{ f(x+h) – f(x) }{ h } \).

This formula, and the whole “first principles” approach, is then promptly forgotten. After we learn the “first principles” of calculus, we then learn a series of rules, techniques and tricks, such as the product rule, quotient rule and chain rule. Using these, combined with a few other “basic” derivatives, most students will never need the “first principles” again.

More specifically, once we know how to differentiate basic functions like polynomials, trig functions and exponentials,

\(\displaystyle \text{e.g.} \quad \frac{d}{dx} (x^n) = nx^{n-1}, \quad \frac{d}{dx} e^x = e^x, \quad \frac{d}{dx} \sin x = \cos x \)

and we know the rules for how to differentiate their products, quotients, and compositions

\(\displaystyle \text{e.g.} \quad \frac{d}{dx} f(x)g(x) = f'(x) g(x) + f(x) g'(x),\)
\(\displaystyle \frac{d}{dx} \frac{f(x)}{g(x)} = \frac{ f'(x) g(x) – f(x) g'(x) }{ g(x)^2 },\)
\(\displaystyle \frac{d}{dx} f(g(x)) = f'(g(x)) \; g'(x) \)

we can forget all about “first principles” and mechanically apply these formulae. With some basics down, and armed with the trident of product, quotient, and chain rules, then, we can differentiate most functions we’re likely to come up against.

It turns out, then, that in a certain sense, differentiation is “easy”. You don’t need to know the theory so much as a few basic rules and techniques. And although these rules can be a bit technically demanding, you can use them in a fairly straightforward way. In fact, their use is algorithmic. If you’ve got the technique sufficiently down, then you can mechanically differentiate most functions we’re likely to come across.

Let’s make this a little more precise. What do we mean by “most functions we’re likely to come across”? What are these functions? We mean the elementary functions. We can define these as follows. We start from some “basic” functions: polynomials, rational functions, trigonometric functions and their inverses, exponential functions and logarithms.

\(\displaystyle \text{E.g.} \quad 31 x^4 – 159 x^2 + 65, \quad \frac{ 2x^5 – 3x + 1 }{ x^3 + 8x^2 – 1 }, \quad \sin x, \quad \cos x, \quad \tan x,\)
\(\displaystyle \quad \arcsin x, \quad \arccos x, \quad \arctan x, \quad a^x, \quad \log_a x.\)

We then think of all the functions that you can get by repeatedly adding, subtracting, multiplying, dividing, taking \(n\)’th roots (i.e. square roots, cube roots, etc) and composing these functions. These functions are the elementary ones. They include functions like the following:

\(\displaystyle \log_2 \left( \frac{ \sqrt[4]{3x^4 – 1} + 2\sin e^x }{ \arcsin (x^{\tan \log_3 x} + \sqrt[7]{ \pi^x – \cos (x^2) } ) – x^x } \right).\)

(Aside: There’s actually a technicality here. Instead of saying that we can take \(n\)’th roots of a function, we should actually say that we can take any function which is a solution of a polynomial expression of existing functions. The \(n\)’th root of a function \( f(x) \), i.e. \( \sqrt[n]{f(x)} \), is the solution of the polynomial equation in \( f(x) \) given by \( f(x)^n – 1 = 0 \). That is, you can take an algebraic extension of the function field. Having done this, you can find the derivative of the new function using implicit differentiation. But we will not worry too much about these technicalities.)

Actually, the above definition is not really a very efficient one. If you start from just the constant real functions and the function \(x\), then you can build a lot just from them! By repeatedly adding and multiplying \(x\)s and constants, you can build any polynomial; and then by dividing polynomials you can build any rational function. If you throw in \( e^x \) and \( \ln x = \log_e x \), then you also have all the other exponential and logarithmic functions, because for any (positive real) constant \(a\),

\(\displaystyle a^x = e^{x \log_e a} \quad \text{and} \quad \log_a x = \frac{ \log_e x }{ \log_e a},\)

and \(\log_e a\) is a constant! If you allow yourself to also use complex number constant functions, then you can build the trig functions out of exponentials,

\(\displaystyle \sin x = \frac{ e^{ix} – e^{-ix} }{ 2i }, \quad \cos x = \frac{ e^{ix} + e^{-ix} }{ 2 },\)

and then you have \( \tan x = \frac{\sin x }{ \cos x } \). You can also build hyperbolic trigonometric functions if you wish, since \( \sinh x = \frac{ e^x – e^{-x} }{2} \), \( \cosh x = \frac{ e^x + e^{-x} }{2} \), and \( \tanh x = \frac{ \sinh x }{ \cosh x } \).

The formulas above for \(\sin x\) and \(cos x\) are relatively well known if you’ve studied complex numbers; a little less well-known are the formulas that allow us to express inverse trigonometric functions in terms of complex numbers, together with logarithms and square roots:

\(\displaystyle \arcsin x = – i \; \ln \left( ix + \sqrt{1-x^2} \right),\)
\(\displaystyle \quad \arccos x = i \; \ln \left( x – i \sqrt{1-x^2} \right),\)
\(\displaystyle \quad \arctan x = \frac{i}{2} \; \left( \ln (1-ix) – \ln (1+ix) \right).\)

(If you haven’t seen these before, try to prove them! There are also logarithmic functions for inverse hyperbolic trigonometric functions, which are probably slightly more well known as they don’t have complex numbers in them.)

Thus, we can define an elementary function as a function which can be built from the functions \( \{ \text{complex constants}, x, e^x, \ln x \} \) using a finite number of additions, subtractions, multiplications, divisions, compositions, and \(n\)’th roots (or really, solving polynomial equations in existing functions but don’t worry about this bit in parentheses).

The point is, that if you are good enough at the product, chain, and quotient rules, you can differentiate any elementary function. You don’t need any more tricks, though you might need to apply the rules very carefully and many times over! A further point is that when you find the answer, you find that the derivative of an elementary function is another elementary function.

Not so elementary, my dear Watson

When we come to integration, though, everything becomes much more difficult. I’m only going to discuss indefinite integration, i.e. antidifferentiation. Definite integration with terminals just ends up giving you a number, but indefinite integration is essentially the inverse problem to differentiation. If we’re asked to find the indefinite integral \( \int f(x) \; dx \), we’re asked to find a function \(g(x)\) whose derivative is \(f(x)\), i.e. such that \( g'(x) = f(x)\). There are many such functions: if you have one such function \(g(x)\), then you can add any constant \(c\) to it, and the resulting function \(g(x)+c\) also has derivative \(f(x)\); that is why we tend to write \(+c\) at the end of the answer to any indefinite integration question. But it will suffice for us, here, to be able to find one — for the sake of simplicity, I will not write \(+c\) in the answers to indefinite integrals. In doing so I lose 1 mark for every integral I solve, but I don’t care!

We start with some basic functions like polynomials and trigonometric functions, exponentials and logarithms, some integrals are standard.

\(\displaystyle \int x^n \; dx = \frac{1}{n+1} x^{n+1}, \quad \int \sin x \; dx = – \cos x, \quad \int \cos x \; dx = \sin x, \quad \int e^x \; dx = e^x.\)

Some are slightly less standard:

\(\displaystyle \int \tan x \; dx = – \ln \cos x, \quad \int \ln x \; dx = x \ln x – x, \quad.\)

(You might complain that the integral of \(\tan x\) should actually be \( \ln | \cos x | \). You’d be right, and I am totally sweeping that technicality under the carpet!)

Some inverse trigonometric integrals, perhaps, are less standard again:

\(\displaystyle \int \arcsin x \; dx = x \arcsin x + \sqrt{1-x^2},\)
\(\displaystyle \int \arccos x \; dx = x \arccos x – \sqrt{1-x^2},\)
\(\displaystyle \int \arctan x \; dx = x \arctan x – \frac{1}{2} \ln (1+x^2).\)

So far, so good — although perhaps not always obvious! But now, in general, what if we start to combine these functions? The problem is that if you know how to integrate \(f(x)\) and you know how to integrate \(g(x)\), it does not follow that you know how to integrate their product \(f(x) g(x) \). This is in contrast to differentiation: if you know how to differentiate \(f(x)\) and \(g(x)\), then you can use the product rule to differentiate \(f(x)g(x)\). There is no product rule for integration!

The product rule for differentiation, rather, translates into the integration by parts formula for integration:

\(\displaystyle \int f(x) g'(x) \; dx = f(x) g(x) – \int f'(x) g(x) \; dx.\)

This is not a formula for \( \int f(x) g(x) \; dx \)! A product rule for integration would say to you “if you can integrate both of my factors, you can integrate me!” But this integration by parts formula says something more along the lines of “if you can integrate one of my factors and differentiate the other, then you can express me in terms of the integral obtained by integrating and differentiating those two factors”. That is a much more subtle statement. A product rule would be a hammer you could use to crack integrals; but the integration formula is a much more subtle card up your sleeve.

Essentially, integration by parts supplies you with a trick which, if you are clever enough, and the integral is conducive to it, you can use to rewrite the integral in terms of a different integral which is hopefully easier. Hopefully. While the product rule for differentiation is an all-purpose tool of the trade — a machine used to calculate derivatives — integration by parts is a subtle trick which, when wielded with enough sophistication and skill, can simplify (rather than calculate) integrals.

Similarly, there is no chain rule for integration. The chain rule for differentiation translates into the integration by substitution formula for integration:

\(\displaystyle \int f'(g(x)) \; g'(x) \; dx = f(g(x)). \)

A chain rule for integration would say to you “if I am a composition of two functions, and you can integrate both of them, then you can integrate me”. But integration by substitution says, instead, “if I am a composition of two functions, multiplied by the derivative of the inner function, then you can integrate me”. In a certain sense it’s easier than integration by parts, because it calculates the integral and gives you an answer, rather than merely reducing to a different (hopefully simpler) integral. But still, it remains an art form: it requires the skill to see how to regard the integrand as an expression of the form \( f'(g(x)) \; g'(x) \). Finally, there is no quotient rule for integration either.

So, while differentiation is a skill which can be learned and applied, integration is an art form for which we learn tricks and strategies, and develop our skills and intuition in applying them. Now, actually there are tables of standard integrals, far far beyond the small examples above. There are theorems about how functions of certain types can be integrated. There are algorithms which can be used to integrate certain, often very complicated, families of functions.

But the question remains: how far can we go? If we see an integral which we can’t immediately solve, do we just need to think a little harder, and apply something from our bag of tricks in a clever new way? Do we just need more skill, or is the integral impossible? How would we tell the difference between a “hard” and an “impossible” integral — and what does that even mean?

In a certain sense, no integrals are “impossible”. An integral of a continuous function always exists, in a certain sense. If you’ve got a continuous function \(f : \mathbb{R} \rightarrow \mathbb{R}\), then its integral is certainly defined as a function, using the definition with Riemann sums — this is a theorem. Even if \(f\) is not continuous, it’s possible that the Riemann sum approach can give a well-defined function as the integral. For more exotic functions \(f\), there is the more advanced method of Lebesgue integration.

But this is not what we have in mind when we say an “integral is impossible”. What we really mean is that we can’t write a nice formula for the integral. This would happen if the result were not an elementary function.

As we discussed above, if you take an elementary function and differentiate it, you can always calculate the derivative with a sufficiently careful application of product/chain/quotient rules, and the result is another elementary function.

So, we might ask: given an elementary function, even though there might not be any straightforward way to calculate its integral, is the result always another elementary function?

Indomitable impossible integrals

It turns out, the answer is no. There are elementary functions such that, when you take their integral, it is not an elementary function. When you try to integrate such a function, although the integral exists, you can’t write a nice formula for it. And it’s not because you’re not skillful enough. It’s not because you’re not smart enough. The reason you can’t write a nice formula for the integral is because no such formula exists: the integral is not an elementary function.

What is an example of such a function? The simplest example is one that high school students come up against all the time: the Gaussian function

\(\displaystyle e^{-x^2}.\)

It’s clearly an elementary function, constructed by composition of a polynomial \(-x^2\) and the exponential function. But its integral is not elementary.

You might recall that the graph of \(y = e^{-x^2} \) is a bell curve. Suitably dilated (normalised), it is the probability density function for a normal distribution. When you calculate probabilities involving normally distributed random variables, you often integrate this function.

You may recall painful time spent in high school looking up a table to find out probabilities for the normal distribution. That table is essentially a table of (definite) integrals for the function \(e^{-x^2}\) (or a closely related function). And the reason that it’s a table you have to look up, rather than a formula, is because there is no formula for the integral \( \int e^{-x^2} \; dx \). You need a table because the integral of the elementary function \(e^{-x^2} \) is not elementary.

There’s no formula for normal distribution probabilities because integration is an art form, rather than algorithmic. And so we are sometimes reduced to the quite non-artistic process of looking up a table to find the integral.

Now, when I say that \( \int e^{-x^2} \; dx \) is not elementary, I mean that it’s known as a theorem. That is, it has been proved mathematically that \( \int e^{-x^2} \; dx \) is not elementary, and so doesn’t have a nice formula. But what could this mean? How could you prove that an integral doesn’t have a nice formula, isn’t an elementary function, can’t be written in a nice way? The proof is a bit complicated, too complicated to recall in complete detail here. But there are some nice ideas involved, and it’s worth recounting some of them here.

Proving the impossible

The fact that \( \int e^{-x^2} \; dx \) is not elementary was proved by the French mathematician Joseph Liouville in the mid-19th century. In fact, he proved quite a deal more. Suppose you have an elementary function \( f(x) \), and you are trying to find its integral \( g(x) = \int f(x) \; dx \). Now as the integrand \(f(x)\) is continuous, the integral \(g(x)\) certainly exists as a continuous function; the question is whether \(g(x)\) is elementary or not, i.e. whether there is a formula for \(g(x)\) involving only complex numbers, powers of \(x\), rational functions, \(\exp\) and \(\log\), and \(n\)’th roots (and their generalisations).

Liouville’s theorem, amazingly, tells you that if the function \(g(x)\) you’re looking for is elementary, then it must have a very specific form. Very roughly, Liouville says, \(g(x)\) can have more logarithms than \(f(x)\), but no more exponentials. You can see the germ of this idea in some of the integrals above:

\(\displaystyle \int \tan x \; dx = – \ln \cos x, \quad \int \arctan x \; dx = x \arctan x – \frac{1}{2} \ln (1+x^2).\)

In these integrals, a new logarithm appears, that did not appear in the integrand. Never does a new exponential appear. If an exponential appears in the integral, then it appeared in the integrand, as in examples like

\(\displaystyle \int e^x \; dx = e^x. \)

To state Liouville’s theorem more precisely, we need the idea of a field of functions. For our purposes, we can think of a field of functions as a collection of functions \(f(x)\) which is closed under addition, subtraction, multiplication, and division. The polynomials in \(x\) do not form a field of functions, because when you divide two polynomials you do not always get a polynomial! However, the rational functions in \(x\) do form a field of functions. A rational function in \(x\) is the quotient of two polynomials (with complex coefficients) in \(x\), i.e. a function like

\(\displaystyle \frac{ 3x^2 – 7 }{ x^{10} – x^9 + x^3 + 1} \quad \text{ or } \quad \frac{ 4x+1}{2x-3} \quad \text{or} \quad x^2 – 3x + \pi \quad \text{or} \quad 3.\)

The first example is the quotient of a quadratic by a 10’th degree polynomial; the second example is the quotient of two linear polynomials. The third example illustrates the notion that any polynomial is also a rational function, because you can think of it as itself divided by \(1\), and \(1\) is a polynomial: \( x^2 – 3x + \pi = \frac{ x^2 – 3x + \pi }{ 1 } \). The final example illustrates the notion that any constant is also a rational function.

The field of rational functions (with complex coefficients) in \(x\) is denoted \( \mathbb{C}(x) \). You can make bigger fields of rational functions by including new elements! For instance, you could throw in the exponential function \( e^x \), and then you can obtain the larger field of functions \( \mathbb{C}(x, e^x) \). The functions in this field are those made up of adding, subtracting, multiplying, and dividing powers of \(x\) and the function \( e^x\). So this includes functions like

\(\displaystyle \frac{ x^2 + x e^x – e^x }{ x + 1 } \quad \text{ or } \quad (e^x) \cdot (e^x) = e^{2x} \quad \text{ or } \quad x^7 e^{4x} – 3 x^2 e^x + \pi.\)

Note however that a function like \( e^{e^x} \) does not lie in \( \mathbb{C} (x, e^x) \). This function field is made up out of adding, subtracting, multiplying and dividing \(x\) and \( e^x \), but not by composing these functions.

We can see, then, that this second function field is bigger than the first one: \( \mathbb{C}(x) \subset \mathbb{C}(x, e^x) \). In technical language, we say that \( \mathbb{C}(x) \subset \mathbb{C}(x, e^x) \) is a field extension. Moreover, both these fields have the nice property that they are closed under differentiation. That is, it you take a rational function and differentiate it, you get another rational function. And if you take a function in \( \mathbb{C}(x, e^x) \), involving \(x\)’s and \(e^x\)’s, and differentiate it, you get another function in \( \mathbb{C}(x, e^x) \). In technical language, we say that \( \mathbb{C}(x) \) and \( \mathbb{C}(x, e^x) \) are differential fields of functions.

A differential field obtained in this way, by starting from rational functions and then throwing in an exponential, is an example of an field of elementary functions. In general, a field of elementary functions is obtained from the field of rational functions \( \mathbb{C}(x) \) by successively throwing in extra functions, some finite number of times. Each time you add a function is must be either

  • an exponential of a function already in the field, or
  • a logarithm of a function already in the field, or
  • an \(n\)’th root of a function already in the field (or more generally the root of a polynomial equation with coefficients in the field but as I keep saying don’t worry too much about this!).

Note that, by definition, any function in a field of elementary functions is made up by adding, subtracting, multiplying, and dividing \(x\)’s, and exponentials, and logarithms, and \(n\)’th roots (or generalisations thereof). That is, a function in an field of elementary functions is an elementary function! So our definitions of “elementary function” and “field of elementary functions” agree — it would be bad if we used the word “elementary” to mean two different things!

We can now state Liouville’s theorem precisely.

Liouville’s theorem: Let \(K\) be an field of elementary functions, and let \(f(x)\) be a function in \(K\). (Hence \(f(x)\) is an elementary function.) If the integral \( \int f(x) \; dx \) is elementary, then

\(\displaystyle \int f(x) \; dx = h(x) + \sum_{j=1}^n c_j \log g_j (x),\)

where \(n\) is a non-negative integer, each of \(c_1, c_2, \ldots, c_n\) is a constant, and the functions \(h(x), g_1(x), g_2(x), \ldots, g_n(x) \) all lie in \(K\).

That is, Liouville’s theorem says that the integral of an elementary function \(f(x)\) must be a sum of a function \(h(x)\) that lies in the same field as \(f\), and a constant linear combination of some logarithms of functions \( g_j(x)\) in the same field as \(f\). The fact that \(h(x) \) and each \(g_j(x)\) lies in the same field \(K\) as \(f(x)\) means that they cannot be much more complicated than \(f(x)\): they must be made up by adding, subtracting, multiplying and dividing the same bunch of functions that you can use to define \(f(x)\)

So Lioville’s theorem says, in a precise way, that when you integrate an elementary function \(f(x)\), if the result is elementary, then it can’t be much more complicated than \(f(x)\), and the only way in which it can be more complicated is that it can have some logarithms in it. This is what we meant when we gave the very rough description “Liouville says \(g(x)\) can have more logarithms than \(f(x)\), but no more exponentials“.

Let’s now return to our specific example of the Gaussian function \(f(x) = e^{-x^2}\). What does Liouville’s theorem mean for this function? Well, this function lies in the field of elementary functions \(K\) where we start from rational functions and then throw in, not \(e^x\), but \(e^{-x^2}\). That is, we can take \(K = \mathbb{C}(x, e^{-x^2})\).
The theorem says that if the integral

\(\displaystyle \int e^{-x^2} \; dx\)

is elementary, then it is given by

\(\displaystyle \int e^{-x^2} \; dx = h(x) + \sum_{j=1}^n c_j \log g_j (x),\)

where \(n\) is a non-negative integer, each of \( c_1, c_2, \ldots, c_n\) is a constant, and the functions \( h(x), g_1(x), g_2(x), \ldots, g_n(x) \) all lie in \(\mathbb{C}(x, e^{-x^2})\). That is, \(h(x), g_1(x), \ldots, g_n(x)\) are “no more complicated” than \(e^{-x^2}\); they are all made by adding, subtracting, multiplying and dividing \(x\)’s and \(e^{-x^2}\)’s.

If we differentiate the above equation, we obtain

\(\displaystyle e^{-x^2} = h'(x) + \sum_{j=1}^n c_j \frac{ g’_j (x) }{ g_j (x) },\)

On the left hand side is the function we started with, \(e^{-x^2}\). On the right hand side is an expression involving several functions. However, all the functions \(g_j(x)\) and \(h(x)\) lie in \(K\); they are “no more complicated” than \(e^{-x^2}\). Now as \(K\) is a differential field, their derivatives \(g’_j(x)\) and \(h'(x)\) also lie in \(K\); they are also “no more complicated”. So in fact the right hand side is an expression involving functions no more complicated than \(e^{-x^2}\). They are all just rational functions, with \(e^{-x^2}\)’s thrown in. And if you think about it, thinking about what you will get for each \(g’_j(x) / g_j (x)\), you might find it hard to avoid having a big denominator. You likely won’t be able to cancel the fraction. So you might find, then, that none of the \(g_j(x)\) can make this equality work, and all \(g_j(x)\) have to be zero; or in other words, \(e^{-x^2} = h'(x)\). But now that \(h(x)\) is, like everything else here, made up by adding, subtracting, multiplying and dividing \(x\)’s and \(e^{-x^2}\)’s. You might find, when you differentiate such a function, that it’s very hard to get a lone \(e^{-x^2}\). Every time you differentiate an \(e^{-x^2}\) you get a \(-2xe^{-x^2}\), which has a pesky extra factor of \(-2x\). And even if it appears together with other terms, as something like \(x^3 e^{-x^2}\), when you differentiate it you get something like \(-2x^4 e^{-x^2} + 3x^2 e^{-x^2}\), which still has no isolated \(e^{-x^2}\) term. And so, in conclusion, you might find it very difficult to find any functions that make the right hand side equal to \(e^{-x^2}\).

Of course, this is not a proof at all; it’s a mere plausibility argument. To prove the integral is not elementary does take a bit more work. But it has been done, and can be found in standard references.

Hopefully, though, this should at least give you some idea why it might be true, and how you might prove, that an integral is “impossible”, and can’t be written with any nice formula.

Mathematics is an amazing place.

References

Brian Conrad, Impossibility theorems for elementary integration, [[http://www2.maths.ox.ac.uk/cmi/library/academy/LectureNotes05/Conrad.pdf]].

Keith O. Geddes, Stephen R. Czapor, George Labahn, Algorithms for Computer Algebra, Kluwer (1992).

Andy R. Magid, Lectures on Differential Galois Theory, AMS (1994).

(Update 2/3/15: Typo fixed.)

Is the Victoria Police Act a step forward?

(This article also appeared on the website of the Police Accountability Project.)
Law Institute Journal considers the new Victoria Police Act — a step forward?
A feature article in the most recent Law Institute Journal, In Search of Certainty, examines the issues surrounding the new Victoria Police Act and its implications for police accountability in Victoria.
The article, by Robinson Gill lawyers Jeremy King and Merys Williams, traces the history of the legislation and its likely effects in practice.
Until July of 2014, the principal legislation regarding police in Victoria was the Police Regulation Act of 1958. In July 2014, this Act was replaced with the Victoria Police Act as the new legislation came into force.
Both acts are problematic from the point of view of holding police accountable for misconduct through civil litigation, and compensating the victims of assaults by police and other wrongdoing.
It is not yet clear how much of an improvement the new Act will be. King and Williams argue that state policy will determine precisely how much. This post summarises their arguments; see their original article for full details.
Making the cops pay: The law governing civil liability for police misconduct
The specific problem is: if you suffer an assault or other wrongdoing at the hands of police, who can you sue? Who is liable? Is it the individual officers? Or is it the State, on whose behalf they act?
This sounds like a technicality — but it can mean the difference between being fully compensated for injuries suffered for wrongdoing, or receiving nothing.
If it is only the individual officers who are liable, those officers may not have the means to pay compensation. They may be bankrupted by the costs, or rendered impecunious.
It is in the interest of victims who have suffered police injustices, then, that the State be liable for police torts.
The position at common law, however, was very different. Known as the Independent Discretion rule, from the 1906 High Court case of Enever v R, it held that when an officer exercises their independent discretion, they are acting on behalf of themselves alone, not the State. If they committed a tort while exercising their discretion — which is what they do most of the time — they were liable and the State was not.
This position was altered by s123 of the old Police Regulation Act, which held that the State would be liable for “anything necessarily or reasonably done or omitted to be done in good faith and in the course of his or her duty as a member”.
This convoluted wording came to mean that when an officer was not acting “necessarily”, “reasonably” or “in good faith”, the State would again not be liable. Most police torts — assault, false imprisonment, malicious prosecution — are intentional. The State avoided liability again.
Indeed, under the old Police Regulation Act, the State avoided liability in precisely the worst cases of police misconduct. The worse the injustice suffered, the less likely the State was to be liable, the less likely the victim would be compensated.
Horvath’s case
The problems with the old Police Regulation Act reached breaking point with the case of Corinna Horvath.
In 1996, Horvath, along with her partner and several friends, were viciously assaulted by police during an unlawful raid on her home. Police violence left her unconscious, with a broken nose — then she was arrested. She suffered grave injuries. She successfully sued for damages.
But the State sought immunity under s123. Because the police were not acting “reasonably” or “in good faith” — indeed, far from it — the State was held not liable. Only the officers were liable. And the officers could not pay. Horvath won her day in court — or rather, won years of hearings and appeals in exhaustive court processes — yet received no compensation.
Horvath took her case to the UN. The Human Rights Committee found that s123 of the old Police Regulation Act was incompatible with the International Covenant on Civil and Political Rights. Her human rights had been breached, but the State had no mechanism to compensate her — only a mechanism to provide her with a Pyrrhic victory, an empty judgment in her favour.
It was only in September 2014, almost 20 years after the event, that Horvath finally received an apology and compensation from Victoria police.
The new Victoria Police Act
In something of an attempt to redress the longrunning injustice of Horvath’s case, s74(1) of the new Police Act specifies that the State is liable for “police torts”.
But the definition of a “police tort” again leads to difficulties. Section s74(2) provides an exception: the State is not liable when “the conduct giving rise to the police tort was serious or wilful misconduct by the police officer“. Again, it seems, victims will not receive compensation from the State for the worst police torts. Many police assaults are serious or wilful misconduct.
However, there is then s79(2), which requires that, in such circumstances of “serious or wilful misconduct”, the State must pay the victim “an amount” — but only when the victim “is unlikely to recover the amount from the officer” who committed the tort, and “the claimant has exhausted all other avenues to recover the amount”.
Together, this new legal regime leaves a great deal of uncertainty. What does it mean that you are “unlikely” to be able to recover from a police officer, and how do you prove it in court? What, precisely, are the “other avenues” that a victim must exhaust first? Must they first put themselves through the largely symbolic process through the Victims of Crime Compensation Assistance Tribunal (VOCAT)? And while the State is required to pay “an amount”, how much is this “amount”?
King and Williams argue that the legislation is unhelpful in answering these questions. But they see the new Police Act as a positive step forward, and conclude that

whether the [new] Police Act will overcome the shortfalls of the [old] Police Regulation Act will largely depend on the policy position adopted by the state of Victoria. The Police Act gives extremely broad discretion to the state regarding the use of the serious and wilful misconduct defence. If the state elects to use this defence in most civil litigation torts cases then the intention of the Police Act may well be undermined. Additionally, the state’s policy on how it will interpret s79(2) regarding ex-gratia payments may be key to the success or failure of the new legislation. If a technical and legalistic approach is adopted by the state then plaintiffs may find themselves no better off than Ms Horvath.

If the State insists on asserting its full legal rights in court, then, the new legislation may not be much of an improvement.
Several concerned groups, including the Flemington & Kensington Community Legal Centre, the Human Rights Law Centre, Remedy Australia, Liberty Victoria, Australian Lawyers for Human Rights, the Law Institute of Victoria, the Uniting Church, Australian Lawyers Alliance, Federation of Community Legal Centres, Aboriginal Legal Service, Victorian Council of Social Service, Springvale Monash Legal Service, and Youthlaw, sent an joint letter to the Victorian Parliament in July 2014 urging a review of Victorian police legislation to ensure conformity with our human rights obligations outlined in the Horvath decsion.
The reply from then Minister for Police and Emergency Services, Kim Wells, asserts that the new sections 72-81 of the Victoria Police Act will guard against a repeat of the circumstances faced my Ms Horvath. He states that the changes “provide an effective remedy for all torts committed by police, including assault, battery, false imprisonment and maliscious prosecution.
We await the formal response to the Horvath decision from the Australian Government.