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Asgar Jamneshan, Or Shalom, and myself have just uploaded to the arXiv our preprints “A Host–Kra -system of order 5 that is not Abramov of order 5, and non-measurability of the inverse theorem for the norm” and “The structure of totally disconnected Host–Kra–Ziegler factors, and the inverse theorem for the Gowers uniformity norms on finite abelian groups of bounded torsion“. These two papers are both concerned with advancing the inverse theory for the Gowers norms and Gowers-Host-Kra seminorms; the first paper provides a counterexample in this theory (in particular disproving a conjecture of Bergelson, Ziegler and myself), and the second paper gives new positive results in the case when the underlying group is bounded torsion, or the ergodic system is totally disconnected. I discuss the two papers more below the fold.
Rachel Greenfeld and I have just uploaded to the arXiv our paper “A counterexample to the periodic tiling conjecture“. This is the full version of the result I announced on this blog a few months ago, in which we disprove the periodic tiling conjecture of Grünbaum-Shephard and Lagarias-Wang. The paper took a little longer than expected to finish, due to a technical issue that we did not realize at the time of the announcement that required a workaround.
In more detail: the original strategy, as described in the announcement, was to build a “tiling language” that was capable of encoding a certain “-adic Sudoku puzzle”, and then show that the latter type of puzzle had only non-periodic solutions if was a sufficiently large prime. As it turns out, the second half of this strategy worked out, but there was an issue in the first part: our tiling language was able (using -group-valued functions) to encode arbitrary boolean relationships between boolean functions, and was also able (using -valued functions) to encode “clock” functions such as that were part of our -adic Sudoku puzzle, but we were not able to make these two types of functions “talk” to each other in the way that was needed to encode the -adic Sudoku puzzle (the basic problem being that if is a finite abelian -group then there are no non-trivial subgroups of that are not contained in or trivial in the direction). As a consequence, we had to replace our “-adic Sudoku puzzle” by a “-adic Sudoku puzzle” which basically amounts to replacing the prime by a sufficiently large power of (we believe will suffice). This solved the encoding issue, but the analysis of the -adic Sudoku puzzles was a little bit more complicated than the -adic case, for the following reason. The following is a nice exercise in analysis:
Theorem 1 (Linearity in three directions implies full linearity) Let be a smooth function which is affine-linear on every horizontal line, diagonal (line of slope ), and anti-diagonal (line of slope ). In other words, for any , the functions , , and are each affine functions on . Then is an affine function on .
Indeed, the property of being affine in three directions shows that the quadratic form associated to the Hessian at any given point vanishes at , , and , and thus must vanish everywhere. In fact the smoothness hypothesis is not necessary; we leave this as an exercise to the interested reader. The same statement turns out to be true if one replaces with the cyclic group as long as is odd; this is the key for us to showing that our -adic Sudoku puzzles have an (approximate) two-dimensional affine structure, which on further analysis can then be used to show that it is in fact non-periodic. However, it turns out that the corresponding claim for cyclic groups can fail when is a sufficiently large power of ! In fact the general form of functions that are affine on every horizontal line, diagonal, and anti-diagonal takes the form
for some integer coefficients . This additional “pseudo-affine” term causes some additional technical complications but ultimately turns out to be manageable.During the writing process we also discovered that the encoding part of the proof becomes more modular and conceptual once one introduces two new definitions, that of an “expressible property” and a “weakly expressible property”. These concepts are somewhat analogous to that of sentences and sentences in the arithmetic hierarchy, or to algebraic sets and semi-algebraic sets in real algebraic geometry. Roughly speaking, an expressible property is a property of a tuple of functions , from an abelian group to finite abelian groups , such that the property can be expressed in terms of one or more tiling equations on the graph
For instance, the property that two functions differ by a constant can be expressed in terms of the tiling equation (the vertical line test), as well as where is the diagonal subgroup of . A weakly expressible property is an existential quantification of some expressible property , so that a tuple of functions obeys the property if and only if there exists an extension of this tuple by some additional functions that obey the property . It turns out that weakly expressible properties are closed under a number of useful operations, and allow us to easily construct quite complicated weakly expressible properties out of a “library” of simple weakly expressible properties, much as a complex computer program can be constructed out of simple library routines. In particular we will be able to “program” our Sudoku puzzle as a weakly expressible property.
Rachel Greenfeld and I have just uploaded to the arXiv our announcement “A counterexample to the periodic tiling conjecture“. This is an announcement of a longer paper that we are currently in the process of writing up (and hope to release in a few weeks), in which we disprove the periodic tiling conjecture of Grünbaum-Shephard and Lagarias-Wang. This conjecture can be formulated in both discrete and continuous settings:
Conjecture 1 (Discrete periodic tiling conjecture) Suppose that is a finite set that tiles by translations (i.e., can be partitioned into translates of ). Then also tiles by translations periodically (i.e., the set of translations can be taken to be a periodic subset of ).
Conjecture 2 (Continuous periodic tiling conjecture) Suppose that is a bounded measurable set of positive measure that tiles by translations up to null sets. Then also tiles by translations periodically up to null sets.
The discrete periodic tiling conjecture can be easily established for by the pigeonhole principle (as first observed by Newman), and was proven for by Bhattacharya (with a new proof given by Greenfeld and myself). The continuous periodic tiling conjecture was established for by Lagarias and Wang. By an old observation of Hao Wang, one of the consequences of the (discrete) periodic tiling conjecture is that the problem of determining whether a given finite set tiles by translations is (algorithmically and logically) decidable.
On the other hand, once one allows tilings by more than one tile, it is well known that aperiodic tile sets exist, even in dimension two – finite collections of discrete or continuous tiles that can tile the given domain by translations, but not periodically. Perhaps the most famous examples of such aperiodic tilings are the Penrose tilings, but there are many other constructions; for instance, there is a construction of Ammann, Grümbaum, and Shephard of eight tiles in which tile aperiodically. Recently, Rachel and I constructed a pair of tiles in that tiled a periodic subset of aperiodically (in fact we could even make the tiling question logically undecidable in ZFC).
Our main result is then
Theorem 3 Both the discrete and continuous periodic tiling conjectures fail for sufficiently large . Also, there is a finite abelian group such that the analogue of the discrete periodic tiling conjecture for is false.
This suggests that the techniques used to prove the discrete periodic conjecture in are already close to the limit of their applicability, as they cannot handle even virtually two-dimensional discrete abelian groups such as . The main difficulty is in constructing the counterexample in the setting.
The approach starts by adapting some of the methods of a previous paper of Rachel and myself. The first step is make the problem easier to solve by disproving a “multiple periodic tiling conjecture” instead of the traditional periodic tiling conjecture. At present, Theorem 3 asserts the existence of a “tiling equation” (where one should think of and as given, and the tiling set is known), which admits solutions, all of which are non-periodic. It turns out that it is enough to instead assert the existence of a system
of tiling equations, which admits solutions, all of which are non-periodic. This is basically because one can “stack” together a system of tiling equations into an essentially equivalent single tiling equation in a slightly larger group. The advantage of this reformulation is that it creates a “tiling language”, in which each sentence in the language expresses a different type of constraint on the unknown set . The strategy then is to locate a non-periodic set which one can try to “describe” by sentences in the tiling language that are obeyed by this non-periodic set, and which are “structured” enough that one can capture their non-periodic nature through enough of these sentences.It is convenient to replace sets by functions, so that this tiling language can be translated to a more familiar language, namely the language of (certain types of) functional equations. The key point here is that the tiling equation
for some abelian groups is precisely asserting that is a graph of some function (this sometimes referred to as the “vertical line test” in U.S. undergraduate math classes). Using this translation, it is possible to encode a variety of functional equations relating one or more functions taking values in some finite group (such as a cyclic group).The non-periodic behaviour that we ended up trying to capture was that of a certain “-adically structured function” associated to some fixed and sufficiently large prime (in fact for our arguments any prime larger than , e.g., , would suffice), defined by the formula
for and , where is the number of times divides . In other words, is the last non-zero digit in the base expansion of (with the convention that the last non-zero digit of is ). This function is not periodic, and yet obeys a lot of functional equations; for instance, one has for all , and also for (and in fact these two equations, together with the condition , completely determine ). Here is what the function looks like (for ):
It turns out that we cannot describe this one-dimensional non-periodic function directly via tiling equations. However, we can describe two-dimensional non-periodic functions such as for some coefficients via a suitable system of tiling equations. A typical such function looks like this:
A feature of this function is that when one restricts to a row or diagonal of such a function, the resulting one-dimensional function exhibits “-adic structure” in the sense that it behaves like a rescaled version of ; see the announcement for a precise version of this statement. It turns out that the converse is essentially true: after excluding some degenerate solutions in which the function is constant along one or more of the columns, all two-dimensional functions which exhibit -adic structure along (non-vertical) lines must behave like one of the functions mentioned earlier, and in particular is non-periodic. The proof of this result is strongly reminiscent of the type of reasoning needed to solve a Sudoku puzzle, and so we have adopted some Sudoku-like terminology in our arguments to provide intuition and visuals. One key step is to perform a shear transformation to the puzzle so that many of the rows become constant, as displayed in this example,
and then perform a “Tetris” move of eliminating the constant rows to arrive at a secondary Sudoku puzzle which one then analyzes in turn:
It is the iteration of this procedure that ultimately generates the non-periodic -adic structure.
Let be a finite set of order ; in applications will be typically something like a finite abelian group, such as the cyclic group . Let us define a -bounded function to be a function such that for all . There are many seminorms of interest that one places on functions that are bounded by on -bounded functions, such as the Gowers uniformity seminorms for (which are genuine norms for ). All seminorms in this post will be implicitly assumed to obey this property.
In additive combinatorics, a significant role is played by inverse theorems, which abstractly take the following form for certain choices of seminorm , some parameters , and some class of -bounded functions:
Theorem 1 (Inverse theorem template) If is a -bounded function with , then there exists such that , where denotes the usual inner product
Informally, one should think of as being somewhat small but fixed independently of , as being somewhat smaller but depending only on (and on the seminorm), and as representing the “structured functions” for these choices of parameters. There is some flexibility in exactly how to choose the class of structured functions, but intuitively an inverse theorem should become more powerful when this class is small. Accordingly, let us define the -entropy of the seminorm to be the least cardinality of for which such an inverse theorem holds. Seminorms with low entropy are ones for which inverse theorems can be expected to be a useful tool. This concept arose in some discussions I had with Ben Green many years ago, but never appeared in print, so I decided to record some observations we had on this concept here on this blog.
Lebesgue norms for have exponentially large entropy (and so inverse theorems are not expected to be useful in this case):
Proposition 2 ( norm has exponentially large inverse entropy) Let and . Then the -entropy of is at most . Conversely, for any , the -entropy of is at least for some absolute constant .
Proof: If is -bounded with , then we have
and hence by the triangle inequality we have where is either the real or imaginary part of , which takes values in . If we let be rounded to the nearest multiple of , then by the triangle inequality again we have There are only at most possible values for each value of , and hence at most possible choices for . This gives the first claim.Now suppose that there is an -inverse theorem for some of cardinality . If we let be a random sign function (so the are independent random variables taking values in with equal probability), then there is a random such that
and hence by the pigeonhole principle there is a deterministic such that On the other hand, from the Hoeffding inequality one has for some absolute constant , hence as claimed.Most seminorms of interest in additive combinatorics, such as the Gowers uniformity norms, are bounded by some finite norm thanks to Hölder’s inequality, so from the above proposition and the obvious monotonicity properties of entropy, we conclude that all Gowers norms on finite abelian groups have at most exponential inverse theorem entropy. But we can do significantly better than this:
- For the seminorm , one can simply take to consist of the constant function , and the -entropy is clearly equal to for any .
- For the norm, the standard Fourier-analytic inverse theorem asserts that if then for some Fourier character . Thus the -entropy is at most .
- For the norm on cyclic groups for , the inverse theorem proved by Green, Ziegler, and myself gives an -inverse theorem for some and consisting of nilsequences for some filtered nilmanifold of degree in a finite collection of cardinality , some polynomial sequence (which was subsequently observed by Candela-Sisask (see also Manners) that one can choose to be -periodic), and some Lipschitz function of Lipschitz norm . By the Arzela-Ascoli theorem, the number of possible (up to uniform errors of size at most , say) is . By standard arguments one can also ensure that the coefficients of the polynomial are , and then by periodicity there are only such polynomials. As a consequence, the -entropy is of polynomial size (a fact that seems to have first been implicitly observed in Lemma 6.2 of this paper of Frantzikinakis; thanks to Ben Green for this reference). One can obtain more precise dependence on using the quantitative version of this inverse theorem due to Manners; back of the envelope calculations using Section 5 of that paper suggest to me that one can take to be polynomial in and the entropy to be of the order , or alternatively one can reduce the entropy to at the cost of degrading to .
- If one replaces the cyclic group by a vector space over some fixed finite field of prime order (so that ), then the inverse theorem of Ziegler and myself (available in both high and low characteristic) allows one to obtain an -inverse theorem for some and the collection of non-classical degree polynomial phases from to , which one can normalize to equal at the origin, and then by the classification of such polynomials one can calculate that the entropy is of quasipolynomial size in . By using the recent work of Gowers and Milicevic, one can make the dependence on here more precise, but we will not perform these calcualtions here.
- For the norm on an arbitrary finite abelian group, the recent inverse theorem of Jamneshan and myself gives (after some calculations) a bound of the polynomial form on the -entropy for some , which one can improve slightly to if one degrades to , where is the maximal order of an element of , and is the rank (the number of elements needed to generate ). This bound is polynomial in in the cyclic group case and quasipolynomial in general.
For general finite abelian groups , we do not yet have an inverse theorem of comparable power to the ones mentioned above that give polynomial or quasipolynomial upper bounds on the entropy. However, there is a cheap argument that at least gives some subexponential bounds:
Proposition 3 (Cheap subexponential bound) Let and , and suppose that is a finite abelian group of order for some sufficiently large . Then the -complexity of is at most .
Proof: (Sketch) We use a standard random sampling argument, of the type used for instance by Croot-Sisask or Briet-Gopi (thanks to Ben Green for this latter reference). We can assume that for some sufficiently large , since otherwise the claim follows from Proposition 2.
Let be a random subset of with the events being iid with probability to be chosen later, conditioned to the event . Let be a -bounded function. By a standard second moment calculation, we see that with probability at least , we have
Thus, by the triangle inequality, if we choose for some sufficiently large , then for any -bounded with , one has with probability at least that We can write the left-hand side as where is the randomly sampled dual function Unfortunately, is not -bounded in general, but we have and the right-hand side can be shown to be on the average, so we can condition on the event that the right-hand side is without significant loss in falure probability.If we then let be rounded to the nearest Gaussian integer multiple of in the unit disk, one has from the triangle inequality that
where is the discretised randomly sampled dual function For any given , there are at most places where can be non-zero, and in those places there are possible values for . Thus, if we let be the collection of all possible associated to a given , the cardinality of this set is , and for any with , we have with probability at least .Now we remove the failure probability by independent resampling. By rounding to the nearest Gaussian integer multiple of in the unit disk for a sufficiently small , one can find a family of cardinality consisting of -bounded functions of norm at least such that for every -bounded with there exists such that
Now, let be independent samples of for some to be chosen later. By the preceding discussion, we see that with probability at least , we have for any given , so by the union bound, if we choose for a large enough , we can find such that for all , and hence y the triangle inequality Taking to be the union of the (applying some truncation and rescaling to these -bounded functions to make them -bounded, and then -bounded), we obtain the claim.One way to obtain lower bounds on the inverse theorem entropy is to produce a collection of almost orthogonal functions with large norm. More precisely:
Proposition 4 Let be a seminorm, let , and suppose that one has a collection of -bounded functions such that for all , one has for all but at most choices of for all distinct . Then the -entropy of is at least .
Proof: Suppose we have an -inverse theorem with some family . Then for each there is such that . By the pigeonhole principle, there is thus such that for all in a subset of of cardinality at least :
We can sum this to obtain for some complex numbers of unit magnitude. By Cauchy-Schwarz, this implies and hence by the triangle inequality On the other hand, by hypothesis we can bound the left-hand side by . Rearranging, we conclude that and hence giving the claim.Thus for instance:
- For the norm, one can take to be the family of linear exponential phases with and , and obtain a linear lower bound of for the -entropy, thus matching the upper bound of up to constants when is fixed.
- For the norm, a similar calculation using polynomial phases of degree , combined with the Weyl sum estimates, gives a lower bound of for the -entropy for any fixed ; by considering nilsequences as well, together with nilsequence equidistribution theory, one can replace the exponent here by some quantity that goes to infinity as , though I have not attempted to calculate the exact rate.
- For the norm, another similar calculation using polynomial phases of degree should give a lower bound of for the -entropy, though I have not fully performed the calculation.
We close with one final example. Suppose is a product of two sets of cardinality , and we consider the Gowers box norm
One possible choice of class here are the indicators of “rectangles” with , (cf. this previous blog post on cut norms). By standard calculations, one can use this class to show that the -entropy of is , and a variant of the proof of the second part of Proposition 2 shows that this is the correct order of growth in . In contrast, a modification of Proposition 3 only gives an upper bound of the form (the bottleneck is ensuring that the randomly sampled dual functions stay bounded in ), which shows that while this cheap bound is not optimal, it can still broadly give the correct “type” of bound (specifically, intermediate growth between polynomial and exponential).Asgar Jamneshan and myself have just uploaded to the arXiv our preprint “The inverse theorem for the Gowers uniformity norm on arbitrary finite abelian groups: Fourier-analytic and ergodic approaches“. This paper, which is a companion to another recent paper of ourselves and Or Shalom, studies the inverse theory for the third Gowers uniformity norm
on an arbitrary finite abelian group , where is the multiplicative derivative. Our main result is as follows:
Theorem 1 (Inverse theorem for ) Let be a finite abelian group, and let be a -bounded function with for some . Then:
- (i) (Correlation with locally quadratic phase) There exists a regular Bohr set with and , a locally quadratic function , and a function such that
- (ii) (Correlation with nilsequence) There exists an explicit degree two filtered nilmanifold of dimension , a polynomial map , and a Lipschitz function of constant such that
Such a theorem was proven by Ben Green and myself in the case when was odd, and by Samorodnitsky in the -torsion case . In all cases one uses the “higher order Fourier analysis” techniques introduced by Gowers. After some now-standard manipulations (using for instance what is now known as the Balog-Szemerédi-Gowers lemma), one arrives (for arbitrary ) at an estimate that is roughly of the form
where denotes various -bounded functions whose exact values are not too important, and is a symmetric locally bilinear form. The idea is then to “integrate” this form by expressing it in the form for some locally quadratic ; this then allows us to write the above correlation as (after adjusting the functions suitably), and one can now conclude part (i) of the above theorem using some linear Fourier analysis. Part (ii) follows by encoding locally quadratic phase functions as nilsequences; for this we adapt an algebraic construction of Manners.So the key step is to obtain a representation of the form (1), possibly after shrinking the Bohr set a little if needed. This has been done in the literature in two ways:
- When is odd, one has the ability to divide by , and on the set one can establish (1) with . (This is similar to how in single variable calculus the function is a function whose second derivative is equal to .)
- When , then after a change of basis one can take the Bohr set to be for some , and the bilinear form can be written in coordinates as for some with . The diagonal terms cause a problem, but by subtracting off the rank one form one can write on the orthogonal complement of for some coefficients which now vanish on the diagonal: . One can now obtain (1) on this complement by taking
In our paper we can now treat the case of arbitrary finite abelian groups , by means of the following two new ingredients:
- (i) Using some geometry of numbers, we can lift the group to a larger (possibly infinite, but still finitely generated) abelian group with a projection map , and find a globally bilinear map on the latter group, such that one has a representation of the locally bilinear form by the globally bilinear form when are close enough to the origin.
- (ii) Using an explicit construction, one can show that every globally bilinear map has a representation of the form (1) for some globally quadratic function .
To illustrate (i), consider the Bohr set in (where denotes the distance to the nearest integer), and consider a locally bilinear form of the form for some real number and all integers (which we identify with elements of . For generic , this form cannot be extended to a globally bilinear form on ; however if one lifts to the finitely generated abelian group
(with projection map ) and introduces the globally bilinear form by the formula then one has (2) when lie in the interval . A similar construction works for higher rank Bohr sets.To illustrate (ii), the key case turns out to be when is a cyclic group , in which case will take the form
for some integer . One can then check by direct construction that (1) will be obeyed with regardless of whether is even or odd. A variant of this construction also works for , and the general case follows from a short calculation verifying that the claim (ii) for any two groups implies the corresponding claim (ii) for the product .This concludes the Fourier-analytic proof of Theorem 1. In this paper we also give an ergodic theory proof of (a qualitative version of) Theorem 1(ii), using a correspondence principle argument adapted from this previous paper of Ziegler, and myself. Basically, the idea is to randomly generate a dynamical system on the group , by selecting an infinite number of random shifts , which induces an action of the infinitely generated free abelian group on by the formula
Much as the law of large numbers ensures the almost sure convergence of Monte Carlo integration, one can show that this action is almost surely ergodic (after passing to a suitable Furstenberg-type limit where the size of goes to infinity), and that the dynamical Host-Kra-Gowers seminorms of that system coincide with the combinatorial Gowers norms of the original functions. One is then well placed to apply an inverse theorem for the third Host-Kra-Gowers seminorm for -actions, which was accomplished in the companion paper to this one. After doing so, one almost gets the desired conclusion of Theorem 1(ii), except that after undoing the application of the Furstenberg correspondence principle, the map is merely an almost polynomial rather than a polynomial, which roughly speaking means that instead of certain derivatives of vanishing, they instead are merely very small outside of a small exceptional set. To conclude we need to invoke a “stability of polynomials” result, which at this level of generality was first established by Candela and Szegedy (though we also provide an independent proof here in an appendix), which roughly speaking asserts that every approximate polynomial is close in measure to an actual polynomial. (This general strategy is also employed in the Candela-Szegedy paper, though in the absence of the ergodic inverse theorem input that we rely upon here, the conclusion is weaker in that the filtered nilmanifold is replaced with a general space known as a “CFR nilspace”.)This transference principle approach seems to work well for the higher step cases (for instance, the stability of polynomials result is known in arbitrary degree); the main difficulty is to establish a suitable higher step inverse theorem in the ergodic theory setting, which we hope to do in future research.
Rachel Greenfeld and I have just uploaded to the arXiv our preprint “Undecidable translational tilings with only two tiles, or one nonabelian tile“. This paper studies the following question: given a finitely generated group , a (periodic) subset of , and finite sets in , is it possible to tile by translations of the tiles ? That is to say, is there a solution to the (translational) tiling equation
for some subsets of , where denotes the set of sums if the sums are all disjoint (and is undefined otherwise), and denotes disjoint union. (One can also write the tiling equation in the language of convolutions as .)A bit more specifically, the paper studies the decidability of the above question. There are two slightly different types of decidability one could consider here:
- Logical decidability. For a given , one can ask whether the solvability of the tiling equation (1) is provable or disprovable in ZFC (where we encode all the data by appropriate constructions in ZFC). If this is the case we say that the tiling equation (1) (or more precisely, the solvability of this equation) is logically decidable, otherwise it is logically undecidable.
- Algorithmic decidability. For data in some specified class (and encoded somehow as binary strings), one can ask whether the solvability of the tiling equation (1) can be correctly determined for all choices of data in this class by the output of some Turing machine that takes the data as input (encoded as a binary string) and halts in finite time, returning either YES if the equation can be solved or NO otherwise. If this is the case, we say the tiling problem of solving (1) for data in the given class is algorithmically decidable, otherwise it is algorithmically undecidable.
Note that the notion of logical decidability is “pointwise” in the sense that it pertains to a single choice of data , whereas the notion of algorithmic decidability pertains instead to classes of data, and is only interesting when this class is infinite. Indeed, any tiling problem with a finite class of data is trivially decidable because one could simply code a Turing machine that is basically a lookup table that returns the correct answer for each choice of data in the class. (This is akin to how a student with a good memory could pass any exam if the questions are drawn from a finite list, merely by memorising an answer key for that list of questions.)
The two notions are related as follows: if a tiling problem (1) is algorithmically undecidable for some class of data, then the tiling equation must be logically undecidable for at least one choice of data for this class. For if this is not the case, one could algorithmically decide the tiling problem by searching for proofs or disproofs that the equation (1) is solvable for a given choice of data; the logical decidability of all such solvability questions will ensure that this algorithm always terminates in finite time.
One can use the Gödel completeness theorem to interpret logical decidability in terms of universes (also known as structures or models) of ZFC. In addition to the “standard” universe of sets that we believe satisfies the axioms of ZFC, there are also other “nonstandard” universes that also obey the axioms of ZFC. If the solvability of a tiling equation (1) is logically undecidable, this means that such a tiling exists in some universes of ZFC, but not in others.
(To continue the exam analogy, we thus see that a yes-no exam question is logically undecidable if the answer to the question is yes in some parallel universes, but not in others. A course syllabus is algorithmically undecidable if there is no way to prepare for the final exam for the course in a way that guarantees a perfect score (in the standard universe).)
Questions of decidability are also related to the notion of aperiodicity. For a given , a tiling equation (1) is said to be aperiodic if the equation (1) is solvable (in the standard universe of ZFC), but none of the solutions (in that universe) are completely periodic (i.e., there are no solutions where all of the are periodic). Perhaps the most well-known example of an aperiodic tiling (in the context of , and using rotations as well as translations) come from the Penrose tilings, but there are many others besides.
It was (essentially) observed by Hao Wang in the 1960s that if a tiling equation is logically undecidable, then it must necessarily be aperiodic. Indeed, if a tiling equation fails to be aperiodic, then (in the standard universe) either there is a periodic tiling, or there are no tilings whatsoever. In the former case, the periodic tiling can be used to give a finite proof that the tiling equation is solvable; in the latter case, the compactness theorem implies that there is some finite fragment of that is not compatible with being tiled by , and this provides a finite proof that the tiling equation is unsolvable. Thus in either case the tiling equation is logically decidable.
This observation of Wang clarifies somewhat how logically undecidable tiling equations behave in the various universes of ZFC. In the standard universe, tilings exist, but none of them will be periodic. In nonstandard universes, tilings may or may not exist, and the tilings that do exist may be periodic (albeit with a nonstandard period); but there must be at least one universe in which no tiling exists at all.
In one dimension when (or more generally with a finite group), a simple pigeonholing argument shows that no tiling equations are aperiodic, and hence all tiling equations are decidable. However the situation changes in two dimensions. In 1966, Berger (a student of Wang) famously showed that there exist tiling equations (1) in the discrete plane that are aperiodic, or even logically undecidable; in fact he showed that the tiling problem in this case (with arbitrary choices of data ) was algorithmically undecidable. (Strictly speaking, Berger established this for a variant of the tiling problem known as the domino problem, but later work of Golomb showed that the domino problem could be easily encoded within the tiling problem.) This was accomplished by encoding the halting problem for Turing machines into the tiling problem (or domino problem); the latter is well known to be algorithmically undecidable (and thus have logically undecidable instances), and so the latter does also. However, the number of tiles required for Berger’s construction was quite large: his construction of an aperiodic tiling required tiles, and his construction of a logically undecidable tiling required an even larger (and not explicitly specified) collection of tiles. Subsequent work by many authors did reduce the number of tiles required; in the setting, the current world record for the fewest number of tiles in an aperiodic tiling is (due to Amman, Grunbaum, and Shephard) and for a logically undecidable tiling is (due to Ollinger). On the other hand, it is conjectured (see Grunbaum-Shephard and Lagarias-Wang) that one cannot lower all the way to :
Conjecture 1 (Periodic tiling conjecture) If is a periodic subset of a finitely generated abelian group , and is a finite subset of , then the tiling equation is not aperiodic.
This conjecture is known to be true in two dimensions (by work of Bhattacharya when , and more recently by us when ), but remains open in higher dimensions. By the preceding discussion, the conjecture implies that every tiling equation with a single tile is logically decidable, and the problem of whether a given periodic set can be tiled by a single tile is algorithmically decidable.
In this paper we show on the other hand that aperiodic and undecidable tilings exist when , at least if one is permitted to enlarge the group a bit:
Theorem 2 (Logically undecidable tilings)
- (i) There exists a group of the form for some finite abelian , a subset of , and finite sets such that the tiling equation is logically undecidable (and hence also aperiodic).
- (ii) There exists a dimension , a periodic subset of , and finite sets such that tiling equation is logically undecidable (and hence also aperiodic).
- (iii) There exists a non-abelian finite group (with the group law still written additively), a subset of , and a finite set such that the nonabelian tiling equation is logically undecidable (and hence also aperiodic).
We also have algorithmic versions of this theorem. For instance, the algorithmic version of (i) is that the problem of determining solvability of the tiling equation for a given choice of finite abelian group , subset of , and finite sets is algorithmically undecidable. Similarly for (ii), (iii).
This result (together with a negative result discussed below) suggest to us that there is a significant qualitative difference in the theory of tiling by a single (abelian) tile, and the theory of tiling with multiple tiles (or one non-abelian tile). (The positive results on the periodic tiling conjecture certainly rely heavily on the fact that there is only one tile, in particular there is a “dilation lemma” that is only available in this setting that is of key importance in the two dimensional theory.) It would be nice to eliminate the group from (i) (or to set in (ii)), but I think this would require a fairly significant modification of our methods.
Like many other undecidability results, the proof of Theorem 2 proceeds by a sequence of reductions, in which the undecidability of one problem is shown to follow from the undecidability of another, more “expressive” problem that can be encoded inside the original problem, until one reaches a problem that is so expressive that it encodes a problem already known to be undecidable. Indeed, all three undecidability results are ultimately obtained from Berger’s undecidability result on the domino problem.
The first step in increasing expressiveness is to observe that the undecidability of a single tiling equation follows from the undecidability of a system of tiling equations. More precisely, suppose we have non-empty finite subsets of a finitely generated group for and , as well as periodic sets of for , such that it is logically undecidable whether the system of tiling equations
for has no solution in . Then, for any , we can “stack” these equations into a single tiling equation in the larger group , and specifically to the equation where and It is a routine exercise to check that the system of equations (2) admits a solution in if and only if the single equation (3) admits a equation in . Thus, to prove the undecidability of a single equation of the form (3) it suffices to establish undecidability of a system of the form (2); note here how the freedom to select the auxiliary group is important here.We view systems of the form (2) as belonging to a kind of “language” in which each equation in the system is a “sentence” in the language imposing additional constraints on a tiling. One can now pick and choose various sentences in this language to try to encode various interesting problems. For instance, one can encode the concept of a function taking values in a finite group as a single tiling equation
since the solutions to this equation are precisely the graphs of a function . By adding more tiling equations to this equation to form a larger system, we can start imposing additional constraints on this function . For instance, if is a coset of some subgroup of , we can impose the additional equation to impose the additional constraint that for all , if we desire. If happens to contain two distinct elements , and , then the additional equation imposes the additional constraints that for all , and additionally that for all .This begins to resemble the equations that come up in the domino problem. Here one has a finite set of Wang tiles – unit squares where each of the four sides is colored with a color (corresponding to the four cardinal directions North, South, East, and West) from some finite set of colors. The domino problem is then to tile the plane with copies of these tiles in such a way that adjacent sides match. In terms of equations, one is seeking to find functions obeying the pointwise constraint
for all where is the set of colors associated to the set of Wang tiles being used, and the matching constraints for all . As it turns out, the pointwise constraint (7) can be encoded by tiling equations that are fancier versions of (4), (5), (6) that involve only one unknown tiling set , but in order to encode the matching constraints (8) we were forced to introduce a second tile (or work with nonabelian tiling equations). This appears to be an inherent feature of the method, since we found a partial rigidity result for tilings of one tile in one dimension that obstructs this encoding strategy from working when one only has one tile available. The result is as follows:
Proposition 3 (Swapping property) Consider the solutions to a tiling equation in a one-dimensional group (with a finite abelian group, finite, and periodic). Suppose there are two solutions to this equation that agree on the left in the sense that For any function , define the “swap” of and to be the set Then also solves the equation (9).
One can think of and as “genes” with “nucleotides” , at each position , and is a new gene formed by choosing one of the nucleotides from the “parent” genes , at each position. The above proposition then says that the solutions to the equation (9) must be closed under “genetic transfer” among any pair of genes that agree on the left. This seems to present an obstruction to trying to encode equation such as
for two functions (say), which is a toy version of the matching constraint (8), since the class of solutions to this equation turns out not to obey this swapping property. On the other hand, it is easy to encode such equations using two tiles instead of one, and an elaboration of this construction is used to prove our main theorem.In the modern theory of higher order Fourier analysis, a key role are played by the Gowers uniformity norms for . For finitely supported functions , one can define the (non-normalised) Gowers norm by the formula
where denotes complex conjugation, and then on any discrete interval and any function we can then define the (normalised) Gowers norm where is the extension of by zero to all of . Thus for instance (which technically makes a seminorm rather than a norm), and one can calculate where , and we use the averaging notation .The significance of the Gowers norms is that they control other multilinear forms that show up in additive combinatorics. Given any polynomials and functions , we define the multilinear form
(assuming that the denominator is finite and non-zero). Thus for instance where we view as formal (indeterminate) variables, and are understood to be extended by zero to all of . These forms are used to count patterns in various sets; for instance, the quantity is closely related to the number of length three arithmetic progressions contained in . Let us informally say that a form is controlled by the norm if the form is small whenever are -bounded functions with at least one of the small in norm. This definition was made more precise by Gowers and Wolf, who then defined the true complexity of a form to be the least such that is controlled by the norm. For instance,- and have true complexity ;
- has true complexity ;
- has true complexity ;
- The form (which among other things could be used to count twin primes) has infinite true complexity (which is quite unfortunate for applications).
Gowers and Wolf formulated a conjecture on what this complexity should be, at least for linear polynomials ; Ben Green and I thought we had resolved this conjecture back in 2010, though it turned out there was a subtle gap in our arguments and we were only able to resolve the conjecture in a partial range of cases. However, the full conjecture was recently resolved by Daniel Altman.
The (semi-)norm is so weak that it barely controls any averages at all. For instance the average
is not controlled by the semi-norm: it is perfectly possible for a -bounded function to even have vanishing norm but have large value of (consider for instance the parity function ).Because of this, I propose inserting an additional norm in the Gowers uniformity norm hierarchy between the and norms, which I will call the (or “profinite “) norm:
where ranges over all arithmetic progressions in . This can easily be seen to be a norm on functions that controls the norm. It is also basically controlled by the norm for -bounded functions ; indeed, if is an arithmetic progression in of some spacing , then we can write as the intersection of an interval with a residue class modulo , and from Fourier expansion we have If we let be a standard bump function supported on with total mass and is a parameter then (extending by zero outside of ), as can be seen by using the triangle inequality and the estimate After some Fourier expansion of we now have Writing as a linear combination of and using the Gowers–Cauchy–Schwarz inequality, we conclude hence on optimising in we have Forms which are controlled by the norm (but not ) would then have their true complexity adjusted to with this insertion.The norm recently appeared implicitly in work of Peluse and Prendiville, who showed that the form had true complexity in this notation (with polynomially strong bounds). [Actually, strictly speaking this control was only shown for the third function ; for the first two functions one needs to localize the norm to intervals of length . But I will ignore this technical point to keep the exposition simple.] The weaker claim that has true complexity is substantially easier to prove (one can apply the circle method together with Gauss sum estimates).
The well known inverse theorem for the norm tells us that if a -bounded function has norm at least for some , then there is a Fourier phase such that
this follows easily from (1) and Plancherel’s theorem. Conversely, from the Gowers–Cauchy–Schwarz inequality one hasFor one has a trivial inverse theorem; by definition, the norm of is at least if and only if
Thus the frequency appearing in the inverse theorem can be taken to be zero when working instead with the norm.For one has the intermediate situation in which the frequency is not taken to be zero, but is instead major arc. Indeed, suppose that is -bounded with , thus
for some progression . This forces the spacing of this progression to be . We write the above inequality as for some residue class and some interval . By Fourier expansion and the triangle inequality we then have for some integer . Convolving by for a small multiple of and a Schwartz function of unit mass with Fourier transform supported on , we have The Fourier transform of is bounded by and supported on , thus by Fourier expansion and the triangle inequality we have for some , so in particular . Thus we have for some of the major arc form with . Conversely, for of this form, some routine summation by parts gives the bound so if (2) holds for a -bounded then one must have .Here is a diagram showing some of the control relationships between various Gowers norms, multilinear forms, and duals of classes of functions (where each class of functions induces a dual norm :
Here I have included the three classes of functions that one can choose from for the inverse theorem, namely degree two nilsequences, bracket quadratic phases, and local quadratic phases, as well as the more narrow class of globally quadratic phases.
The Gowers norms have counterparts for measure-preserving systems , known as Host-Kra seminorms. The norm can be defined for as
and the norm can be defined as The seminorm is orthogonal to the invariant factor (generated by the (almost everywhere) invariant measurable subsets of ) in the sense that a function has vanishing seminorm if and only if it is orthogonal to all -measurable (bounded) functions. Similarly, the norm is orthogonal to the Kronecker factor , generated by the eigenfunctions of (that is to say, those obeying an identity for some -invariant ); for ergodic systems, it is the largest factor isomorphic to rotation on a compact abelian group. In analogy to the Gowers norm, one can then define the Host-Kra seminorm by it is orthogonal to the profinite factor , generated by the periodic sets of (or equivalently, by those eigenfunctions whose eigenvalue is a root of unity); for ergodic systems, it is the largest factor isomorphic to rotation on a profinite abelian group.The (classical) Möbius function is the unique function that obeys the classical Möbius inversion formula:
Proposition 1 (Classical Möbius inversion) Let be functions from the natural numbers to an additive group . Then the following two claims are equivalent:
- (i) for all .
- (ii) for all .
There is a generalisation of this formula to (finite) posets, due to Hall, in which one sums over chains in the poset:
Proposition 2 (Poset Möbius inversion) Let be a finite poset, and let be functions from that poset to an additive group . Then the following two claims are equivalent:(Note from the finite nature of that the inner sum in (ii) is vacuous for all but finitely many .)
- (i) for all , where is understood to range in .
- (ii) for all , where in the inner sum are understood to range in with the indicated ordering.
Comparing Proposition 2 with Proposition 1, it is natural to refer to the function as the Möbius function of the poset; the condition (ii) can then be written as
Proof: If (i) holds, then we have for any . Iterating this we obtain (ii). Conversely, from (ii) and separating out the term, and grouping all the other terms based on the value of , we obtain (1), and hence (i).In fact it is not completely necessary that the poset be finite; an inspection of the proof shows that it suffices that every element of the poset has only finitely many predecessors .
It is not difficult to see that Proposition 2 includes Proposition 1 as a special case, after verifying the combinatorial fact that the quantity
is equal to when divides , and vanishes otherwise.I recently discovered that Proposition 2 can also lead to a useful variant of the inclusion-exclusion principle. The classical version of this principle can be phrased in terms of indicator functions: if are subsets of some set , then
In particular, if there is a finite measure on for which are all measurable, we haveOne drawback of this formula is that there are exponentially many terms on the right-hand side: of them, in fact. However, in many cases of interest there are “collisions” between the intersections (for instance, perhaps many of the pairwise intersections agree), in which case there is an opportunity to collect terms and hopefully achieve some cancellation. It turns out that it is possible to use Proposition 2 to do this, in which one only needs to sum over chains in the resulting poset of intersections:
Proposition 3 (Hall-type inclusion-exclusion principle) Let be subsets of some set , and let be the finite poset formed by intersections of some of the (with the convention that is the empty intersection), ordered by set inclusion. Then for any , one has where are understood to range in . In particular (setting to be the empty intersection) if the are all proper subsets of then we have In particular, if there is a finite measure on for which are all measurable, we have
Using the Möbius function on the poset , one can write these formulae as
andProof: It suffices to establish (2) (to derive (3) from (2) observe that all the are contained in one of the , so the effect of may be absorbed into ). Applying Proposition 2, this is equivalent to the assertion that
for all . But this amounts to the assertion that for each , there is precisely one in with the property that and for any in , namely one can take to be the intersection of all in such that contains .
Example 4 If with , and are all distinct, then we have for any finite measure on that makes measurable that due to the four chains , , , of length one, and the three chains , , of length two. Note that this expansion just has six terms in it, as opposed to the given by the usual inclusion-exclusion formula, though of course one can reduce the number of terms by combining the factors. This may not seem particularly impressive, especially if one views the term as really being three terms instead of one, but if we add a fourth set with for all , the formula now becomes and we begin to see more cancellation as we now have just seven terms (or ten if we count as four terms) instead of terms.
Example 5 (Variant of Legendre sieve) If are natural numbers, and is some sequence of complex numbers with only finitely many terms non-zero, then by applying the above proposition to the sets and with equal to counting measure weighted by the we obtain a variant of the Legendre sieve where range over the set formed by taking least common multiples of the (with the understanding that the empty least common multiple is ), and denotes the assertion that divides but is strictly less than . I am curious to know of this version of the Legendre sieve already appears in the literature (and similarly for the other applications of Proposition 2 given here).
If the poset has bounded depth then the number of terms in Proposition 3 can end up being just polynomially large in rather than exponentially large. Indeed, if all chains in have length at most then the number of terms here is at most . (The examples (4), (5) are ones in which the depth is equal to two.) I hope to report in a later post on how this version of inclusion-exclusion with polynomially many terms can be useful in an application.
Actually in our application we need an abstraction of the above formula, in which the indicator functions are replaced by more abstract idempotents:
Proposition 6 (Hall-type inclusion-exclusion principle for idempotents) Let be pairwise commuting elements of some ring with identity, which are all idempotent (thus for ). Let be the finite poset formed by products of the (with the convention that is the empty product), ordered by declaring when (note that all the elements of are idempotent so this is a partial ordering). Then for any , one has where are understood to range in . In particular (setting ) if all the are not equal to then we have
Morally speaking this proposition is equivalent to the previous one after applying a “spectral theorem” to simultaneously diagonalise all of the , but it is quicker to just adapt the previous proof to establish this proposition directly. Using the Möbius function for , we can rewrite these formulae as
andProof: Again it suffices to verify (6). Using Proposition 2 as before, it suffices to show that
for all (all sums and products are understood to range in ). We can expand where ranges over all subsets of that contain . For such an , if we write , then is the greatest lower bound of , and we observe that vanishes whenever fails to contain some with . Thus the only that give non-zero contributions to (8) are the intervals of the form for some (which then forms the greatest lower bound for that interval), and the claim (7) follows (after noting that for any ).
Laura Cladek and I have just uploaded to the arXiv our paper “Additive energy of regular measures in one and higher dimensions, and the fractal uncertainty principle“. This paper concerns a continuous version of the notion of additive energy. Given a finite measure on and a scale , define the energy at scale to be the quantity
where is the product measure on formed from four copies of the measure on . We will be interested in Cantor-type measures , supported on a compact set and obeying the Ahlfors-David regularity condition for all balls and some constants , as well as the matching lower bound when whenever . One should think of as a -dimensional fractal set, and as some vaguely self-similar measure on this set.Note that once one fixes , the variable in (1) is constrained to a ball of radius , hence we obtain the trivial upper bound
If the set contains a lot of “additive structure”, one can expect this bound to be basically sharp; for instance, if is an integer, is a -dimensional unit disk, and is Lebesgue measure on this disk, one can verify that (where we allow implied constants to depend on . However we show that if the dimension is non-integer, then one obtains a gain:
Theorem 1 If is not an integer, and are as above, then for some depending only on .
Informally, this asserts that Ahlfors-David regular fractal sets of non-integer dimension cannot behave as if they are approximately closed under addition. In fact the gain we obtain is quasipolynomial in the regularity constant :
(We also obtain a localised version in which the regularity condition is only required to hold at scales between and .) Such a result was previously obtained (with more explicit values of the implied constants) in the one-dimensional case by Dyatlov and Zahl; but in higher dimensions there does not appear to have been any results for this general class of sets and measures . In the paper of Dyatlov and Zahl it is noted that some dependence on is necessary; in particular, cannot be much better than . This reflects the fact that there are fractal sets that do behave reasonably well with respect to addition (basically because they are built out of long arithmetic progressions at many scales); however, such sets are not very Ahlfors-David regular. Among other things, this result readily implies a dimension expansion result for any non-degenerate smooth map , including the sum map and (in one dimension) the product map , where the non-degeneracy condition required is that the gradients are invertible for every . We refer to the paper for the formal statement.Our higher-dimensional argument shares many features in common with that of Dyatlov and Zahl, notably a reliance on the modern tools of additive combinatorics (and specifically the Bogulybov-Ruzsa lemma of Sanders). However, in one dimension we were also able to find a completely elementary argument, avoiding any particularly advanced additive combinatorics and instead primarily exploiting the order-theoretic properties of the real line, that gave a superior value of , namely
One of the main reasons for obtaining such improved energy bounds is that they imply a fractal uncertainty principle in some regimes. We focus attention on the model case of obtaining such an uncertainty principle for the semiclassical Fourier transform
where is a small parameter. If are as above, and denotes the -neighbourhood of , then from the Hausdorff-Young inequality one obtains the trivial bound (There are also variants involving pairs of sets , but for simplicity we focus on the uncertainty principle for a single set .) The fractal uncertainty principle, when it applies, asserts that one can improve this to for some ; informally, this asserts that a function and its Fourier transform cannot simultaneously be concentrated in the set when , and that a function cannot be concentrated on and have its Fourier transform be of maximum size on when . A modification of the disk example mentioned previously shows that such a fractal uncertainty principle cannot hold if is an integer. However, in one dimension, the fractal uncertainty principle is known to hold for all . The above-mentioned results of Dyatlov and Zahl were able to establish this for close to , and the remaining cases and were later established by Bourgain-Dyatlov and Dyatlov-Jin respectively. Such uncertainty principles have applications to hyperbolic dynamics, in particular in establishing spectral gaps for certain Selberg zeta functions.It remains a largely open problem to establish a fractal uncertainty principle in higher dimensions. Our results allow one to establish such a principle when the dimension is close to , and is assumed to be odd (to make a non-integer). There is also work of Han and Schlag that obtains such a principle when one of the copies of is assumed to have a product structure. We hope to obtain further higher-dimensional fractal uncertainty principles in subsequent work.
We now sketch how our main theorem is proved. In both one dimension and higher dimensions, the main point is to get a preliminary improvement
over the trivial bound (2) for any small , provided is sufficiently small depending on ; one can then iterate this bound by a fairly standard “induction on scales” argument (which roughly speaking can be used to show that energies behave somewhat multiplicatively in the scale parameter ) to propagate the bound to a power gain at smaller scales. We found that a particularly clean way to run the induction on scales was via use of the Gowers uniformity norm , and particularly via a clean Fubini-type inequality (ultimately proven using the Gowers-Cauchy-Schwarz inequality) that allows one to “decouple” coarse and fine scale aspects of the Gowers norms (and hence of additive energies).It remains to obtain the preliminary improvement. In one dimension this is done by identifying some “left edges” of the set that supports : intervals that intersect , but such that a large interval just to the left of this interval is disjoint from . Here is a large constant and is a scale parameter. It is not difficult to show (using in particular the Archimedean nature of the real line) that if one has the Ahlfors-David regularity condition for some then left edges exist in abundance at every scale; for instance most points of would be expected to lie in quite a few of these left edges (much as most elements of, say, the ternary Cantor set would be expected to contain a lot of s in their base expansion). In particular, most pairs would be expected to lie in a pair of left edges of equal length. The key point is then that if lies in such a pair with , then there are relatively few pairs at distance from for which one has the relation , because will both tend to be to the right of respectively. This causes a decrement in the energy at scale , and by carefully combining all these energy decrements one can eventually cobble together the energy bound (3).
We were not able to make this argument work in higher dimension (though perhaps the cases and might not be completely out of reach from these methods). Instead we return to additive combinatorics methods. If the claim (3) failed, then by applying the Balog-Szemeredi-Gowers theorem we can show that the set has high correlation with an approximate group , and hence (by the aforementioned Bogulybov-Ruzsa type theorem of Sanders, which is the main source of the quasipolynomial bounds in our final exponent) will exhibit an approximate “symmetry” along some non-trivial arithmetic progression of some spacing length and some diameter . The -neighbourhood of will then resemble the union of parallel “cylinders” of dimensions . If we focus on a typical -ball of , the set now resembles a Cartesian product of an interval of length with a subset of a -dimensional hyperplane, which behaves approximately like an Ahlfors-David regular set of dimension (this already lets us conclude a contradiction if ). Note that if the original dimension was non-integer then this new dimension will also be non-integer. It is then possible to contradict the failure of (3) by appealing to a suitable induction hypothesis at one lower dimension.
Ben Green and I have updated our paper “An arithmetic regularity lemma, an associated counting lemma, and applications” to account for a somewhat serious issue with the paper that was pointed out to us recently by Daniel Altman. This paper contains two core theorems:
- An “arithmetic regularity lemma” that, roughly speaking, decomposes an arbitrary bounded sequence on an interval as an “irrational nilsequence” of controlled complexity, plus some “negligible” errors (where one uses the Gowers uniformity norm as the main norm to control the neglibility of the error); and
- An “arithmetic counting lemma” that gives an asymptotic formula for counting various averages for various affine-linear forms when the functions are given by irrational nilsequences.
The combination of the two theorems is then used to address various questions in additive combinatorics.
There are no direct issues with the arithmetic regularity lemma. However, it turns out that the arithmetic counting lemma is only true if one imposes an additional property (which we call the “flag property”) on the affine-linear forms . Without this property, there does not appear to be a clean asymptotic formula for these averages if the only hypothesis one places on the underlying nilsequences is irrationality. Thus when trying to understand the asymptotics of averages involving linear forms that do not obey the flag property, the paradigm of understanding these averages via a combination of the regularity lemma and a counting lemma seems to require some significant revision (in particular, one would probably have to replace the existing regularity lemma with some variant, despite the fact that the lemma is still technically true in this setting). Fortunately, for most applications studied to date (including the important subclass of translation-invariant affine forms), the flag property holds; however our claim in the paper to have resolved a conjecture of Gowers and Wolf on the true complexity of systems of affine forms must now be narrowed, as our methods only verify this conjecture under the assumption of the flag property.
In a bit more detail: the asymptotic formula for our counting lemma involved some finite-dimensional vector spaces for various natural numbers , defined as the linear span of the vectors as ranges over the parameter space . Roughly speaking, these spaces encode some constraints one would expect to see amongst the forms . For instance, in the case of length four arithmetic progressions when , , and
for , then is spanned by the vectors and and can thus be described as the two-dimensional linear space while is spanned by the vectors , , and can be described as the hyperplane As a special case of the counting lemma, we can check that if takes the form for some irrational , some arbitrary , and some smooth , then the limiting value of the average as is equal to which reflects the constraints and These constraints follow from the descriptions (1), (2), using the containment to dispense with the lower order term (which then plays no further role in the analysis).The arguments in our paper turn out to be perfectly correct under the assumption of the “flag property” that for all . The problem is that the flag property turns out to not always hold. A counterexample, provided by Daniel Altman, involves the four linear forms
Here it turns out that and and is no longer contained in . The analogue of the asymptotic formula given previously for is then valid when vanishes, but not when is non-zero, because the identity holds in the former case but not the latter. Thus the output of any purported arithmetic regularity lemma in this case is now sensitive to the lower order terms of the nilsequence and cannot be described in a uniform fashion for all “irrational” sequences. There should still be some sort of formula for the asymptotics from the general equidistribution theory of nilsequences, but it could be considerably more complicated than what is presented in this paper.Fortunately, the flag property does hold in several key cases, most notably the translation invariant case when contains , as well as “complexity one” cases. Nevertheless non-flag property systems of affine forms do exist, thus limiting the range of applicability of the techniques in this paper. In particular, the conjecture of Gowers and Wolf (Theorem 1.13 in the paper) is now open again in the non-flag property case.
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