A computer-generated proof that nobody understands

Very early on when I was reading about this formal proof verification game, I learnt about the Robbins Conjecture. Let me start this post with an overview of what this conjecture is, and how it was proved by a computer, and how the proof is easy for humans to understand. Then let me tell you about Bruck Loops, where the situation is quite different, and finally let me tell you about fancier mathematical objects and why things aren’t so easy in that case.

Robbins algebras

There is something in maths called a Boolean Algebra — it’s just a definition, like a group or a topological space. Feel free to look at the formal definition on the Wikipedia page for Boolean algebras. In the 1930s Herbert Robbins defined some other mathematical structure now called a Robbins Algebra, and conjectured that every Robbins Algebra was a Boolean Algebra. Proving this conjecture is like solving a big logic puzzle; we have some set with some structure and a load of axioms (a Robbins algebra), and we want to prove some other statements about this structure (i.e., the axioms for a Boolean algebra).

The conjecture remained open for around 60 years, possibly because it was tricky and possibly because there were not too many people working on it. Then in 1996 William McCune proved the conjecture using “automated theorem provers” called EQP and Otter. To give a rather brutal description of what an automated theorem prover is — it is something which takes as input a question such as the Robbins Conjecture, and then just throws all the axioms around generating lemma after lemma about Robbins algebras with the hope of ultimately managing to prove all the statements which define Boolean algebras. As you can imagine, this “brute force and ignorance” approach is not particularly appealing to the purist, but, let’s face it, it used to be the way that computers played chess, and anyone who has had their king and rook forked by a computer’s knight a fraction of a second after they have made a careless move knows that this approach can sometimes pay off.

Now one interesting thing about McCune’s proof was that actually, at the end of the day, it was pretty short. Within a year Bernd Dahn had got yet another system, ILF, to go through the Otter proof and simplify it (spotting common themes which were used more than once in the proof and pulling them off as useful lemmas); Dahn ultimately wrote a “normal” seven page maths paper, published in the Journal of Algebra in 1998, containing a human-readable account of the proof. The proof had now been completely “de-computerised”.

We learn from this story the unsurprising fact that computers are good at logic puzzles.

Bruck loops

I didn’t tell you what a Robbins algebra was, but I will attempt to tell you what a Bruck loop is. If you really don’t care then just skip down to the statement of the theorem below.

A loop is “a group without the associativity axiom”. More precisely a loop is a set Q equipped with a binary operation \cdot : Q \times Q \to Q and an identity element 1\in Q satisfying 1 \cdot x = x \cdot 1 = x for all x\in Q, plus the following “inverse axiom”: for all q\in Q, left multiplication by q and right multiplication by q are both bijections from Q to Q. In particular for any q\in Q the equations qr=1 and rq=1 have unique solutions for r, and one could call these solutions the left and right inverses of q. These two inverses might not coincide though.

Groups of course give examples of loops, but there are non-associative examples too. Most definitions in group theory have some sort of analogue for loop theory, although you sometimes have to think about things the right way. For example one can consider the group of permutations Q\to Q generated by left and right multiplications by elements of Q, and the inner mapping group Inn(Q) of a loop Q is the subgroup consisting of elements sending 1 to 1; if Q is a group then this is readily checked to be the inner automorphisms of Q.

Sometimes the lack of associativity makes these analogues really painful though. For example the centre of a loop Q is the subloop Z(Q) of Q consisting of the elements z\in Q such that z\cdot q=q\cdot z for all q\in Q and z\cdot(x\cdot y)=(z\cdot x)\cdot y for all x,y\in Q and two more equations like this with z in the middle and on the right. One checks that the centre of a loop is a normal subloop and one can form a quotient loop Q/Z(Q).

Just like groups, we say a loop Q has nilpotency class at most 1 if Q=Z(Q), and Q has nilpotency class at most 2 if Q/Z(Q) has nilpotency class at most 1.

For groups, we have Inn(G)\cong G/Z(G) and in particular if Inn(G) is abelian then G has nilpotency class at most 2. These results use associativity though, and are not true in general for loops. However they are true for Bruck Loops:

Theorem (a computer). If Q is a Bruck loop and Inn(Q) is abelian, then Q has nilpotency class at most 2.

A Bruck loop is a loop satisfying two extra axioms: firstly x\cdot (y\cdot (x\cdot z)) = (x \cdot (y \cdot x)) \cdot z (which implies that left inverses equal right inverses), and secondly that (xy)^{-1}=x^{-1}y^{-1} (another “commutativity” condition).

The humans involved in the proof were J. D. Phillips and David Stanovsk√Ĺ, who wrote a paper published in 2012 in Communications in Algebra. The humans reduced the question to proving that a certain equation was always satisfied for Bruck loops with abelian inner mapping groups, and then they threw a bunch of automated theorem provers at it. The prover Waldmeister managed to come up with a proof. Here it is — all 30000+ lines of it. This helpful page on Stanovsky’s website offers other formats of the proof, for example a 1068 page pdf file containing a complete “human-readable” proof. What human would ever read this proof though?

I had no idea that computers were doing that sort of thing nowadays. I learnt about this work from Michael Kinyon at AITP 2019.

Shimura varieties

In my mind, this work raises an interesting question. Note that the work also raises a lot of boring questions. Of course “boring” a very subjective term. But let’s try and put this work on Bruck loops into some sort of context. I work in a mathematics department full of people thinking about mirror symmetry, perfectoid spaces, canonical rings of algebraic varieties in characteristic p, etale cohomology of Shimura varieties defined over number fields, and the Langlands philosophy, amongst other things. Nobody in my department cares about Bruck loops. People care about objects which it takes an entire course to define, not a paragraph. The questions raised by this work which people in my department might find “boring” are: here are other classes of loops; can one prove analogous theorems about these classes? Or : here is another elementary object which takes a paragraph to define but which is not taught to the undergraduates at Imperial College London. Can one prove the following conjecture about these objects? The kind of mathematicians I know are, for the most part, not remotely interested in such questions. This is all to do with subtleties such as fashions in mathematics, and which areas are regarded as important (that is, worth funding).

So what are the mathematicians I know interested in? Well, let’s take the research staff in my department at Imperial College. They are working on results about about objects which in some cases take hundreds of axioms to define, or are even more complicated: sometimes even the definitions of the objects we study can only be formalised once one has proved hard theorems. For example the definition of the canonical model of a Shimura variety over a number field can only be made once one has proved most of the theorems in Deligne’s paper on canonical models, which in turn rely on the theory of CM abelian varieties, which in turn rely on the theorems of global class field theory. That’s the kind of definitions which mathematicians in my department get excited about — not Bruck Loops. I once went to an entire 24 lecture course by John Coates which assumed local class field theory and deduced the theorems of global class field theory. I have read enough of the book by Shimura and Taniyama on CM abelian varieties to know what’s going on there. I have been to a study group on Deligne’s paper on canonical models. So after perhaps 100 hours of study absorbing the prerequisites, I was ready for the definition of a Shimura variety over a number field. And then there is still the small matter of the definition of etale cohomology.

So why are computers proving theorems about Bruck loops but not proving theorems about the cohomology of Shimura varieties?

Here is a conjectural answer. Bruck loops are easy, so it’s easy to prove theorems about them. Shimura varieties are hard, so it’s never going to work.

Yeah, but hang on a minute. If 20 years ago we had raised the possibility that a computer could come up with a 1000 page proof of a statement which humans had formulated, however “easy” the objects in question were, I think that it would not have been hard to find people who would have been very skeptical. Think about it. The definition of a Bruck Loop in the 1000 page pdf is 19 axioms. Now make a naive guess about how long it would take to create a 30,000 line proof of a statement about Bruck Loops. The number 19^{30000} does not fit into our universe in any meaningful way. The computer scientists must have done something clever here. In particular I think that although many mathematicians would instinctively rule out the possibility of computers proving hard theorems about complicated objects because of issues of scale, this work on Bruck loops throws some sort of spanner into those works.

Here is another answer, which is correct for trivial reasons. One reason why computers are not proving theorems about the etale cohomology of Shimura varieties over number fields is that the human race have not yet taken the time to tell a proof verification system what the phrase “etale cohomology of a Shimura variety over a number field” means. Why is this? Well, I am currently finding it very hard to think of people who know the definition of the canonical model of a Shimura variety and also know how to use proof verification systems. I also think that it is much easier to train mathematicians to use proof verification systems than it is to train computer scientists to read papers by Deligne, and this is one of the reasons why the Xena project exists.

But is this the only reason? Well, unfortunately, I suspect that it is not. If you were to ask a computer scientist what they would need in order to start proving things about the cohomology of Shimura varieties defined over number fields, I suspect that they would ask for something like

  • the definitions;
  • sample proofs of hundreds (or thousands?) of theorems to train their AI;
  • some conjectures, of approximately the same level of difficulty as the theorems.

The reason that, in contrast to the Bruck loop work, they will need some proofs, is because the natural framework to define objects like Shimura varieties is within some higher order logical structure; even for the definition of a topological space one has to quantify over subsets rather than just elements. On the other hand, after AITP 2019, Josef Urban showed me some work where the E theorem prover had managed to prove basic theorems about topological spaces given enough “training data” theorems.

If instead of Shimura varieties we think about getting computers to prove theorems about perfectoid spaces, then Commelin, Massot and I have achieved the first bullet point above. As you can see, we still have a vast amount of work to do before we can catch up with Peter Scholze. Another milestone in this game would be to prove the tilting correspondence, because proving that would involve proving hundreds of other theorems along the way (which could also be used to train). However before that milestone, we still have the milestone of stating the tilting correspondence. Even stating it will involve having to prove some theorems. There is still a long way to go.

About xenaproject

The Xena Project aims to get mathematics undergraduates at Imperial College (and beyond) trained in the art of formalising mathematics on a computer.
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