Polynomial bound for the Partition Rank vs the Analytic Rank of Tensors
Oliver Janzer
Abstract
A tensor defined over a finite field F has low analytic rank if the distribution of its values differs significantly from the uniform distribution. An order d tensor has partition rank 1 if it can be written as a product of two tensors of order less than d, and it has partition rank at most k if it can be written as a sum of k tensors of partition rank 1. In this paper, we prove that if the analytic rank of an order d tensor is at most r, then its partition rank is at most f(r,d,β£Fβ£), where, for fixed d and F, f is a polynomial in r. This is an improvement of a recent result of the author, where he obtained a tower-type bound. Prior to our work, the best known bound was an Ackermann-type function in r and d, though it did not depend on F. It follows from our results that a biased polynomial has low rank; there too we obtain a polynomial dependence improving the previously known Ackermann-type bound.
A similar polynomial bound for the partition rank was obtained independently and simultaneously by MiliΔeviΔ.
\dajAUTHORdetails
title = Polynomial bound for the Partition Rank vs the Analytic Rank of Tensors, author = Oliver Janzer,
plaintextauthor = Oliver Janzer,
keywords = partition rank, analytic rank, tensor,
\dajEDITORdetailsyear=2020,
number=7,
received=23 October 2018, revised=6 March 2019, published=19 May 2020, doi=10.19086/da.12935,
[classification=text]
1 Introduction
1.1 Bias and rank of polynomials
For a finite field F and a polynomial P:FnβF, we say that P is unbiased if the distribution of the values P(x) is close to the uniform distribution on F; otherwise we say that P is biased. It is an important direction of research in higher order Fourier analysis to understand the structure of biased polynomials.
Note that a generic degree d polynomial should be unbiased. In fact, as we will see below, if a degree d polynomial is biased, then it can be written as a function of not too many polynomials of degree at most dβ1. Let us now make this discussion more precise.
Definition 1.1**.**
Let F be a finite field and let Ο be a nontrivial character of F. The bias of a function f:FnβF with respect to Ο is defined to be biasΟβ(f)=ExβFnβ[Ο(f(x))]. (Here and elsewhere in the paper ExβGβh(x) denotes β£Gβ£1ββxβGβh(x).)
Remark 1.2*.*
Most of the previous work is on the case F=Fpβ with p a prime, in which case the standard definition of bias is bias(f)=ExβFnβΟf(x) where Ο=ep2Οiβ.
Definition 1.3**.**
Let P be a polynomial FnβF of degree d. The rank of P (denoted rank(P)) is defined to be the smallest integer r such that there exist polynomials Q1β,β¦,Qrβ:FnβF of degree at most dβ1 and a function f:FrβF such that P=f(Q1β,β¦,Qrβ).
As discussed above, it is known that if a polynomial has large bias, then it has low rank. The first result in this direction was proved by Green and Tao [4] who showed that if F is a field of prime order and P:FnβF is a polynomial of degree d with d<β£Fβ£ and bias(P)β₯Ξ΄>0, then rank(P)β€c(F,Ξ΄,d). Kaufman and Lovett [8] proved that the condition d<β£Fβ£ can be omitted. In both results, c has Ackermann-type dependence on its parameters. Finally, Bhowmick and Lovett [1] proved that if d<char(F) and bias(P)β₯β£Fβ£βs, then rank(P)β€cβ²(d,s). The novelty of this result is that cβ² does not depend on F. However, it still has Ackermann-type dependence on d and s.
One of our main results is the following theorem, which improves the result of Bhowmick and Lovett, unless β£Fβ£ is very large.
Theorem 1.4**.**
Let F be a finite field and let Ο be a nontrivial character of F. Let P be a polynomial FnβF of degree d<char(F). Suppose that biasΟβ(P)β₯Ο΅>0 where Ο΅β€1/β£Fβ£. Then
[TABLE]
where c is an absolute constant and cβ²(d)=4dd.
Recall that if G is an Abelian group and d is a positive integer, then the Gowers Ud norm (which is only a seminorm for d=1) of f:GβC is defined to be
[TABLE]
where C is the conjugation operator. It is a major area of research to understand the structure of functions f whose Ud norm is large. Our next theorem is a result in this direction.
Theorem 1.5**.**
Let F be a finite field and let Ο be a nontrivial character of F. Let P be a polynomial FnβF of degree d<char(F). Let f(x)=Ο(P(x)) and assume that β₯fβ₯Udββ₯Ο΅>0 where Ο΅β€1/β£Fβ£. Then
[TABLE]
where c is an absolute constant and cβ²(d)=4dd.
Our result implies a similar improvement to the bounds for the quantitative inverse theorem for Gowers norms for polynomial phase functions of degree d.
Theorem 1.6**.**
Let F be a field of prime order and let P be a polynomial FnβF of degree d<char(F). Let f(x)=ΟP(x) where Ο=eβ£Fβ£2Οiβ and assume that β₯fβ₯Udββ₯Ο΅>0 where Ο΅β€1/β£Fβ£. Then there exists a polynomial Q:FnβF of degree at most dβ1 such that
[TABLE]
where c is an absolute constant and cβ²(d)=4dd.
Theorems 1.4 and 1.6 easily follow from Theorem 1.5.
Proof of Theorem 1.4. Note that when f(x)=Ο(P(x)), then β₯fβ₯U12β=β£Ex,yβFnβf(x)βf(x+y)β£=β£ExβFnβf(x)β£2, so β₯fβ₯U1β=β£ExβFnβf(x)β£=β£biasΟβ(P)β£. However, β₯fβ₯Ukβ is increasing in k (see eg. Claim 6.2.2 in [6]), therefore β₯fβ₯Udββ₯β£biasΟβ(P)β£β₯Ο΅. The result is now immediate from Theorem 1.5.
Proof of Theorem 1.6. By Theorem 1.5, there exists a set of rβ€(cβ
2dβ
log(1/Ο΅))cβ²(d)+1 polynomials Q1β,β¦,Qrβ such that P(x) is a function of Q1β(x),β¦,Qrβ(x).
Then ΟP(x)=g(Q1β(x),β¦,Qrβ(x)) for some function g:FrβC. Let G=Fr. Note that β£g(y)β£=1 for all yβG, therefore β£g^β(Ο)β£β€1 for every character ΟβG^. Now ΟP(x)=βΟβG^βg^β(Ο)Ο((Q1β(x),β¦,Qrβ(x)), so
[TABLE]
Thus, there exists some ΟβG^ with β£ExβFnβΟP(x)Ο(Q1β(x),β¦,Qrβ(x))ββ£β₯1/β£Gβ£=1/β£Fβ£r. But Ο is of the form Ο(y1β,β¦,yrβ)=Οβiβ€rβΞ±iβyiβ for some Ξ±iββF. Then Ο(Q1β(x),β¦,Qrβ(x))=ΟQΞ±β(x), where QΞ±β is the degree dβ1 polynomial QΞ±β(x)=βiβ€rβΞ±iβQiβ(x). So Q=QΞ±β is a suitable choice.
1.2 Analytic rank and partition rank of tensors
Related to the bias and rank of polynomials are the notions of analytic rank and partition rank of tensors. Recall that if F is a field and V1β,β¦,Vdβ are finite dimensional vector spaces over F, then an order d tensor is a multilinear map T:V1βΓβ―ΓVdββF. (In this subsection, assume that dβ₯2.) Each Vkβ can be identified with Fnkβ for some nkβ, and then there exist ti1β,β¦,idβββF for all i1ββ€n1β,β¦,idββ€ndβ such that T(v1,β¦,vd)=βi1ββ€n1β,β¦,idββ€ndββti1β,β¦,idββvi1β1ββ¦vidβdβ for every v1βFn1β,β¦,vdβFndβ (where vkβ is the kth coordinate of the vector v). Indeed, ti1β,β¦,idββ is just T(ei1β,β¦,eidβ), where ei is the ith standard basis vector.
The following notion was introduced by Gowers and Wolf [3].
Definition 1.7**.**
Let F be a finite field, let V1β,β¦,Vdβ be finite dimensional vector spaces over F and let T:V1βΓβ―ΓVdββF be an order d tensor. Then the analytic rank of T is defined to be arank(T)=βlogβ£Fβ£βbias(T), where bias(T)=Ev1βV1β,β¦,vdβVdββ[Ο(T(v1,β¦,vd))] for any nontrivial character Ο of F.
Remark 1.8*.*
This is well-defined. Indeed, if Ο is a nontrivial character of F, then
[TABLE]
where T(v1,β¦,vdβ1,x) is viewed as a function in x. The second equality holds because
EvdβVdββΟ(T(v1,β¦,vd))=0 unless T(v1,β¦,vdβ1,x)β‘0, in which case it is 1.
Thus, Ev1βV1β,β¦,vdβVdββ[Ο(T(v1,β¦,vd))] does not depend on Ο, and is always positive. Moreover, it is at most 1, therefore the analytic rank is always nonnegative.
A different notion of rank was defined by Naslund [13].
Definition 1.9**.**
Let T:V1βΓβ―ΓVdββF be a (non-zero) order d tensor. We say that T has partition rank 1 if there is some Sβ[d] with Sξ =β
,Sξ =[d] such that T(v1,β¦,vd)=T1β(vi:iβS)T2β(vi:iξ βS) where T1β:βiβSβViββF,T2β:βiξ βSβViββF are tensors. In general, the partition rank of T is the smallest r such that T can be written as the sum of r tensors of partition rank 1. This number is denoted prank(T).
Kazhdan and Ziegler [9] and Lovett [11] proved that arank(T)β€prank(T). In the other direction, it follows from the work of Bhowmick and Lovett [1] that if an order d tensor T has arank(T)β€r, then prank(T)β€f(r,d) for some function f. Note that f does not depend on β£Fβ£ or the dimension of the vector spaces Vkβ. However, f has an Ackermann-type dependence on d and r. For d=3,4, better bounds were established by Haramaty and Shpilka [5]. They proved that for d=3 we have prank(T)=O(r4), and that for d=4 we have prank(T)=exp(O(r)).
The main result of our paper is a polynomial upper bound, which holds for general d.
Theorem 1.10**.**
Let T:V1βΓβ―ΓVdββF be an order d tensor with arank(T)β€r and assume that rβ₯1. Then
[TABLE]
for some absolute constant c, and cβ²(d)=4dd.
We remark that a very similar result was obtained independently and simultaneously by MiliΔeviΔ [12]. Moreover, in the special case d=4, a similar bound was proved independently by Lampert [10].
It is not hard to see that Theorem 1.10 implies Theorem 1.5. Indeed, let P be a polynomial FnβF of degree d<char(F), let f(x)=Ο(P(x)) and assume that β₯fβ₯Udββ₯Ο΅>0, where Ο΅β€1/β£Fβ£. Define T:(Fn)dβF by T(y1β,β¦,ydβ)=βSβ[d]β(β1)dββ£Sβ£P(βiβSβyiβ). By Lemma 2.4 from [3], T is a tensor of order d. Moreover, by the same lemma, we have T(y1β,β¦,ydβ)=βSβ[d]β(β1)dββ£Sβ£P(x+βiβSβyiβ) for any xβFn. Thus,
[TABLE]
for any xβFn. By averaging over all xβFn, it follows that bias(T)=β₯fβ₯Ud2dββ₯Ο΅2d. Thus, arank(T)β€2dlogβ£Fβ£β(1/Ο΅). Note that 2dlogβ£Fβ£β(1/Ο΅)β₯1. Therefore, by Theorem 1.10 with r=2dlogβ£Fβ£β(1/Ο΅), we get
[TABLE]
Note that T(y1β,β¦,ydβ)=Dy1βββ¦DydββP(x) where Dyβg(x)=g(x+y)βg(x). Thus, by Taylorβs approximation theorem, since d<char(F), we get P(x)=d!1βDxββ¦DxβP(0)+W(x)=d!1βT(x,β¦,x)+W(x) for some polynomial W of degree at most dβ1.
By equation (1), T can be written as a sum of at most (cβ
2dβ
log(1/Ο΅))cβ²(d) tensors of partition rank 1. Hence, d!1βT(x,β¦,x) can be written as a sum of at most (cβ
2dβ
log(1/Ο΅))cβ²(d) expressions of the form Q(x)R(x) where Q,R are polynomials of degree at most dβ1 each. Thus, PβW has rank at most (cβ
2dβ
log(1/Ο΅))cβ²(d), and therefore P has rank at most
[TABLE]
We remark that the proof of the main result of this paper follows the strategy introduced by the author in [7], but the argument is improved locally at a few places.
2 The proof of Theorem 1.10
2.1 Notation and preliminaries
In the rest of the paper, we identify Viβ with Fniβ. Thus, the set of all tensors V1βΓβ―ΓVdββF is the tensor product Fn1βββ―βFndβ, which will be denoted by G throughout this section. Also, B will always stand for the multiset {u1βββ―βudβ:uiββFniβΒ forΒ allΒ i}. The elements of B will be called pure tensors. Note that G=Fn1βββ―βFndβ can be viewed as the set of d-dimensional (n1β,β¦,ndβ)-arrays over F which in turn can be viewed as Fn1βn2ββ¦ndβ, equipped with the entry-wise dot product.
For Iβ[d], we write FI for β¨iβIβFniβ so that we naturally have G=FIβFIc, where Ic always denotes [d]βI.
If rβF[d]=G and sβF[k] (for some kβ€d), then we define rs to be the tensor in F[k+1,d] with coordinates (rs)ik+1β,β¦,idββ=βi1ββ€n1β,β¦,ikββ€nkββri1β,β¦,idββsi1β,β¦,ikββ. If k=d, then rs is the same as the entry-wise dot product r.s. Also, note that viewing r as a d-multilinear map R:Fn1βΓβ―ΓFndββF, we have R(v1,β¦,vd)=βi1ββ€niβ,β¦,idββ€ndββri1β,β¦,idββvi1β1ββ¦vidβdβ=r(v1ββ―βvd).
Finally, we use a non-standard notation and write kB to mean the set of elements of G which can be written as a sum of at most k elements of B, where B is some fixed (multi)subset of G, and similarly, we write kBβlB for the set of elements that can be obtained by adding at most k members and subtracting at most l members of B.
We will use the next result several times in our proofs. It is a version of Bogolyubovβs lemma, due to Sanders.
Lemma 2.1** (Sanders [14]).**
There is an absolute constant C with the following property. Let A be a subset of Fn with β£Aβ£β₯Ξ΄β£Fnβ£. Then 2Aβ2A contains a subspace of Fn of codimension at most C(log(1/Ξ΄))4.
Throughout the paper, C stands for the constant appearing in the previous lemma. Clearly we may assume that Cβ₯1. Logarithms are base 2.
2.2 The main lemma and some consequences
Theorem 1.10 will follow easily from the next lemma, which is the main technical result of this paper. See [2] for an application of a qualitative version of this lemma.
Lemma 2.2**.**
Let dβ₯1 be an integer and let Ξ΄β€1/2. Let f1β(d)=23d+3, f2β(d)=2β3d+3 and G(d,Ξ΄,F)=((logβ£Fβ£)c1β(d)(log1/Ξ΄))c2β(d) where c1β(d)=Cβ
23d+6 and c2β(d)=4dd. If Bβ²βB is a multiset such that β£Bβ²β£β₯Ξ΄β£Bβ£, then there exists a multiset Q whose elements are pure tensors chosen from f1β(d)Bβ²βf1β(d)Bβ² (but with arbitrary multiplicity) with the following property. The set of arrays rβG with r.q=0 for at least (1βf2β(d))β£Qβ£ choices qβQ is contained in βIβ[d],Iξ =β
βVIββFIc for subspaces VIββFI of dimension at most G(d,Ξ΄,F).
Throughout the paper, the functions G,c1β,c2β will refer to the functions introduced in the previous lemma. In fact, as F is fixed, we will write G(d,Ξ΄) to mean G(d,Ξ΄,F).
In this subsection we deduce Theorem 1.10 from Lemma 2.2.
The notion introduced in the next definition is closely related to the partition rank, but will be somewhat more convenient to work with.
Definition 2.3**.**
Let k be a positive integer. We say that rβG is k-degenerate if for every Iβ[d],Iξ =β
,Iξ =[d], there exists a subspace HIββFI of dimension at most k such that rββIβ[dβ1],Iξ =β
βHIββHIcβ.
If rβHIββFIc with dim(HIβ)β€k, then rβHIββHIcβ for some HIcββFIc of dimension at most k. (This follows by writing r as βjβ€mβsjββtjβ with {sjβ} a basis for HIβ and letting HIcβ be the span of all the tjβ.) Thus, r is k-degenerate if and only if rββIβ[dβ1],Iξ =β
βHIββFIc for some HIββFI of dimension at most k, or equivalently, if and only if rββIβ[dβ1],Iξ =β
βFIβHIcβ for some HIcββFIc of dimension at most k. Moreover, note that if r is k-degenerate, then prank(r)β€2dβ1k. This is because if Iξ =β
,Iβ[dβ1] and wβHIββHIcβ for subspaces HIββFI and HIcββFIc of dimension at most k, then w=βiβ€kβsiββtiβ for some siββHIβ, tiββHIcβ. But clearly, siββtiβ has partition rank 1.
Lemma 2.4**.**
Let Ξ΄β€1/2 and dβ₯2. Suppose that Lemma 2.2 has been proved for dβ²=dβ1. Let rβG be such that r(v1βββ―βvdβ1β)=0βFndβ for at least Ξ΄β£Fβ£n1ββ¦ndβ1β choices v1ββFn1β,β¦,vdβ1ββFndβ1β. Then r is f-degenerate for f=G(dβ1,Ξ΄).
Proof.
Write r=βiβsiββtiβ where siββF[dβ1] and {tiβ}iβ is a basis for Fndβ. Let D be the multiset {u1βββ―βudβ1β:u1ββFn1β,β¦,udβ1ββFndβ1β} and let Dβ²={wβD:rw=0}. Since β£Dβ²β£β₯Ξ΄β£Dβ£, by Lemma 2.2 there is a multiset Q with elements from 23d+2Dβ²β23d+2Dβ² such that the set of arrays rβ²βF[dβ1] with rβ².q=0 for all choices qβQ is contained in some βIβ[dβ1],Iξ =β
βVIββF[dβ1]βI, where dim(VIβ)β€G(dβ1,Ξ΄). Note that for every i we have siβ.w=0 for all wβDβ² and so also siβ.q=0 for all qβQ. Thus, rββIβ[dβ1],Iξ =β
βVIββFIc.
β
Now we are in a position to prove Theorem 1.10 conditional on Lemma 2.2.
Proof of Theorem 1.10.
Let T:Fn1βΓβ―ΓFndββF be an order d tensor with arank(T)β€r. By Remark 1.8, we have Pv1ββFn1β,β¦,vdβ1ββFndβ1ββ[T(v1β,β¦,vdβ1β,x)β‘0]β₯β£Fβ£βr. Writing t for the element in G corresponding to T, we get that t(v1βββ―βvdβ1ββx)β‘0 as a function of x for at least Ξ΄β£Fβ£n1ββ¦ndβ choices v1ββFn1β,β¦,vdβ1ββFndβ1β, where Ξ΄=β£Fβ£βr. But t(v_{1}\otimes\dots\otimes v_{d-1}\otimes x)=\big{(}t(v_{1}\otimes\dots\otimes v_{d-1})\big{)}.x, so we have t(v1βββ―βvdβ1β)=0 for all these choices of viβ. The condition rβ₯1 implies Ξ΄β€1/2, therefore by Lemma 2.4, t is f-degenerate for f=G(dβ1,Ξ΄). Hence,
[TABLE]
But there exists some absolute constant c such that c1β(d)c2β(dβ1)β€cc2β(d) holds for all d. Moreover, 2c2β(dβ1)β€c2β(d). Thus, prank(T)β€(cβ
logβ£Fβ£)c2β(d)β
rc2β(d)=(cβ
logβ£Fβ£)cβ²(d)β
rcβ²(d).
β
2.3 The overview of the proof of Lemma 2.2
The proof of the lemma goes by induction on d. In what follows, we shall prove results conditional on the assumption that Lemma 2.2 has been verified for all dβ²<d. Eventually, we will use these results to prove the induction step.
In this subsection, we give a detailed sketch of the proof in the d=3 case. At the end of the subsection, we also briefly sketch the d>3 case.
2.3.1 The high-level outline in the case d=3
We assume that Lemma 2.2 has been proven for dβ€2 and use this assumption to show that it holds for d=3. We will take Q=Q{1,2,3}ββͺQ{1}ββͺQ{2}ββͺQ{3}β with elements chosen from 23d+3Bβ²β23d+3Bβ² such that the QIβ have roughly equal size. This implies that if for some rβG we have r.q=0 for almost all qβQ, then r.q=0 holds for almost all qβQIβ for every I={1},{2},{3},{1,2,3}. We define Q{1,2,3}β first, in a way that if r.q=0 for almost all qβQ{1,2,3}β, then r=x+y where xβV{1,2,3}β for a vector space V{1,2,3}β which is independent of r and have small dimension, and y has small partition rank. This already implies that any array rβG with r.q=0 for almost all qβQ is contained in V{1,2,3}β+Fn1ββH{2,3}β(r)+Fn2ββH{1,3}β(r)+Fn3ββH{1,2}β(r) for some subspaces HIβ(r)βFI depending on r and of small dimension. We then find Q{1}β such that if rβV{1,2,3}β+Fn1ββH{2,3}β(r)+Fn2ββH{1,3}β(r)+Fn3ββH{1,2}β(r) has r.q=0 for almost all qβQ{1}β, then rβV{1,2,3}β+V{1}ββF{2,3}+Fn1ββV{2,3}β+Fn2ββK{1,3}β(r)+Fn3ββK{1,2}β(r), where V{1}ββFn1β and V{2,3}ββF{2,3} are subspaces independent of r and have small dimension, and KIβ(r)βFI are subspaces of small dimension (although quite a bit larger than dim(HIβ(r))). Then we find Q{2}β such that if rβV{1,2,3}β+V{1}ββF{2,3}+Fn1ββV{2,3}β+Fn2ββK{1,3}β(r)+Fn3ββK{1,2}β(r) has r.q=0 for almost all qβQ{2}β, then rβV{1,2,3}β+V{1}ββF{2,3}+Fn1ββV{2,3}β+V{2}ββF{1,3}+Fn2ββV{1,3}β+Fn3ββL{1,2}β(r), where V{2}ββFn2β and V{1,3}ββF{1,3} are subspaces independent of r and have small dimension, and L{1,2}β(r)βF{1,2} is a subspace of small dimension. Finally, we find Q{3}β such that if rβV{1,2,3}β+V{1}ββF{2,3}+Fn1ββV{2,3}β+V{2}ββF{1,3}+Fn2ββV{1,3}β+Fn3ββL{1,2}β(r) has r.q=0 for almost all qβQ{3}β, then rβV{1,2,3}β+V{1}ββF{2,3}+Fn1ββV{2,3}β+V{2}ββF{1,3}+Fn2ββV{1,3}β+V{3}ββF{1,2}+Fn3ββV{1,2}β, where V{3}ββFn3β and V{1,2}ββF{1,2} are subspaces independent of r and have small dimension.
How will we find Q{1,2,3}β,Q{1}β,Q{2}β and Q{3}β? In this outline we will only explain how to find Q{2}β (but finding Q{1}β and Q{3}β is very similar). We take Q{2}β=βuβUβuβQuβ where UβFn2β is a subspace of low codimension, and for each uβU, QuββF{1,3} is a multiset consisting of pure tensors such that if for some xβF{1,3} we have x.t=0 for almost all tβQuβ, then xβW{1,3}β(u)+Fn1ββW{3}β(u)+W{1}β(u)βFn3β for some subspaces WIβ(u)βFI not depending on x and of small dimension. Let us call a Quβ with this property forcing. We will also make sure that all the Quβ have roughly the same size.
2.3.2 Why does this Q{2}β work?
In what follows, we will sketch why this choice is suitable. We remark that in the general case this is done in Lemma 2.15. Let R consist of those
[TABLE]
such that r.q=0 for almost all qβQ{2}β. Let rβR. Write r=r2β+r3β+r4β where
[TABLE]
It is enough to prove that
[TABLE]
for some small subspaces V{2}ββFn2β, V{1,3}ββF{1,3} and L{1,2}β²β(r)βF{1,2} (in fact, we will be able to take V{2}β=Uβ₯).
First note that r2βu has small (partition) rank for every uβU. Indeed, r2βuβV{1}ββFn3β+Fn1ββV{2,3}βu+Fn3ββK{1,2}β(r)u, where, for a vector space L of tensors, Lu denotes the space {su:sβL}.
Moreover, since the Quβ all have roughly the same size, for almost every uβU we have that r.(uβt)=0 holds for almost every tβQuβ. But r.(uβt)=(ru).t, therefore as Quβ is forcing, it follows that for any such u
[TABLE]
for some subspaces WIβ(u)βFI not depending on r and of small dimension. Since any element of Fn1ββW{3}β(u)+W{1}β(u)βFn3β has small partition rank, it follows that for almost every uβU,
[TABLE]
where s(u) is a tensor of small partition rank.
Define a sequence 0=Z(0)βZ(1)ββ―βZ(m)βF{1,3} of subspaces recursively as follows. Given Z(j), if there is some rβR such that r4βu is far from Z(j) for many uβU, then set Z(j+1)=Z(j)+K1,3β(r). What we mean by r4βu being far from Z(j) is that there is no zβZ(j) such that r4βuβz has small partition rank. For suitably chosen parameters, one can show that this procedure cannot go on for too long, ie. that for some not too large m we have that for every rβR, for almost all uβU there is some zβZ(m) with r4βuβz having small partition rank.
Now let rβR. Let X(r) be the set consisting of those xβK{1,3}β(r) which are close to Z(m). Then r4βuβX(r) for almost every uβU. Let t1β,β¦,tΞ±β be a maximal linearly independent subset of X(r) and extend it to a basis t1β,β¦,tΞ±β,t1β²β,β¦,tΞ²β²β for K{1,3}β(r). Now if a linear combination of t1β,β¦,tΞ±β,t1β²β,β¦,tΞ²β²β is in X(r), then the coefficients of t1β²β,β¦,tΞ²β²β are all zero. Write r4β=βiβ€Ξ±βsiββtiβ+βjβ€Ξ²βsjβ²ββtjβ²β for some siβ,sjβ²ββFn2β. Since r4βuβX(r) for almost all uβU, we have, for all j, that sjβ²β.u=0 for almost all uβU. Since these hold for more than half of uβU, we obtain sjβ²ββUβ₯ for every j, therefore βjβ€Ξ²βsjβ²ββtjβ²ββUβ₯βF{1,3}.
Since tiββX(r) for every i, we may choose ziββZ(m) such that tiβ=ziβ+yiβ where yiββF{1,3} has small partition rank. Now βiβ€Ξ±βsiββtiββFn2ββZ(m)+βiβ€Ξ±βsiββyiβ. Moreover, as Ξ± is small and each yiβ has small partition rank, we have βiβ€Ξ±βsiββyiββL{1,2}β²β(r)βFn3β for some small L{1,2}β²β(r)βF{1,2}. So we have proved (2) with V{2}β=Uβ₯ and V{1,3}β=Z(m).
2.3.3 Why can we find such a Q{2}β inside 23d+3Bβ²β23d+3Bβ²?
Now we describe why there must exist Q{2}β with elements chosen from 233+3Bβ²β233+3Bβ² and having the required properties. We remark that in the general case this is done in Lemma 2.14. We want to find a subspace UβFn2β of low codimension, and forcing multisets QuββF{1,3} (uβU) consisting of pure tensors such that for every uβU, uβQuββ233+3Bβ²β233+3Bβ². Let D be the multiset {vβw:vβFn1β,wβFn3β}. Notice that if some set R is dense in D, then by the induction hypothesis we can find a forcing set in 232+3Rβ232+3R consisting of pure tensors. Therefore it is enough to find a low codimensional subspace U and dense sets RuββD (for every uβU) such that uβRuββ32Bβ²β32Bβ². As Bβ² is dense in B, we have a dense subset SβFn2β and dense subsets TsββD (sβS) such that sβTsββBβ² for every sβS. By Bogolyubovβs lemma (Lemma 2.1), there is a low codimensional subspace U contained in 2Sβ2S. To establish the existence of a dense RuββD with uβRuββ32Bβ²β32Bβ² for every uβU, it is enough to prove the following lemma.
Lemma 2.5**.**
Let T1β,T2β,T3β,T4β be dense subsets of D. Then Dβ©βiβ€4β(8Tiββ8Tiβ) is dense in D.
Indeed, once we have this lemma, it follows that for any s1β,s2β,s3β,s4ββS, the set Dβ©βiβ€4β(8Tsiβββ8Tsiββ) is dense in D. But if uβU, then we can write u=s1β+s2ββs3ββs4β for some siββS, and then uββiβ€4β(8Tsiβββ8Tsiββ)βs1βββiβ€4β(8Tsiβββ8Tsiββ)+s2βββiβ€4β(8Tsiβββ8Tsiββ)βs3βββiβ€4β(8Tsiβββ8Tsiββ)βs4βββiβ€4β(8Tsiβββ8Tsiββ)β32Bβ²β32Bβ².
Lemma 2.5 follows easily from the next two lemmas.
Lemma 2.6**.**
Let A be a dense subset of D. Then there exist a dense subspace VβFn1β and for each vβV a dense subspace WvββFn3β such that vβWvββ8Aβ8A for every vβV.
Proof.
There exist a dense subset BβFn1β and dense subsets CbββFn3β for each bβB such that bβCbββA. By Bogolyubovβs lemma, 2Bβ2B contains a dense subspace VβFn1β, and for every bβB, 2Cbββ2Cbβ contains a dense subspace LbββFn3β. For any vβV, choose b1β,b2β,b3β,b4ββB with v=b1β+b2ββb3ββb4β and set Wvβ=βiβ€4βLbiββ. Note that biββwβ2Aβ2A for every iβ€4 and wβWvβ, therefore vβwβ8Aβ8A.
β
Lemma 2.7**.**
Suppose that we have dense subspaces V,Vβ²βFn1β, for each vβV a dense subspace WvββFn3β, and for each vβ²βVβ² a dense subspace Wvβ²β²ββFn3β. Then (βvβVβvβWvβ)β©(βvβ²βVβ²βvβ²βWvβ²β²β)=βvβVβ©Vβ²βvβ(Wvββ©Wvβ²β). In particular, this intersection is a dense subset of D.
Proof.
The identity is trivial. Since the subspaces Vβ©Vβ² and Wvββ©Wvβ²β are dense, the second assertion follows.
β
2.3.4 How can this be extended to d>3?
Now we briefly sketch what the main difficulties are in the d>3 case and how we can address them. The underlying strategy is similar: we take an ordering βΊ of the set of non-empty subsets Iβ[dβ1], and for each such I we choose QIβ such that any array
[TABLE]
with r.q=0 for almost all qβQIβ has
[TABLE]
where UJβ,UJcβ,KJcβ(r) can have dimension slightly larger than those of WJβ,WJcβ and HJcβ, but they are still low dimensional. In the d=3 case, we have made use of a decomposition r=r2β+r3β+r4β where r4ββFIβHIcβ(r), r2βu has small partition rank and r3βu is in a small subspace independent of r for every uβFI. In general, such a decomposition need not exist. For example, when d=4 and I={1,2}, then an array in W{1}ββF{2,3,4} (or in Fn1ββH{2,3,4}β(r) if we were to take {1,2}βΊ{1}), when multiplied by some pure tensor uβF{1,2}, yields a tensor which need not have small partition rank and need not lie a small space independent of r. However, by restricting the possible choices for u, we can make sure that the product is always zero. So we will take a decomposition r=r1β+r2β+r3β+r4β such that r4ββFIβHIcβ(r); for every pure tensor uβFI, r2βu has small partition rank and r3βu lies in a small space depending only on u; and crucially, for every qβQIβ, r1β.q=0. To achieve this, we need to insist that JβΊI whenever JβI and that QIβ is orthogonal to certain subspaces. To see this, note that in the above example where d=4 and I={1,2} we need that {1}βΊ{1,2} and Q{1,2}β is orthogonal to W{1}ββF{2,3,4}. (If we had {1,2}βΊ{1}, then in (4) we would have a term Fn1ββH{2,3,4}β(r) rather than W{1}ββF{2,3,4}, which we could not control.)
We also need to generalise Lemma 2.5 to the case d>3. Instead of using βvβVβvβWvβ as in Lemma 2.6, we need to define an object in B such that
-
an instance of the object can be found in kBβ²βkBβ² for some small k whenever Bβ² is dense in B (generalising Lemma 2.6)
2. 2.
the intersection of few instances of this object is a dense subset of B (generalising Lemma 2.7)
In the next subsection we describe this object and show that it has the required properties.
2.4 Construction of some auxiliary sets
Definition 2.8**.**
Suppose that we have a collection of vector spaces as follows. The first one is UβFn1β, of codimension at most l. Then, for every u1ββU, there is some Uu1βββFn2β. In general, for every 2β€kβ€d and every u1ββU,u2ββUu1ββ,β¦,ukβ1ββUu1β,β¦,ukβ2ββ, there is a subspace Uu1β,β¦,ukβ1βββFnkβ. Assume, in addition, that the codimension of Uu1β,β¦,ukβ1ββ in Fnkβ is at most l for every u1ββU,β¦,ukβ1ββUu1β,β¦,ukβ2ββ. Then the multiset Q={u1βββ―βudβ:u1ββU,β¦,udββUu1β,β¦,udβ1ββ} is called an l-system.
The next lemma is the generalisation of Lemma 2.7 from the previous subsection.
Lemma 2.9**.**
Let Q be an l-system and let Qβ² be an lβ²-system. Then Qβ©Qβ² contains an (l+lβ²)-system.
Proof.
Let Q have spaces as in Definition 2.8 and let Qβ² have spaces Uu1β²β,β¦,ukβ1β²ββ²β.
We define an (l+lβ²)-system P contained in Qβ©Qβ² as follows. Let V=Uβ©Uβ². Suppose we have defined Vv1β,β¦,vjβ1ββ for all jβ€k. Let v1ββV,v2ββVv1ββ,β¦,vkβ1ββVv1β,β¦,vkβ2ββ. We let Vv1ββ¦,vkβ1ββ=Uv1ββ¦,vkβ1βββ©Uv1ββ¦,vkβ1ββ²β. This is well-defined and has codimension at most l+lβ² in Fnkβ. Let P be the (l+lβ²)-system with spaces Vv1β,β¦,vkβ1ββ.
β
The next lemma is the generalisation of Lemma 2.6 from the previous subsection.
Lemma 2.10**.**
Let Bβ²βB be a multiset such that β£Bβ²β£β₯Ξ΄β£Bβ£. Then there exists an f1β-system whose elements are chosen from f2βBβ²βf2βBβ² with f1β=Cβ
4d(log(2d/Ξ΄))4 and f2β=4d.
Proof.
The proof is by induction on d. The case d=1 is a direct consequence of Lemma 2.1. Suppose that the lemma has been proved for all dβ²<d and let Bβ²βB be a multiset such that β£Bβ²β£β₯Ξ΄β£Bβ£. Let D be the multiset {v2βββ―βvdβ:v2ββFn2β,β¦,vdββFndβ}. For each uβFn1β, let Buβ²β={sβD:uβsβBβ²} and let T={uβFn1β:β£Buβ²ββ£β₯2Ξ΄ββ£Dβ£}. By averaging, we have that β£Tβ£β₯2Ξ΄ββ£Fn1ββ£. Now by the induction hypothesis, for every tβT, there exists a g1β-system in Fn2βββ―βFndβ (whose definition is analogous to the definition of a system in Fn1βββ―βFndβ), called Ptβ, contained in g2βBtβ²ββg2βBtβ²β where g1β=Cβ
4dβ1(log(2d/Ξ΄))4 and g2β=4dβ1. By Lemma 2.1, 2Tβ2T contains a subspace UβFn1β of codimension at most C(log(2/Ξ΄))4. For each uβU, write u=t1β+t2ββt3ββt4β arbitrarily with tiββT, and let Quβ=Pt1βββ©Pt2βββ©Pt3βββ©Pt4ββ, which is a g3β-system with g3β=4g1β=Cβ
4d(log(2d/Ξ΄))4, by Lemma 2.9. Thus, Q=βuβUβ(uβQuβ) is indeed an f1β-system. Moreover, for any uβU,sβQuβ, we have uβs=t1ββs+t2ββsβt3ββsβt4ββs for some tiββT and sββiβ€4βPtiββ. Then tiββsβg2βBβ²βg2βBβ², therefore uβsβ4g2βBβ²β4g2βBβ², so the elements of Q are indeed chosen from f2βBβ²βf2βBβ².
β
The next lemma describes a property of systems which was not needed for us in the d=3 case, but is crucial in the general case. It is required for finding a suitable decomposition r=r1β+r2β+r3β+r4β described at the end of the previous subsection. Indeed, we need a set QIβ which is orthogonal to certain spaces of the form WJββFJc (ie. is contained in WJβ₯ββFJc) to make sure that r1β.q=0 for every qβQIβ. We will use the following lemma to guarantee the existence of such a set QIβ.
Lemma 2.11**.**
Let Q be a k-system and for every non-empty Iβ[d], let LIββFI be a subspace of codimension at most l. Let T=βIβ(LIββFIc). Then Qβ©T contains an f-system for f=k+2dl.
Proof.
Let the spaces of Q be Uu1β,β¦,ujβ1ββ. It suffices to prove that for every 1β€jβ€d, and every u1ββU,β¦,ujβ1ββUu1β,β¦,ujβ2ββ, the codimension of (u1βββ―βujβ1ββUu1β,β¦,ujβ1ββ)β©βIβ[j],jβIβ(LIββF[j]βI) in u1βββ―βujβ1ββUu1β,β¦,ujβ1ββ is at most 2dl. Thus, it suffices to prove that for every Iβ[j] with jβI, the codimension of (u1βββ―βujβ1ββUu1β,β¦,ujβ1ββ)β©(LIββF[j]βI) in u1βββ―βujβ1ββUu1β,β¦,ujβ1ββ is at most l. But this is equivalent to the statement that \big{(}(\bigotimes_{i\in I\setminus\{j\}}u_{i})\otimes U_{u_{1},\dots,u_{j-1}}\big{)}\cap L_{I} has codimension at most l in (β¨iβIβ{j}βuiβ)βUu1β,β¦,ujβ1ββ, which clearly holds.
β
2.5 The proof of Lemma 2.2
We now turn to the proof of Lemma 2.2. As described in the outline, the first step is to find a Q[d]β such that if r.q=0 for almost all qβQ[d]β, then r=x+y where xβV[d]β for a small space V[d]β independent of r, and y has low partition rank.
Lemma 2.12**.**
Let dβ₯2 and suppose that Lemma 2.2 has been proved for dβ²=dβ1. Let Bβ²βB be such that β£Bβ²β£β₯Ξ΄β£Bβ£ for some Ξ΄>0. Then there exist some Qβ2Bβ²β2Bβ² consisting of pure tensors and a subspace V[d]ββF[d] of dimension at most 4C(log(2/Ξ΄))4 with the following property. Any array r with r.q=0 for at least 87ββ£Qβ£ choices qβQ can be written as r=x+y where xβV[d]β and y is f-degenerate for f=G(dβ1,4β£Fβ£4C(log2/Ξ΄)4Ξ΄β).
Proof.
Let D be the multiset {u1βββ―βudβ1β:u1ββFn1β,β¦,udβ1ββFndβ1β} and let Dβ²={tβD:tβuβBβ²Β forΒ atΒ leastΒ 2Ξ΄ββ£Fβ£ndβΒ choicesΒ uβFndβ}. Clearly, we have β£Dβ²β£β₯2Ξ΄ββ£Dβ£. Moreover, by Lemma 2.1, for every tβDβ², there exists a subspace UtββFndβ of codimension at most C(log(2/Ξ΄))4 such that tβUtββ2Bβ²β2Bβ². After passing to suitable subspaces, we may assume that all Utβ have the same codimension kβ€C(log(2/Ξ΄))4. Now let Q=βͺtβDβ²β(tβUtβ).
Write R for the set of arrays r with r.q=0 for at least 87ββ£Qβ£ choices qβQ.
We now define a sequence of subspaces 0=V(0)βV(1)ββ―βV(m)βF[d] recursively as follows.
Given V(j), if for every rβR there are at least 2β£Dβ²β£β choices tβDβ² with rtβV(j)t, then we set m=j and terminate. (Here and below, for a subspace LβG and an array sβFI, we write Ls for the subspace {rs:rβL}βFIc.)
Else, we choose some rβR such that there are at most 2β£Dβ²β£β choices tβDβ² with rtβV(j)t. We set V(j+1)=V(j)+span(r). Note that r.(tβs)=(rt).s for every sβUtβ. If rtξ βUtβ₯β, then (rt).s=0 holds for only a proportion 1/β£Fβ£β€1/2 of all sβUtβ. Thus, as rβR, we have rtβUtβ₯β for at least 43ββ£Dβ²β£ choices tβDβ². Moreover, since rtβV(j)t holds for at most 2β£Dβ²β£β choices tβDβ², it follows that for at least 4β£Dβ²β£β choices tβDβ² we have rtβUtβ₯ββV(j)t. Thus, we have dim(Utβ₯ββ©V(j+1)t)>dim(Utβ₯ββ©V(j)t) for at least 4β£Dβ²β£β choices tβDβ².
However, for any j we have βtβDβ²βdim(Utβ₯ββ©V(j)t)β€βtβDβ²βdimUtβ₯ββ€Cβ£Dβ²β£(log(2/Ξ΄))4. Thus, we get mβ€4C(log(2/Ξ΄))4. Set V[d]β=V(m). Then dimV[d]ββ€4C(log(2/Ξ΄))4, as claimed.
Now let rβR be arbitrary. By definition, there are at least β£Dβ²β£/2 choices tβDβ² with rtβV[d]βt. Then there is some vβV[d]β such that rt=vt for at least 2β£V[d]ββ£β£Dβ²β£β choices tβDβ², and hence also for at least 4β£V[d]ββ£Ξ΄β£Dβ£β choices tβD. Note that 4β£V[d]ββ£Ξ΄ββ₯4β£Fβ£4C(log2/Ξ΄)4Ξ΄β, therefore by Lemma 2.4, rβv is f-degenerate.
β
Definition 2.13**.**
Let k be a positive integer and let 0β€Ξ±β€1. Let Q be a multiset with elements chosen from G (with arbitrary multiplicity). We say that Q is (k,Ξ±)-forcing if the set of all arrays rβG with r.q=0 for at least Ξ±β£Qβ£ choices qβQ is contained in a set of the from βIβ[d],Iξ =β
βVIββFIc for some VIββFI of dimension at most k.
We now turn to the main part of the proof of Lemma 2.2. For each non-empty Iβ[dβ1] we will construct QIβ as defined in the next result, and (roughly) we will take Q=Q[d]ββͺβIβ[dβ1],Iξ =β
βQIβ, where Q[d]β is provided by Lemma 2.12. The properties that QIβ has are generalisations of the properties that Q{2}β had in Subsection 2.3. Accordingly, the next lemma is the generalisation of the discussion in Subsubsection 2.3.3.
Lemma 2.14**.**
Let dβ₯2 and suppose that Lemma 2.2 has been proved for every dβ²<d. Let Bβ²βB have β£Bβ²β£β₯Ξ΄β£Bβ£ for some 0<Ξ΄β€1/2. Let kβ₯G(dβ1,Ξ΄) be arbitrary, let Iβ[dβ1],Iξ =β
, and let WJββFJ be subspaces of dimension at most k for every JβI,Jξ =I,Jξ =β
. Then there exist a multiset Qβ², and a multiset Qsβ for each sβQβ² with the following properties.
- (1)
The elements of Qβ² are pure tensors chosen from βJβI,Jξ =I,Jξ =β
β(WJβ₯ββFIβJ)βFI
2. (2)
Qβ²* is (f1β,1βf2β)-forcing with f1β=G(β£Iβ£,β£Fβ£β2d+1dk), f2β=2β3d+2*
3. (3)
For each sβQβ², the elements of Qsβ are pure tensors chosen from FIc
4. (4)
For each sβQβ², Qsβ is (f3β,1βf4β)-forcing with f3β=G(dββ£Iβ£,β£Fβ£β23d+4C(log(2dβ1/Ξ΄))4), f4β=2β3d+2
5. (5)
maxsβQβ²ββ£Qsββ£β€2minsβQβ²ββ£Qsββ£**
6. (6)
The elements of the multiset QIβ:={sβt:sβQβ²,tβQsβ}=βsβQβ²β(sβQsβ) are chosen from f5βBβ²βf5βBβ² with f5β=23d+3.
Proof.
By symmetry, we may assume that I=[a] for some 1β€aβ€dβ1. Let C be the multiset {u1βββ―βuaβ:uiββFniβ} and let D be the multiset {ua+1βββ―βudβ:uiββFniβ}. For each sβC, let Dsβ={tβD:sβtβBβ²}. Also, let Cβ²={sβC:β£Dsββ£β₯2Ξ΄ββ£Dβ£}. Clearly, β£Cβ²β£β₯2Ξ΄ββ£Cβ£. By Lemma 2.10, there exists a g1β-system R (with respect to FI) with elements chosen from g2βCβ²βg2βCβ² with g1β=Cβ
4d(log(2dβ1/Ξ΄))4 and g2β=4d. By Lemma 2.11, Rβ©βJβI,Jξ =I,Jξ =β
β(WJβ₯ββFIβJ) contains a g3β-system Tβ² for g3β=Cβ
4d(log(2dβ1/Ξ΄))4+2dk. Now β£Tβ²β£β₯β£Fβ£βdg3ββ£Cβ£. By Lemma 2.2 (applied to a in place of d), it follows that there exists a multiset Qβ² whose elements are pure tensors chosen from g4βTβ²βg4βTβ² and which is (g5β,1βg6β)-forcing for g4β=23a+3β€23d+2, g5β=G(a,β£Fβ£βdg3β) and g6β=2β3a+3β₯2β3d+2. Note that since Ξ΄β€1/2, we have Cβ
4d(log(2dβ1/Ξ΄))4=Cβ
4d(dβ1+log(1/Ξ΄))4β€Cβ
4d(dlog(1/Ξ΄))4. But this is at most as G(dβ1,Ξ΄)β€k, so g3ββ€2β
2dk, therefore Qβ² satisfies (1) and (2) in the statement of this lemma.
By Lemma 2.10, for each sβCβ² there exists a g7β-system Rsβ (with respect to FIc) contained in g8βDsββg8βDsβ, where g7β=Cβ
4d(log(2dβ1/Ξ΄))4 and g8β=4d. For every sβQβ², choose s1β,β¦,sl+lβ²ββCβ² with l,lβ²β€23d+3 such that s=s1β+β―+slββsl+1βββ―βsl+lβ²β (this is possible, since the elements of Qβ² are chosen from 2g2βg4βCβ²β2g2βg4βCβ² and 2g2βg4ββ€23d+3), and let Psβ=βiβ€l+lβ²βRsβ. By Lemma 2.9, Psβ contains a g9β-system with g9β=2β
23d+3β
Cβ
4d(log(2dβ1/Ξ΄))4, therefore β£Psββ£β₯g10ββ£Dβ£ for g10β=β£Fβ£βdg9ββ₯β£Fβ£β23d+4C(log(2dβ1/Ξ΄))4. By Lemma 2.2 (applied to dβa in place of d), for every sβQβ² there exists a multiset Qsβ consisting of pure tensors with elements chosen from g11βPsββg11βPsβ which is (g12β,1βg13β)-forcing for g11β=23dβa+3β€23d+2, g12β=G(dβa,β£Fβ£βdg9β)β€G(dβa,β£Fβ£β23d+4C(log(2dβ1/Ξ΄))4) and g13β=2β3dβa+3β₯2β3d+2. Notice that if we repeat every element of Qsβ the same number of times, then the multiset obtained is still (g12β,1βg13β)-forcing, so we may assume that maxsβQβ²ββ£Qsββ£β€2minsβQβ²ββ£Qsββ£. Thus, the Qsβ satisfy (3), (4) and (5).
Define QIβ={sβt:sβQβ²,tβQsβ}=βsβQβ²β(sβQsβ). Note that as Rsββg8βDsββg8βDsβ for all sβCβ², we have sβRsββg8βBβ²βg8βBβ² for all sβCβ². But the elements of Qβ² are chosen from 2g2βg4βCβ²β2g2βg4βCβ², so sβPsββ4g2βg4βg8βBβ²β4g2βg4βg8βBβ² for all sβQβ². Finally, the elements of Qsβ are chosen from g11βPsββg11βPsβ, so the elements of sβQsβ are chosen from 8g2βg4βg8βg11βBβ²β8g2βg4βg8βg11βBβ² for every sβQβ². Since 8g2βg4βg8βg11ββ€8β
(4d)2β
(23d+2)2=23+4d+2β
3d+2β€23d+3, property (6) is satisfied.
β
The next lemma is the last ingredient of the proof. It is a generalisation of the discussion in Subsubsection 2.3.2. Given a tensor rβV[d]β+βIβ[dβ1],Iξ =β
βFIβHIcβ(r), we turn the terms FIβHIcβ(r) one by one into terms VIββFIc+FIβVIcβ where VJβ are small and do not depend on r. (Note that this is not quite the same as our approach to the case d=3.) As briefly explained in Subsubsection 2.3.4, the order in which the various I are considered is important: we define βΊ to be any total order on the set of non-empty subsets of [dβ1] such that if JβI then JβΊI. It is worth noting that unlike in the d=3 case, the subspaces VJβ,VJcβ with JβΊI are allowed to change when VIβ and VIcβ get defined (although in fact the VJcβ will not change, and the VJβ change only for JβI). All we require is that they do not become much larger.
Lemma 2.15**.**
Let dβ₯2, 0<Ξ΄β€1/2 and kβ₯G(dβ1,Ξ΄)2. Let Iβ[dβ1],Iξ =β
and let WJββFJ,WJcββFJc be subspaces of dimension at most k for every JβΊI. Moreover, let W[d]ββF[d] have dimension at most k. Suppose that Qβ²,Qsβ (and QIβ) have the six properties described in Lemma 2.14. Then any array
[TABLE]
with dim(HJcβ(r))β€k and the property that r.q=0 for at least (1β41β(2β3d+2)2)β£QIββ£ choices qβQIβ is contained in
[TABLE]
for some UJββFJ,UJcββFJc not depending on r and some KJcβ(r)βFJc possibly depending on r, all of dimension at most k2c2β(β£Iβ£).
Proof.
By (4) in Lemma 2.14, for every sβQβ² there exist subspaces VJβ(s)βFJ for every JβIc,Jξ =β
, with dimension at most
g1β=G(dβ1,β£Fβ£β23d+4C(log2dβ1/Ξ΄)4)
such that the set of arrays tβFIc with t.q=0 for at least (1βg2β)β£Qsββ£ choices qβQsβ is contained in βJβIc,Jξ =β
βVJβ(s)βFIcβJ, where g2β=2β3d+2. Note, for future reference, that
[TABLE]
Let R consist of the set of arrays with rβW[d]β+βJβΊIβ(WJββFJc+FJβWJcβ)+βJβͺ°IβFJβHJcβ(r) with dim(HJcβ(r))β€k and the property that r.q=0 for at least (1β41β(2β3d+2)2)β£QIββ£ choices qβQIβ.
Let rβR. Then by averaging and using (5) from Lemma 2.14, for at least (1βg3β)β£Qβ²β£ choices sβQβ² we have r.(sβt)=0 for at least (1βg2β)β£Qsββ£ choices tβQsβ, where g3β=21β2β3d+2. Thus, (noting that r.(sβt)=(rs).t), rsββJβIc,Jξ =β
βVJβ(s)βFIcβJ holds for at least (1βg3β)β£Qβ²β£ choices sβQβ². Let Qβ²(r) be the submultiset of Qβ² consisting of those sβQβ² for which rsββJβIc,Jξ =β
βVJβ(s)βFIcβJ. Then we have β£Qβ²(r)β£β₯(1βg3β)β£Qβ²β£.
Note that we can write r=r1β+r2β+r3β+r4β where
[TABLE]
[TABLE]
[TABLE]
[TABLE]
By (1) in Lemma 2.14, the elements of Qβ² belong to βJβI,Jξ =I,Jξ =β
β(WJβ₯ββFIβJ), so we have r1βs=0 for every sβQβ².
Note that for every pure tensor sβFI, r2βs is 2dk-degenerate. Indeed, for any Jβ[dβ1] with Jξ βI there are some s1ββFIβ©J,s2ββFIβ©Jc with s=s1ββs2β. Then (WJββFJc)sβ(WJβs1β)βFIcβJ. Since dim(WJβs1β)β€k, Jξ βI and dβIcβJ, any tensor in (WJβs1β)βFIcβJ is k-degenerate. Similarly, any tensor in (FJβWJcβ)s or (FJβHJcβ(r))s is also k-degenerate, so r2βs is indeed 2dk-degenerate. Since Qβ² consists of pure tensors, this holds for every sβQβ².
Also, r3βsββJβI,Jξ =Iβ((FJβWJcβ)s). It follows that for every sβQβ²(r), there exists some t(s)βVIcβ(s)+βJβI,Jξ =Iβ((FJβWJcβ)s) such that r4βsβt(s) is g4β-degenerate for g4β=g1β+2dk (we have used that dim(VJβ(s))β€g1β). To ease the notation, write T(s) for the space VIcβ(s)+βJβI,Jξ =Iβ((FJβWJcβ)s). We claim that the dimension of T(s) is at most g4β=g1β+2dk. Indeed, dim(VIcβ)β€g1β, so it suffices to prove that dim((FJβWJcβ)s)β€k for every JβI,Jξ =I. Since sβQβ², s is a pure tensor, so for any such J we have s=s1ββs2β for some s1ββFJ,s2ββFIβJ. But then (FJβWJcβ)sβWJcβs2β, which has dimension at most dim(WJcβ)β€k.
Let us define a sequence of subspaces 0=Z(0)βZ(1)ββ―βZ(m)βFIc recursively as follows. Given Z(j), if for all rβR we have that for all but at most 2g3ββ£Qβ²β£ choices sβQβ² there is some zβZ(j) such that r4βsβz is (g4β+1)g4β-degenerate, then set m=j and terminate.
Else, choose some rβR such that for at least 2g3ββ£Qβ²β£ choices sβQβ² there is no zβZ(j) such that r4βsβz is (g4β+1)g4β-degenerate, and set Z(j+1)=Z(j)+HIcβ(r). Recall that for every sβQβ²(r), and in particular, for at least (1βg3β)β£Qβ²β£ choices sβQβ², there exists some t(s)βT(s) such that r4βsβt(s) is g4β-degenerate. So for at least g3ββ£Qβ²β£ choices sβQβ² there is some t(s)βT(s) such that r4βsβt(s) is g4β-degenerate, but there is no zβZ(j) such that r4βsβz is (g4β+1)g4β-degenerate. In this case there is no zβZ(j) such that zβt(s) is g42β-degenerate. On the other hand, since r4βsβHIcβ(r)βZ(j+1), there is some zβZ(j+1) such that zβt(s) is g4β-degenerate. For any i, let K(i,s) be the subspace of T(s) spanned by those tβT(s) for which there is some zβZ(i) with zβt being g4β-degenerate. Since the dimension of T(s) is at most g4β, we have t(s)ξ βK(j,s), else there would exist some zβZ(j) such that zβt(s) is g42β-degenerate. On the other hand, t(s)βK(j+1,s). Thus, dimK(j+1,s)>dimK(j,s). This holds for at least g3ββ£Qβ²β£ choices sβQβ², so
[TABLE]
Since K(m,s)βT(s), we have dimK(m,s)β€g4β. Thus,
[TABLE]
so mβ€g3βg4ββ and dimZ(m)β€g3βkg4ββ. Write Z=Z(m).
Now let rβR. Let X(r) be the set consisting of those xβHIcβ(r) for which there is some zβZ with xβz being (g4β+1)g4β-degenerate. Then r4βsβX(r) apart from at most 2g3ββ£Qβ²β£ choices sβQβ². Let t1β,β¦,tΞ±β be a maximal linearly independent subset of X(r) and extend it to a basis t1β,β¦,tΞ±β,t1β²β,β¦,tΞ²β²β for HIcβ(r). Now if a linear combination of t1β,β¦,tΞ±β,t1β²β,β¦,tΞ²β²β is in X(r), then the coefficients of t1β²β,β¦,tΞ²β²β are all zero. Write r4β=βiβ€Ξ±βsiββtiβ+βjβ€Ξ²βsjβ²ββtjβ²β for some siβ,sjβ²ββFI. Since r4βqβX(r) for at least (1β2g3β)β£Qβ²β£=(1β2β3d+2)β£Qβ²β£ choices qβQβ², we have, for all j, that sjβ²β.q=0 for at least (1β2β3d+2)β£Qβ²β£ choices qβQβ². Thus, by (2) in Lemma 2.14 there exist subspaces LJββFJ (JβI,Jξ =β
) not depending on r, and of dimension at most G(β£Iβ£,β£Fβ£β2d+1dk) such that sjβ²βββJβI,Jξ =β
βLJββFIβJ for all j. Thus, r4βββiβ€Ξ±βsiββtiβ+βJβI,Jξ =β
βLJββFJc. Moreover, for every iβ€Ξ±, we have tiββX(r), so there exist ziββZ such that tiββziβ is (g4β+1)g4β-degenerate. It follows that r4ββFIβZ+βJβI,Jξ =I,Jβ[dβ1]βFJβKJcβ²β(r)+βJβI,Jξ =β
βLJββFJc for some KJcβ²β(r)βFJc of dimension at most Ξ±β
(g4β+1)g4ββ€kβ
(g4β+1)g4β.
We claim that dim(Z),dim(KJcβ²β) and dim(LJβ) are all bounded by k2c2β(β£Iβ£)βk.
Firstly, note that g4β=g1β+2dkβ€k2+2dkβ€2k2.
Now dim(KJcβ²β)β€k(g4β+1)g4ββ€k6β€k2c2β(β£Iβ£)βk. Also, dim(Z)β€g3βkg4βββ€k4β€k2c2β(β£Iβ£)βk. Finally,
[TABLE]
This completes the proof of the claim and the lemma.
β
Proof of Lemma 2.2.
As stated earlier, the proof goes by induction on d. For d=1, by Lemma 2.1 there is a subspace UβFn1β of codimension at most C(log1/Ξ΄)4 contained in 2Bβ²β2Bβ². Choose Q=U. Now if r.q=0 for at least (1β2β34)β£Qβ£ choices qβQ then the same holds for all qβQ, therefore rβUβ₯, but dim(Uβ₯)β€C(log1/Ξ΄)4, so the case d=1 is proved.
Now let us assume that dβ₯2. Extend the total order βΊ defined above such that it now contains β
which has β
βΊI for every non-empty Iβ[dβ1]. Say β
=I0ββΊI1ββΊI2ββΊβ―βΊI2dβ1β1β where {I0β,β¦,I2dβ1β1β}=P([dβ1]).
Claim. For every 0β€iβ€2dβ1β1 there exists a multiset QIiββ of pure tensors with elements chosen from 23d+3Bβ²β23d+3Bβ², and subspaces WIjββ(i)βFIjβ, W(Ijβ)cβ(i)βF(Ijβ)c for every jβ€i (for j=0, we only require W[d]β(i) and not Wβ
β(i)) with the following properties. The dimension of each of these spaces is at most g1β(i)=G(dβ1,Ξ΄)Ξ±(i), where Ξ±(i)=4β
Ξ 1β€jβ€iβ2c2β(β£Ijββ£)
. Moreover, if rβG has r.q=0 for at least (1β41β(2β3d+2)2)β£QIjβββ£ choices qβQIjββ for all jβ€i, then rβW[d]β(i)+β1β€jβ€iβ(WIjββ(i)βF(Ijβ)c+FIjββW(Ijβ)cβ(i))+βj>iβFIjββH(Ijβ)cβ(i,r) holds for some H(Ijβ)cβ(i,r) possibly depending on r and of dimension at most g1β(i).
Proof of Claim. This is proved by induction on i. For i=0, by Lemma 2.12, there exist Qβ
ββ2Bβ²β2Bβ² consisting of pure tensors and V[d]ββF[d] of dimension at most 4C(log(2/Ξ΄))4β€4C(2log(1/Ξ΄))4β€G(dβ1,Ξ΄)4 such that if r.q=0 for at least 87ββ£Qβ
ββ£ choices qβQβ
β, then r can be written as r=x+y where xβV[d]β and y is g2β-degenerate for g2β=G(dβ1,4β£Fβ£4C(log2/Ξ΄)4Ξ΄β). Since
[TABLE]
we can take W[d]β(0)=V[d]β.
Once we have found suitable sets WIjββ(iβ1) and W(Ijβ)cβ(iβ1) for all jβ€iβ1, we can apply Lemmas 2.14 and 2.15 with I=Iiβ and k=g1β(iβ1) to find a suitable QIiββ, WIjββ(i) and W(Ijβ)cβ(i) for all jβ€i, and the claim is proved, since g1β(i)=g1β(iβ1)2c2β(β£Iiββ£).
Now, after taking several copies of each QIβ, we may assume that additionally maxIββ£QIββ£β€2minIββ£QIββ£. Let Q=βIβ[dβ1]βQIβ and suppose that r.q=0 for at least (1β2β3d+3)β£Qβ£ choices qβQ. Since 2β3d+3β€2β
2dβ11ββ
41β(2β3d+2)2, it follows that for every Iβ[dβ1] we have r.q=0 for at least (1β41β(2β3d+2)2)β£QIββ£ choices qβQIβ. By the Claim with i=2dβ1β1, we get that rββIβ[d],Iξ =β
βVIββFIc for some VIββFI not depending on r, and of dimension at most g1β(2dβ1β1)=G(dβ1,Ξ΄)Ξ±(2dβ1β1). Note that
[TABLE]
But
[TABLE]
Thus, Ξ±(2dβ1β1)β€4dd.
This completes the proof of the lemma.
β
Acknowledgments
I would like to thank Timothy Gowers for helpful discussions. I am also grateful to him and the anonymous referee for their valuable comments on a previous version of this paper.