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HomeMathNotes on inverse theorem entropy

Notes on inverse theorem entropy

Let {G} be a finite set of order {N}; in purposes {G} will probably be sometimes one thing like a finite abelian group, such because the cyclic group {{bf Z}/N{bf Z}}. Allow us to outline a {1}-bounded perform to be a perform {f: G rightarrow {bf C}} such that  leq 1 for all {n in G}. There are a lot of seminorms of curiosity that one locations on capabilities {f: G rightarrow {bf C}} which can be bounded by {1} on {1}-bounded capabilities, such because the Gowers uniformity seminorms _k for {k geq 1} (that are real norms for {k geq 2}). All seminorms on this publish will probably be implicitly assumed to obey this property.

In additive combinatorics, a big function is performed by inverse theorems, which abstractly take the next type for sure decisions of seminorm , some parameters {eta, varepsilon>0}, and a few class {{mathcal F}} of {1}-bounded capabilities:

Theorem 1 (Inverse theorem template) If {f} is a {1}-bounded perform with  geq eta, then there exists {F in {mathcal F}} such that  geq varepsilon, the place {langle,rangle} denotes the standard interior product

displaystyle  langle f, F rangle := {bf E}_{n in G} f(n) overline{F(n)}.

Informally, one ought to consider {eta} as being considerably small however fastened independently of {N}, {varepsilon} as being considerably smaller however relying solely on {eta} (and on the seminorm), and {{mathcal F}} as representing the “structured capabilities” for these decisions of parameters. There may be some flexibility in precisely how to decide on the category {{mathcal F}} of structured capabilities, however intuitively an inverse theorem ought to turn out to be extra highly effective when this class is small. Accordingly, allow us to outline the {(eta,varepsilon)}-entropy of the seminorm to be the least cardinality of {{mathcal F}} for which such an inverse theorem holds. Seminorms with low entropy are ones for which inverse theorems will be anticipated to be a great tool. This idea arose in some discussions I had with Ben Inexperienced a few years in the past, however by no means appeared in print, so I made a decision to report some observations we had on this idea right here on this weblog.

Lebesgue norms {| f|_{L^p} := ({bf E}_{n in G} |f(n)|^p)^{1/p}} for {1 < p < infty} have exponentially giant entropy (and so inverse theorems will not be anticipated to be helpful on this case):

Proposition 2 ({L^p} norm has exponentially giant inverse entropy) Let {1 < p < infty} and {0 < eta < 1}. Then the {(eta,eta^p/4)}-entropy of {| |_{L^p}} is at most {(1+8/eta^p)^N}. Conversely, for any {varepsilon>0}, the {(eta,varepsilon)}-entropy of {| |_{L^p}} is a minimum of {exp( c varepsilon^2 N)} for some absolute fixed {c>0}.

Proof: If {f} is {1}-bounded with {|f|_{L^p} geq eta}, then now we have

displaystyle  |langle f, |f|^{p-2} f rangle| geq eta^p

and therefore by the triangle inequality now we have

displaystyle  |langle f, F rangle| geq eta^p/2

the place {F} is both the actual or imaginary a part of {|f|^{p-2} f}, which takes values in {[-1,1]}. If we let {tilde F} be {F} rounded to the closest a number of of {eta^p/4}, then by the triangle inequality once more now we have

displaystyle  |langle f, tilde F rangle| geq eta^p/4.

There are solely at most {1+8/eta^p} doable values for every worth {tilde F(n)} of {tilde F}, and therefore at most {(1+8/eta^p)^N} choices for {tilde F}. This offers the primary declare.

Now suppose that there’s an {(eta,varepsilon)}-inverse theorem for some {{mathcal F}} of cardinality {M}. If we let {f} be a random signal perform (so the {f(n)} are unbiased random variables taking values in {-1,+1} with equal likelihood), then there’s a random {F in {mathcal F}} such that

displaystyle  |langle f, F rangle| geq varepsilon

and therefore by the pigeonhole precept there’s a deterministic {F in {mathcal F}} such that

displaystyle  {bf P}( |langle f, F rangle| geq varepsilon ) geq 1/M.

Then again, from the Hoeffding inequality one has

displaystyle  {bf P}( |langle f, F rangle| geq varepsilon ) ll exp( - c varepsilon^2 N )

for some absolute fixed {c}, therefore

displaystyle  M geq exp( c varepsilon^2 N )

as claimed. Box

Most seminorms of curiosity in additive combinatorics, such because the Gowers uniformity norms, are bounded by some finite {L^p} norm due to Hölder’s inequality, so from the above proposition and the apparent monotonicity properties of entropy, we conclude that every one Gowers norms on finite abelian teams {G} have at most exponential inverse theorem entropy. However we are able to do considerably higher than this:

  • For the {U^1} seminorm {|f|_{U^1(G)} := |{bf E}_{n in G} f(n)|}, one can merely take {{mathcal F} = {1}} to encompass the fixed perform {1}, and the {(eta,eta)}-entropy is clearly equal to {1} for any {0 < eta < 1}.
  • For the {U^2} norm, the usual Fourier-analytic inverse theorem asserts that if {|f|_{U^2(G)} geq eta} then langle f, e(xi cdot) rangle for some Fourier character {xi in hat G}. Thus the {(eta,eta^2)}-entropy is at most {N}.
  • For the {U^k({bf Z}/N{bf Z})} norm on cyclic teams for {k > 2}, the inverse theorem proved by Inexperienced, Ziegler, and myself provides an {(eta,varepsilon)}-inverse theorem for some {varepsilon gg_{k,eta} 1} and {{mathcal F}} consisting of nilsequences {n mapsto F(g(n) Gamma)} for some filtered nilmanifold {G/Gamma} of diploma {k-1} in a finite assortment of cardinality {O_{eta,k}(1)}, some polynomial sequence {g: {bf Z} rightarrow G} (which was subsequently noticed by Candela-Sisask (see additionally Manners) that one can select to be {N}-periodic), and a few Lipschitz perform {F: G/Gamma rightarrow {bf C}} of Lipschitz norm {O_{eta,k}(1)}. By the Arzela-Ascoli theorem, the variety of doable {F} (as much as uniform errors of dimension at most {varepsilon/2}, say) is {O_{eta,k}(1)}. By customary arguments one may also be sure that the coefficients of the polynomial {g} are {O_{eta,k}(1)}, after which by periodicity there are solely {O(N^{O_{eta,k}(1)}} such polynomials. As a consequence, the {(eta,varepsilon)}-entropy is of polynomial dimension {O_{eta,k}( N^{O_{eta,k}(1)} )} (a indisputable fact that appears to have first been implicitly noticed in Lemma 6.2 of this paper of Frantzikinakis; due to Ben Inexperienced for this reference). One can get hold of extra exact dependence on {eta,k} utilizing the quantitative model of this inverse theorem as a result of Manners; again of the envelope calculations utilizing Part 5 of that paper recommend to me that one can take {varepsilon = eta^{O_k(1)}} to be polynomial in {eta} and the entropy to be of the order {O_k( N^{exp(exp(eta^{-O_k(1)}))} )}, or alternatively one can scale back the entropy to {O_k( exp(exp(eta^{-O_k(1)})) N^{eta^{-O_k(1)}})} at the price of degrading {varepsilon} to {1/expexp( O(eta^{-O(1)}))}.
  • If one replaces the cyclic group {{bf Z}/N{bf Z}} by a vector house {{bf F}_p^n} over some fastened finite subject {{bf F}_p} of prime order (in order that {N=p^n}), then the inverse theorem of Ziegler and myself (accessible in each excessive and low attribute) permits one to acquire an {(eta,varepsilon)}-inverse theorem for some {varepsilon gg_{k,eta} 1} and {{mathcal F}} the gathering of non-classical diploma {k-1} polynomial phases from {{bf F}_p^n} to {S^1}, which one can normalize to equal {1} on the origin, after which by the classification of such polynomials one can calculate that the {(eta,varepsilon)} entropy is of quasipolynomial dimension {exp( O_{p,k}(n^{k-1}) ) = exp( O_{p,k}( log^{k-1} N ) )} in {N}. By utilizing the current work of Gowers and Milicevic, one could make the dependence on {p,k} right here extra exact, however we won’t carry out these calcualtions right here.
  • For the {U^3(G)} norm on an arbitrary finite abelian group, the current inverse theorem of Jamneshan and myself provides (after some calculations) a sure of the polynomial type {O( q^{O(n^2)} N^{exp(eta^{-O(1)})})} on the {(eta,varepsilon)}-entropy for some {varepsilon gg eta^{O(1)}}, which one can enhance barely to {O( q^{O(n^2)} N^{eta^{-O(1)}})} if one degrades {varepsilon} to {1/exp(eta^{-O(1)})}, the place {q} is the maximal order of a component of {G}, and {n} is the rank (the variety of components wanted to generate {G}). This sure is polynomial in {N} within the cyclic group case and quasipolynomial typically.

For common finite abelian teams {G}, we don’t but have an inverse theorem of comparable energy to those talked about above that give polynomial or quasipolynomial higher bounds on the entropy. Nevertheless, there’s a low-cost argument that a minimum of provides some subexponential bounds:

Proposition 3 (Low-cost subexponential sure) Let {k geq 2} and {0 < eta < 1/2}, and suppose that {G} is a finite abelian group of order {N geq eta^{-C_k}} for some sufficiently giant {C_k}. Then the {(eta,c_k eta^{O_k(1)})}-complexity of {| |_{U^k(G)}} is at most {O( exp( eta^{-O_k(1)} N^{1 - frac{k+1}{2^k-1}} ))}.

Proof: (Sketch) We use an ordinary random sampling argument, of the kind used for example by Croot-Sisask or Briet-Gopi (due to Ben Inexperienced for this latter reference). We will assume that {N geq eta^{-C_k}} for some sufficiently giant {C_k>0}, since in any other case the declare follows from Proposition 2.

Let {A} be a random subset of {{bf Z}/N{bf Z}} with the occasions {n in A} being iid with likelihood {0 < p < 1} to be chosen later, conditioned to the occasion  leq 2pN. Let {f} be a {1}-bounded perform. By an ordinary second second calculation, we see that with likelihood a minimum of {1/2}, now we have

displaystyle  |f|_{U^k(G)}^{2^k} = {bf E}_{n, h_1,dots,h_k in G} f(n) prod_{omega in {0,1}^k backslash {0}} {mathcal C}^ frac{1}{p} 1_A f(n + omega cdot h)

displaystyle + O((frac{1}{N^{k+1} p^{2^k-1}})^{1/2}).

Thus, by the triangle inequality, if we select {p := C eta^{-2^{k+1}/(2^k-1)} / N^{frac{k+1}{2^k-1}}} for some sufficiently giant {C = C_k > 0}, then for any {1}-bounded {f} with {|f|_{U^k(G)} geq eta/2}, one has with likelihood a minimum of {1/2} that

displaystyle  |{bf E}_{n, h_1,dots,h_k i2^n G} f(n) prod_{omega in {0,1}^k backslash {0}} {mathcal C}^ frac{1}{p} 1_A f(n + omega cdot h)|

displaystyle geq eta^{2^k}/2^{2^k+1}.

We will write the left-hand aspect as langle f, F rangle the place {F} is the randomly sampled twin perform

displaystyle  F(n) := {bf E}_{n, h_1,dots,h_k in G} f(n) prod_{omega in {0,1}^k backslash {0}} {mathcal C}^+1 frac{1}{p} 1_A f(n + omega cdot h).

Sadly, {F} is just not {1}-bounded typically, however now we have

displaystyle  |F|_{L^2(G)}^2 leq {bf E}_{n, h_1,dots,h_k ,h'_1,dots,h'_k in G}

displaystyle  prod_{omega in {0,1}^k backslash {0}} frac{1}{p} 1_A(n + omega cdot h) frac{1}{p} 1_A(n + omega cdot h')

and the right-hand aspect will be proven to be {1+o(1)} on the typical, so we are able to situation on the occasion that the right-hand aspect is {O(1)} with out vital loss in falure likelihood.

If we then let {tilde f_A} be {1_A f} rounded to the closest Gaussian integer a number of of {eta^{2^k}/2^{2^{10k}}} within the unit disk, one has from the triangle inequality that

displaystyle  |langle f, tilde F rangle| geq eta^{2^k}/2^{2^k+2}

the place {tilde F} is the discretised randomly sampled twin perform

displaystyle  tilde F(n) := {bf E}_{n, h_1,dots,h_k in G} f(n) prod_{omega in {0,1}^k backslash {0}} {mathcal C}^+1 frac{1}{p} tilde f_A(n + omega cdot h).

For any given {A}, there are at most {2np} locations {n} the place {tilde f_A(n)} will be non-zero, and in these locations there are {O_k( eta^{-2^{k}})} doable values for {tilde f_A(n)}. Thus, if we let {{mathcal F}_A} be the gathering of all doable {tilde f_A} related to a given {A}, the cardinality of this set is {O( exp( eta^{-O_k(1)} N^{1 - frac{k+1}{2^k-1}} ) )}, and for any {f} with {|f|_{U^k(G)} geq eta/2}, now we have

displaystyle  sup_{tilde F in {mathcal F}_A} |langle f, tilde F rangle| geq eta^{2^k}/2^{k+2}

with likelihood a minimum of {1/2}.

Now we take away the failure likelihood by unbiased resampling. By rounding to the closest Gaussian integer a number of of {c_k eta^{2^k}} within the unit disk for a small enough {c_k>0}, one can discover a household {{mathcal G}} of cardinality {O( eta^{-O_k(N)})} consisting of {1}-bounded capabilities {tilde f} of {U^k(G)} norm a minimum of {eta/2} such that for each {1}-bounded {f} with {|f|_{U^k(G)} geq eta} there exists {tilde f in {mathcal G}} such that

displaystyle  |f-tilde f|_{L^infty(G)} leq eta^{2^k}/2^{k+3}.

Now, let {A_1,dots,A_M} be unbiased samples of {A} for some {M} to be chosen later. By the previous dialogue, we see that with likelihood a minimum of {1 - 2^{-M}}, now we have

displaystyle  sup_{tilde F in bigcup_{j=1}^M {mathcal F}_{A_j}} |langle tilde f, tilde F rangle| geq eta^{2^k}/2^{k+2}

for any given {tilde f in {mathcal G}}, so by the union sure, if we select {M = lfloor C N log frac{1}{eta} rfloor} for a big sufficient {C = C_k}, we are able to discover {A_1,dots,A_M} such that

displaystyle  sup_{tilde F in bigcup_{j=1}^M {mathcal F}_{A_j}} |langle tilde f, tilde F rangle| geq eta^{2^k}/2^{k+2}

for all {tilde f in {mathcal G}}, and therefore y the triangle inequality

displaystyle  sup_{tilde F in bigcup_{j=1}^M {mathcal F}_{A_j}} |langle f, tilde F rangle| geq eta^{2^k}/2^{k+3}.

Taking {{mathcal F}} to be the union of the {{mathcal F}_{A_j}} (making use of some truncation and rescaling to those {L^2}-bounded capabilities to make them {L^infty}-bounded, after which {1}-bounded), we get hold of the declare. Box

One technique to get hold of decrease bounds on the inverse theorem entropy is to supply a group of just about orthogonal capabilities with giant norm. Extra exactly:

Proposition 4 Let be a seminorm, let {0 < varepsilon leq eta < 1}, and suppose that one has a group {f_1,dots,f_M} of {1}-bounded capabilities such that for all {i=1,dots,M},  geq eta one has  leq varepsilon^2/2 for all however at most {L} decisions of {j in {1,dots,M}} for all distinct {i,j in {1,dots,M}}. Then the {(eta, varepsilon)}-entropy of is a minimum of {varepsilon^2 M / 2L}.

Proof: Suppose now we have an {(eta,varepsilon)}-inverse theorem with some household {{mathcal F}}. Then for every {i=1,dots,M} there may be {F_i in {mathcal F}} such that  geq varepsilon. By the pigeonhole precept, there may be thus {F in {mathcal F}} such that  geq varepsilon for all {i} in a subset {I} of {{1,dots,M}} of cardinality a minimum of {M/|{mathcal F}|}:

displaystyle  |I| geq M / |{mathcal F}|.

We will sum this to acquire

displaystyle  |sum_{i in I} c_i langle f_i, F rangle| geq |I| varepsilon

for some complicated numbers {c_i} of unit magnitude. By Cauchy-Schwarz, this means

displaystyle  | sum_{i in I} c_i f_i |_{L^2(G)}^2 geq |I|^2 varepsilon^2

and therefore by the triangle inequality

displaystyle  sum_{i,j in I} |langle f_i, f_j rangle| geq |I|^2 varepsilon^2.

Then again, by speculation we are able to sure the left-hand aspect by I. Rearranging, we conclude that

displaystyle  |I| leq 2 L / varepsilon^2

and therefore

displaystyle  |{mathcal F}| geq varepsilon^2 M / 2L

giving the declare. Box

Thus for example:

  • For the {U^2(G)} norm, one can take {f_1,dots,f_M} to be the household of linear exponential phases {n mapsto e(xi cdot n)} with {M = N} and {L=1}, and procure a linear decrease sure of {varepsilon^2 N/2} for the {(eta,varepsilon)}-entropy, thus matching the higher sure of {N} as much as constants when {varepsilon} is fastened.
  • For the {U^k({bf Z}/N{bf Z})} norm, the same calculation utilizing polynomial phases of diploma {k-1}, mixed with the Weyl sum estimates, provides a decrease sure of {gg_{k,varepsilon} N^{k-1}} for the {(eta,varepsilon)}-entropy for any fastened {eta,varepsilon}; by contemplating nilsequences as properly, along with nilsequence equidistribution idea, one can change the exponent {k-1} right here by some amount that goes to infinity as {eta rightarrow 0}, although I’ve not tried to calculate the precise price.
  • For the {U^k({bf F}_p^n)} norm, one other comparable calculation utilizing polynomial phases of diploma {k-1} ought to give a decrease sure of {gg_{p,k,eta,varepsilon} exp( c_{p,k,eta,varepsilon} n^{k-1} )} for the {(eta,varepsilon)}-entropy, although I’ve not absolutely carried out the calculation.

We shut with one ultimate instance. Suppose {G} is a product {G = A times B} of two units {A,B} of cardinality {asymp sqrt{N}}, and we contemplate the Gowers field norm

displaystyle  |f|_{Box^2(G)}^4 := {bf E}_{a,a' in A; b,b' in B} f(a,b) overline{f}(a,b') overline{f}(a',b) f(a,b).

One doable alternative of sophistication {{mathcal F}} listed below are the symptoms {1_{U times V}} of “rectangles” {U times V} with {U subset A}, {V subset B} (cf. this earlier weblog publish on lower norms). By customary calculations, one can use this class to point out that the {(eta, eta^4/10)}-entropy of {| |_{Box^2(G)}} is {O( exp( O(sqrt{N}) )}, and a variant of the proof of the second a part of Proposition 2 reveals that that is the proper order of development in {N}. In distinction, a modification of Proposition 3 solely provides an higher sure of the shape {O( exp( O( N^{2/3} ) ) )} (the bottleneck is making certain that the randomly sampled twin capabilities keep bounded in {L^2}), which reveals that whereas this low-cost sure is just not optimum, it could possibly nonetheless broadly give the proper “sort” of sure (particularly, intermediate development between polynomial and exponential).



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