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Kaisa Matomäki, Xuancheng Shao, Joni Teräväinen, and myself have just uploaded to the arXiv our preprint “Higher uniformity of arithmetic functions in short intervals I. All intervals“. This paper investigates the higher order (Gowers) uniformity of standard arithmetic functions in analytic number theory (and specifically, the Möbius function ${\mu}$, the von Mangoldt function ${\Lambda}$, and the generalised divisor functions ${d_k}$) in short intervals ${(X,X+H]}$, where ${X}$ is large and ${H}$ lies in the range ${X^{\theta+\varepsilon} \leq H \leq X^{1-\varepsilon}}$ for a fixed constant ${0 < \theta < 1}$ (that one would like to be as small as possible). If we let ${f}$ denote one of the functions ${\mu, \Lambda, d_k}$, then there is extensive literature on the estimation of short sums

$\displaystyle \sum_{X < n \leq X+H} f(n)$

and some literature also on the estimation of exponential sums such as

$\displaystyle \sum_{X < n \leq X+H} f(n) e(-\alpha n)$

for a real frequency ${\alpha}$, where ${e(\theta) := e^{2\pi i \theta}}$. For applications in the additive combinatorics of such functions ${f}$, it is also necessary to consider more general correlations, such as polynomial correlations

$\displaystyle \sum_{X < n \leq X+H} f(n) e(-P(n))$

where ${P: {\bf Z} \rightarrow {\bf R}}$ is a polynomial of some fixed degree, or more generally

$\displaystyle \sum_{X < n \leq X+H} f(n) \overline{F}(g(n) \Gamma)$

where ${G/\Gamma}$ is a nilmanifold of fixed degree and dimension (and with some control on structure constants), ${g: {\bf Z} \rightarrow G}$ is a polynomial map, and ${F: G/\Gamma \rightarrow {\bf C}}$ is a Lipschitz function (with some bound on the Lipschitz constant). Indeed, thanks to the inverse theorem for the Gowers uniformity norm, such correlations let one control the Gowers uniformity norm of ${f}$ (possibly after subtracting off some renormalising factor) on such short intervals ${(X,X+H]}$, which can in turn be used to control other multilinear correlations involving such functions.

Traditionally, asymptotics for such sums are expressed in terms of a “main term” of some arithmetic nature, plus an error term that is estimated in magnitude. For instance, a sum such as ${\sum_{X < n \leq X+H} \Lambda(n) e(-\alpha n)}$ would be approximated in terms of a main term that vanished (or is negligible) if ${\alpha}$ is “minor arc”, but would be expressible in terms of something like a Ramanujan sum if ${\alpha}$ was “major arc”, together with an error term. We found it convenient to cancel off such main terms by subtracting an approximant ${f^\sharp}$ from each of the arithmetic functions ${f}$ and then getting upper bounds on remainder correlations such as

$\displaystyle |\sum_{X < n \leq X+H} (f(n)-f^\sharp(n)) \overline{F}(g(n) \Gamma)| \ \ \ \ \ (1)$

(actually for technical reasons we also allow the ${n}$ variable to be restricted further to a subprogression of ${(X,X+H]}$, but let us ignore this minor extension for this discussion). There is some flexibility in how to choose these approximants, but we eventually found it convenient to use the following choices.

• For the Möbius function ${\mu}$, we simply set ${\mu^\sharp = 0}$, as per the Möbius pseudorandomness conjecture. (One could choose a more sophisticated approximant in the presence of a Siegel zero, as I did with Joni in this recent paper, but we do not do so here.)
• For the von Mangoldt function ${\Lambda}$, we eventually went with the Cramér-Granville approximant ${\Lambda^\sharp(n) = \frac{W}{\phi(W)} 1_{(n,W)=1}}$, where ${W = \prod_{p < R} p}$ and ${R = \exp(\log^{1/10} X)}$.
• For the divisor functions ${d_k}$, we used a somewhat complicated-looking approximant ${d_k^\sharp(n) = \sum_{m \leq X^{\frac{k-1}{5k}}} P_m(\log n)}$ for some explicit polynomials ${P_m}$, chosen so that ${d_k^\sharp}$ and ${d_k}$ have almost exactly the same sums along arithmetic progressions (see the paper for details).

The objective is then to obtain bounds on sums such as (1) that improve upon the “trivial bound” that one can get with the triangle inequality and standard number theory bounds such as the Brun-Titchmarsh inequality. For ${\mu}$ and ${\Lambda}$, the Siegel-Walfisz theorem suggests that it is reasonable to expect error terms that have “strongly logarithmic savings” in the sense that they gain a factor of ${O_A(\log^{-A} X)}$ over the trivial bound for any ${A>0}$; for ${d_k}$, the Dirichlet hyperbola method suggests instead that one has “power savings” in that one should gain a factor of ${X^{-c_k}}$ over the trivial bound for some ${c_k>0}$. In the case of the Möbius function ${\mu}$, there is an additional trick (introduced by Matomäki and Teräväinen) that allows one to lower the exponent ${\theta}$ somewhat at the cost of only obtaining “weakly logarithmic savings” of shape ${\log^{-c} X}$ for some small ${c>0}$.

Our main estimates on sums of the form (1) work in the following ranges:

• For ${\theta=5/8}$, one can obtain strongly logarithmic savings on (1) for ${f=\mu,\Lambda}$, and power savings for ${f=d_k}$.
• For ${\theta=3/5}$, one can obtain weakly logarithmic savings for ${f = \mu, d_k}$.
• For ${\theta=5/9}$, one can obtain power savings for ${f=d_3}$.
• For ${\theta=1/3}$, one can obtain power savings for ${f=d_2}$.

Conjecturally, one should be able to obtain power savings in all cases, and lower ${\theta}$ down to zero, but the ranges of exponents and savings given here seem to be the limit of current methods unless one assumes additional hypotheses, such as GRH. The ${\theta=5/8}$ result for correlation against Fourier phases ${e(\alpha n)}$ was established previously by Zhan, and the ${\theta=3/5}$ result for such phases and ${f=\mu}$ was established previously by by Matomäki and Teräväinen.

By combining these results with tools from additive combinatorics, one can obtain a number of applications:

• Direct insertion of our bounds in the recent work of Kanigowski, Lemanczyk, and Radziwill on the prime number theorem on dynamical systems that are analytic skew products gives some improvements in the exponents there.
• We can obtain a “short interval” version of a multiple ergodic theorem along primes established by Frantzikinakis-Host-Kra and Wooley-Ziegler, in which we average over intervals of the form ${(X,X+H]}$ rather than ${[1,X]}$.
• We can obtain a “short interval” version of the “linear equations in primes” asymptotics obtained by Ben Green, Tamar Ziegler, and myself in this sequence of papers, where the variables in these equations lie in short intervals ${(X,X+H]}$ rather than long intervals such as ${[1,X]}$.

We now briefly discuss some of the ingredients of proof of our main results. The first step is standard, using combinatorial decompositions (based on the Heath-Brown identity and (for the ${\theta=3/5}$ result) the Ramaré identity) to decompose ${\mu(n), \Lambda(n), d_k(n)}$ into more tractable sums of the following types:

• Type ${I}$ sums, which are basically of the form ${\sum_{m \leq A:m|n} \alpha(m)}$ for some weights ${\alpha(m)}$ of controlled size and some cutoff ${A}$ that is not too large;
• Type ${II}$ sums, which are basically of the form ${\sum_{A_- \leq m \leq A_+:m|n} \alpha(m)\beta(n/m)}$ for some weights ${\alpha(m)}$, ${\beta(n)}$ of controlled size and some cutoffs ${A_-, A_+}$ that are not too close to ${1}$ or to ${X}$;
• Type ${I_2}$ sums, which are basically of the form ${\sum_{m \leq A:m|n} \alpha(m) d_2(n/m)}$ for some weights ${\alpha(m)}$ of controlled size and some cutoff ${A}$ that is not too large.

The precise ranges of the cutoffs ${A, A_-, A_+}$ depend on the choice of ${\theta}$; our methods fail once these cutoffs pass a certain threshold, and this is the reason for the exponents ${\theta}$ being what they are in our main results.

The Type ${I}$ sums involving nilsequences can be treated by methods similar to those in this previous paper of Ben Green and myself; the main innovations are in the treatment of the Type ${II}$ and Type ${I_2}$ sums.

For the Type ${II}$ sums, one can split into the “abelian” case in which (after some Fourier decomposition) the nilsequence ${F(g(n)\Gamma)}$ is basically of the form ${e(P(n))}$, and the “non-abelian” case in which ${G}$ is non-abelian and ${F}$ exhibits non-trivial oscillation in a central direction. In the abelian case we can adapt arguments of Matomaki and Shao, which uses Cauchy-Schwarz and the equidistribution properties of polynomials to obtain good bounds unless ${e(P(n))}$ is “major arc” in the sense that it resembles (or “pretends to be”) ${\chi(n) n^{it}}$ for some Dirichlet character ${\chi}$ and some frequency ${t}$, but in this case one can use classical multiplicative methods to control the correlation. It turns out that the non-abelian case can be treated similarly. After applying Cauchy-Schwarz, one ends up analyzing the equidistribution of the four-variable polynomial sequence

$\displaystyle (n,m,n',m') \mapsto (g(nm)\Gamma, g(n'm)\Gamma, g(nm') \Gamma, g(n'm'\Gamma))$

as ${n,m,n',m'}$ range in various dyadic intervals. Using the known multidimensional equidistribution theory of polynomial maps in nilmanifolds, one can eventually show in the non-abelian case that this sequence either has enough equidistribution to give cancellation, or else the nilsequence involved can be replaced with one from a lower dimensional nilmanifold, in which case one can apply an induction hypothesis.

For the type ${I_2}$ sum, a model sum to study is

$\displaystyle \sum_{X < n \leq X+H} d_2(n) e(\alpha n)$

which one can expand as

$\displaystyle \sum_{n,m: X < nm \leq X+H} e(\alpha nm).$

We experimented with a number of ways to treat this type of sum (including automorphic form methods, or methods based on the Voronoi formula or van der Corput’s inequality), but somewhat to our surprise, the most efficient approach was an elementary one, in which one uses the Dirichlet approximation theorem to decompose the hyperbolic region ${\{ (n,m) \in {\bf N}^2: X < nm \leq X+H \}}$ into a number of arithmetic progressions, and then uses equidistribution theory to establish cancellation of sequences such as ${e(\alpha nm)}$ on the majority of these progressions. As it turns out, this strategy works well in the regime ${H > X^{1/3+\varepsilon}}$ unless the nilsequence involved is “major arc”, but the latter case is treatable by existing methods as discussed previously; this is why the ${\theta}$ exponent for our ${d_2}$ result can be as low as ${1/3}$.

In a sequel to this paper (currently in preparation), we will obtain analogous results for almost all intervals ${(x,x+H]}$ with ${x}$ in the range ${[X,2X]}$, in which we will be able to lower ${\theta}$ all the way to ${0}$.

Joni Teräväinen and I have just uploaded to the arXiv our preprint “The Hardy–Littlewood–Chowla conjecture in the presence of a Siegel zero“. This paper is a development of the theme that certain conjectures in analytic number theory become easier if one makes the hypothesis that Siegel zeroes exist; this places one in a presumably “illusory” universe, since the widely believed Generalised Riemann Hypothesis (GRH) precludes the existence of such zeroes, yet this illusory universe seems remarkably self-consistent and notoriously impossible to eliminate from one’s analysis.

For the purposes of this paper, a Siegel zero is a zero ${\beta}$ of a Dirichlet ${L}$-function ${L(\cdot,\chi)}$ corresponding to a primitive quadratic character ${\chi}$ of some conductor ${q_\chi}$, which is close to ${1}$ in the sense that

$\displaystyle \beta = 1 - \frac{1}{\eta \log q_\chi}$

for some large ${\eta \gg 1}$ (which we will call the quality) of the Siegel zero. The significance of these zeroes is that they force the Möbius function ${\mu}$ and the Liouville function ${\lambda}$ to “pretend” to be like the exceptional character ${\chi}$ for primes of magnitude comparable to ${q_\chi}$. Indeed, if we define an exceptional prime to be a prime ${p^*}$ in which ${\chi(p^*) \neq -1}$, then very few primes near ${q_\chi}$ will be exceptional; in our paper we use some elementary arguments to establish the bounds

$\displaystyle \sum_{q_\chi^{1/2+\varepsilon} < p^* \leq x} \frac{1}{p^*} \ll_\varepsilon \frac{\log x}{\eta \log q_\chi} \ \ \ \ \ (1)$

for any ${x \geq q_\chi^{1/2+\varepsilon}}$ and ${\varepsilon>0}$, where the sum is over exceptional primes in the indicated range ${q_\chi^{1/2+\varepsilon} < p^* \leq x}$; this bound is non-trivial for ${x}$ as large as ${q_\chi^{\eta^{1-\varepsilon}}}$. (See Section 1 of this blog post for some variants of this argument, which were inspired by work of Heath-Brown.) There is also a companion bound (somewhat weaker) that covers a range of ${p^*}$ a little bit below ${q_\chi^{1/2}}$.

One of the early influential results in this area was the following result of Heath-Brown, which I previously blogged about here:

Theorem 1 (Hardy-Littlewood assuming Siegel zero) Let ${h}$ be a fixed natural number. Suppose one has a Siegel zero ${\beta}$ associated to some conductor ${q_\chi}$. Then we have

$\displaystyle \sum_{n \leq x} \Lambda(n) \Lambda(n+h) = ({\mathfrak S} + O( \frac{1}{\log\log \eta} )) x$

for all ${q_\chi^{250} \leq x \leq q_\chi^{300}}$, where ${\Lambda}$ is the von Mangoldt function and ${{\mathfrak S}}$ is the singular series

$\displaystyle {\mathfrak S} = \prod_{p|h} \frac{p}{p-1} \prod_{p \nmid h} (1 - \frac{1}{(p-1)^2})$

In particular, Heath-Brown showed that if there are infinitely many Siegel zeroes, then there are also infinitely many twin primes, with the correct asymptotic predicted by the Hardy-Littlewood prime tuple conjecture at infinitely many scales.

Very recently, Chinis established an analogous result for the Chowla conjecture (building upon earlier work of Germán and Katai):

Theorem 2 (Chowla assuming Siegel zero) Let ${h_1,\dots,h_\ell}$ be distinct fixed natural numbers. Suppose one has a Siegel zero ${\beta}$ associated to some conductor ${q_\chi}$. Then one has

$\displaystyle \sum_{n \leq x} \lambda(n+h_1) \dots \lambda(n+h_\ell) \ll \frac{x}{(\log\log \eta)^{1/2} (\log \eta)^{1/12}}$

in the range ${q_\chi^{10} \leq x \leq q_\chi^{\log\log \eta / 3}}$, where ${\lambda}$ is the Liouville function.

In our paper we unify these results and also improve the quantitative estimates and range of ${x}$:

Theorem 3 (Hardy-Littlewood-Chowla assuming Siegel zero) Let ${h_1,\dots,h_k,h'_1,\dots,h'_\ell}$ be distinct fixed natural numbers with ${k \leq 2}$. Suppose one has a Siegel zero ${\beta}$ associated to some conductor ${q_\chi}$. Then one has

$\displaystyle \sum_{n \leq x} \Lambda(n+h_1) \dots \Lambda(n+h_k) \lambda(n+h'_1) \dots \lambda(n+h'_\ell)$

$\displaystyle = ({\mathfrak S} + O_\varepsilon( \frac{1}{\log^{1/10\max(1,k)} \eta} )) x$

for

$\displaystyle q_\chi^{10k+\frac{1}{2}+\varepsilon} \leq x \leq q_\chi^{\eta^{1/2}}$

for any fixed ${\varepsilon>0}$.

Our argument proceeds by a series of steps in which we replace ${\Lambda}$ and ${\lambda}$ by more complicated looking, but also more tractable, approximations, until the correlation is one that can be computed in a tedious but straightforward fashion by known techniques. More precisely, the steps are as follows:

• (i) Replace the Liouville function ${\lambda}$ with an approximant ${\lambda_{\mathrm{Siegel}}}$, which is a completely multiplicative function that agrees with ${\lambda}$ at small primes and agrees with ${\chi}$ at large primes.
• (ii) Replace the von Mangoldt function ${\Lambda}$ with an approximant ${\Lambda_{\mathrm{Siegel}}}$, which is the Dirichlet convolution ${\chi * \log}$ multiplied by a Selberg sieve weight ${\nu}$ to essentially restrict that convolution to almost primes.
• (iii) Replace ${\lambda_{\mathrm{Siegel}}}$ with a more complicated truncation ${\lambda_{\mathrm{Siegel}}^\sharp}$ which has the structure of a “Type I sum”, and which agrees with ${\lambda_{\mathrm{Siegel}}}$ on numbers that have a “typical” factorization.
• (iv) Replace the approximant ${\Lambda_{\mathrm{Siegel}}}$ with a more complicated approximant ${\Lambda_{\mathrm{Siegel}}^\sharp}$ which has the structure of a “Type I sum”.
• (v) Now that all terms in the correlation have been replaced with tractable Type I sums, use standard Euler product calculations and Fourier analysis, similar in spirit to the proof of the pseudorandomness of the Selberg sieve majorant for the primes in this paper of Ben Green and myself, to evaluate the correlation to high accuracy.

Steps (i), (ii) proceed mainly through estimates such as (1) and standard sieve theory bounds. Step (iii) is based primarily on estimates on the number of smooth numbers of a certain size.

The restriction ${k \leq 2}$ in our main theorem is needed only to execute step (iv) of this step. Roughly speaking, the Siegel approximant ${\Lambda_{\mathrm{Siegel}}}$ to ${\Lambda}$ is a twisted, sieved version of the divisor function ${\tau}$, and the types of correlation one is faced with at the start of step (iv) are a more complicated version of the divisor correlation sum

$\displaystyle \sum_{n \leq x} \tau(n+h_1) \dots \tau(n+h_k).$

For ${k=1}$ this sum can be easily controlled by the Dirichlet hyperbola method. For ${k=2}$ one needs the fact that ${\tau}$ has a level of distribution greater than ${1/2}$; in fact Kloosterman sum bounds give a level of distribution of ${2/3}$, a folklore fact that seems to have first been observed by Linnik and Selberg. We use a (notationally more complicated) version of this argument to treat the sums arising in (iv) for ${k \leq 2}$. Unfortunately for ${k > 2}$ there are no known techniques to unconditionally obtain asymptotics, even for the model sum

$\displaystyle \sum_{n \leq x} \tau(n) \tau(n+1) \tau(n+2),$

although we do at least have fairly convincing conjectures as to what the asymptotics should be. Because of this, it seems unlikely that one will be able to relax the ${k \leq 2}$ hypothesis in our main theorem at our current level of understanding of analytic number theory.

Step (v) is a tedious but straightforward sieve theoretic computation, similar in many ways to the correlation estimates of Goldston and Yildirim used in their work on small gaps between primes (as discussed for instance here), and then also used by Ben Green and myself to locate arithmetic progressions in primes.

Joni Teräväinen and myself have just uploaded to the arXiv our preprint “Quantitative bounds for Gowers uniformity of the Möbius and von Mangoldt functions“. This paper makes quantitative the Gowers uniformity estimates on the Möbius function ${\mu}$ and the von Mangoldt function ${\Lambda}$.

To discuss the results we first discuss the situation of the Möbius function, which is technically simpler in some (though not all) ways. We assume familiarity with Gowers norms and standard notations around these norms, such as the averaging notation ${\mathop{\bf E}_{n \in [N]}}$ and the exponential notation ${e(\theta) = e^{2\pi i \theta}}$. The prime number theorem in qualitative form asserts that

$\displaystyle \mathop{\bf E}_{n \in [N]} \mu(n) = o(1)$

as ${N \rightarrow \infty}$. With Vinogradov-Korobov error term, the prime number theorem is strengthened to

$\displaystyle \mathop{\bf E}_{n \in [N]} \mu(n) \ll \exp( - c \log^{3/5} N (\log \log N)^{-1/5} );$

we refer to such decay bounds (With ${\exp(-c\log^c N)}$ type factors) as pseudopolynomial decay. Equivalently, we obtain pseudopolynomial decay of Gowers ${U^1}$ seminorm of ${\mu}$:

$\displaystyle \| \mu \|_{U^1([N])} \ll \exp( - c \log^{3/5} N (\log \log N)^{-1/5} ).$

As is well known, the Riemann hypothesis would be equivalent to an upgrade of this estimate to polynomial decay of the form

$\displaystyle \| \mu \|_{U^1([N])} \ll_\varepsilon N^{-1/2+\varepsilon}$

for any ${\varepsilon>0}$.

Once one restricts to arithmetic progressions, the situation gets worse: the Siegel-Walfisz theorem gives the bound

$\displaystyle \| \mu 1_{a \hbox{ mod } q}\|_{U^1([N])} \ll_A \log^{-A} N \ \ \ \ \ (1)$

for any residue class ${a \hbox{ mod } q}$ and any ${A>0}$, but with the catch that the implied constant is ineffective in ${A}$. This ineffectivity cannot be removed without further progress on the notorious Siegel zero problem.

In 1937, Davenport was able to show the discorrelation estimate

$\displaystyle \mathop{\bf E}_{n \in [N]} \mu(n) e(-\alpha n) \ll_A \log^{-A} N$

for any ${A>0}$ uniformly in ${\alpha \in {\bf R}}$, which leads (by standard Fourier arguments) to the Fourier uniformity estimate

$\displaystyle \| \mu \|_{U^2([N])} \ll_A \log^{-A} N.$

Again, the implied constant is ineffective. If one insists on effective constants, the best bound currently available is

$\displaystyle \| \mu \|_{U^2([N])} \ll \log^{-c} N \ \ \ \ \ (2)$

for some small effective constant ${c>0}$.

For the situation with the ${U^3}$ norm the previously known results were much weaker. Ben Green and I showed that

$\displaystyle \mathop{\bf E}_{n \in [N]} \mu(n) \overline{F}(g(n) \Gamma) \ll_{A,F,G/\Gamma} \log^{-A} N \ \ \ \ \ (3)$

uniformly for any ${A>0}$, any degree two (filtered) nilmanifold ${G/\Gamma}$, any polynomial sequence ${g: {\bf Z} \rightarrow G}$, and any Lipschitz function ${F}$; again, the implied constants are ineffective. On the other hand, in a separate paper of Ben Green and myself, we established the following inverse theorem: if for instance we knew that

$\displaystyle \| \mu \|_{U^3([N])} \geq \delta$

for some ${0 < \delta < 1/2}$, then there exists a degree two nilmanifold ${G/\Gamma}$ of dimension ${O( \delta^{-O(1)} )}$, complexity ${O( \delta^{-O(1)} )}$, a polynomial sequence ${g: {\bf Z} \rightarrow G}$, and Lipschitz function ${F}$ of Lipschitz constant ${O(\delta^{-O(1)})}$ such that

$\displaystyle \mathop{\bf E}_{n \in [N]} \mu(n) \overline{F}(g(n) \Gamma) \gg \exp(-\delta^{-O(1)}).$

Putting the two assertions together and comparing all the dependencies on parameters, one can establish the qualitative decay bound

$\displaystyle \| \mu \|_{U^3([N])} = o(1).$

However the decay rate ${o(1)}$ produced by this argument is completely ineffective: obtaining a bound on when this ${o(1)}$ quantity dips below a given threshold ${\delta}$ depends on the implied constant in (3) for some ${G/\Gamma}$ whose dimension depends on ${\delta}$, and the dependence on ${\delta}$ obtained in this fashion is ineffective in the face of a Siegel zero.

For higher norms ${U^k, k \geq 3}$, the situation is even worse, because the quantitative inverse theory for these norms is poorer, and indeed it was only with the recent work of Manners that any such bound is available at all (at least for ${k>4}$). Basically, Manners establishes if

$\displaystyle \| \mu \|_{U^k([N])} \geq \delta$

then there exists a degree ${k-1}$ nilmanifold ${G/\Gamma}$ of dimension ${O( \delta^{-O(1)} )}$, complexity ${O( \exp\exp(\delta^{-O(1)}) )}$, a polynomial sequence ${g: {\bf Z} \rightarrow G}$, and Lipschitz function ${F}$ of Lipschitz constant ${O(\exp\exp(\delta^{-O(1)}))}$ such that

$\displaystyle \mathop{\bf E}_{n \in [N]} \mu(n) \overline{F}(g(n) \Gamma) \gg \exp\exp(-\delta^{-O(1)}).$

(We allow all implied constants to depend on ${k}$.) Meanwhile, the bound (3) was extended to arbitrary nilmanifolds by Ben and myself. Again, the two results when concatenated give the qualitative decay

$\displaystyle \| \mu \|_{U^k([N])} = o(1)$

but the decay rate is completely ineffective.

Our first result gives an effective decay bound:

Theorem 1 For any ${k \geq 2}$, we have ${\| \mu \|_{U^k([N])} \ll (\log\log N)^{-c_k}}$ for some ${c_k>0}$. The implied constants are effective.

This is off by a logarithm from the best effective bound (2) in the ${k=2}$ case. In the ${k=3}$ case there is some hope to remove this logarithm based on the improved quantitative inverse theory currently available in this case, but there is a technical obstruction to doing so which we will discuss later in this post. For ${k>3}$ the above bound is the best one could hope to achieve purely using the quantitative inverse theory of Manners.

We have analogues of all the above results for the von Mangoldt function ${\Lambda}$. Here a complication arises that ${\Lambda}$ does not have mean close to zero, and one has to subtract off some suitable approximant ${\Lambda^\sharp}$ to ${\Lambda}$ before one would expect good Gowers norms bounds. For the prime number theorem one can just use the approximant ${1}$, giving

$\displaystyle \| \Lambda - 1 \|_{U^1([N])} \ll \exp( - c \log^{3/5} N (\log \log N)^{-1/5} )$

but even for the prime number theorem in arithmetic progressions one needs a more accurate approximant. In our paper it is convenient to use the “Cramér approximant”

$\displaystyle \Lambda_{\hbox{Cram\'er}}(n) := \frac{W}{\phi(W)} 1_{(n,W)=1}$

where

$\displaystyle W := \prod_{p

and ${Q}$ is the quasipolynomial quantity

$\displaystyle Q = \exp(\log^{1/10} N). \ \ \ \ \ (4)$

Then one can show from the Siegel-Walfisz theorem and standard bilinear sum methods that

$\displaystyle \mathop{\bf E}_{n \in [N]} (\Lambda - \Lambda_{\hbox{Cram\'er}}(n)) e(-\alpha n) \ll_A \log^{-A} N$

and

$\displaystyle \| \Lambda - \Lambda_{\hbox{Cram\'er}}\|_{U^2([N])} \ll_A \log^{-A} N$

for all ${A>0}$ and ${\alpha \in {\bf R}}$ (with an ineffective dependence on ${A}$), again regaining effectivity if ${A}$ is replaced by a sufficiently small constant ${c>0}$. All the previously stated discorrelation and Gowers uniformity results for ${\mu}$ then have analogues for ${\Lambda}$, and our main result is similarly analogous:

Theorem 2 For any ${k \geq 2}$, we have ${\| \Lambda - \Lambda_{\hbox{Cram\'er}} \|_{U^k([N])} \ll (\log\log N)^{-c_k}}$ for some ${c_k>0}$. The implied constants are effective.

By standard methods, this result also gives quantitative asymptotics for counting solutions to various systems of linear equations in primes, with error terms that gain a factor of ${O((\log\log N)^{-c})}$ with respect to the main term.

We now discuss the methods of proof, focusing first on the case of the Möbius function. Suppose first that there is no “Siegel zero”, by which we mean a quadratic character ${\chi}$ of some conductor ${q \leq Q}$ with a zero ${L(\beta,\chi)}$ with ${1 - \beta \leq \frac{c}{\log Q}}$ for some small absolute constant ${c>0}$. In this case the Siegel-Walfisz bound (1) improves to a quasipolynomial bound

$\displaystyle \| \mu 1_{a \hbox{ mod } q}\|_{U^1([N])} \ll \exp(-\log^c N). \ \ \ \ \ (5)$

To establish Theorem 1 in this case, it suffices by Manners’ inverse theorem to establish the polylogarithmic bound

$\displaystyle \mathop{\bf E}_{n \in [N]} \mu(n) \overline{F}(g(n) \Gamma) \ll \exp(-\log^c N) \ \ \ \ \ (6)$

for all degree ${k-1}$ nilmanifolds ${G/\Gamma}$ of dimension ${O((\log\log N)^c)}$ and complexity ${O( \exp(\log^c N))}$, all polynomial sequences ${g}$, and all Lipschitz functions ${F}$ of norm ${O( \exp(\log^c N))}$. If the nilmanifold ${G/\Gamma}$ had bounded dimension, then one could repeat the arguments of Ben and myself more or less verbatim to establish this claim from (5), which relied on the quantitative equidistribution theory on nilmanifolds developed in a separate paper of Ben and myself. Unfortunately, in the latter paper the dependence of the quantitative bounds on the dimension ${d}$ was not explicitly given. In an appendix to the current paper, we go through that paper to account for this dependence, showing that all exponents depend at most doubly exponentially in the dimension ${d}$, which is barely sufficient to handle the dimension of ${O((\log\log N)^c)}$ that arises here.

Now suppose we have a Siegel zero ${L(\beta,\chi)}$. In this case the bound (5) will not hold in general, and hence also (6) will not hold either. Here, the usual way out (while still maintaining effective estimates) is to approximate ${\mu}$ not by ${0}$, but rather by a more complicated approximant ${\mu_{\hbox{Siegel}}}$ that takes the Siegel zero into account, and in particular is such that one has the (effective) pseudopolynomial bound

$\displaystyle \| (\mu - \mu_{\hbox{Siegel}}) 1_{a \hbox{ mod } q}\|_{U^1([N])} \ll \exp(-\log^c N) \ \ \ \ \ (7)$

for all residue classes ${a \hbox{ mod } q}$. The Siegel approximant to ${\mu}$ is actually a little bit complicated, and to our knowledge the first appearance of this sort of approximant only appears as late as this 2010 paper of Germán and Katai. Our version of this approximant is defined as the multiplicative function such that

$\displaystyle \mu_{\hbox{Siegel}}(p^j) = \mu(p^j)$

when ${p < Q}$, and

$\displaystyle \mu_{\hbox{Siegel}}(n) = \alpha n^{\beta-1} \chi(n)$

when ${n}$ is coprime to all primes ${p, and ${\alpha}$ is a normalising constant given by the formula

$\displaystyle \alpha := \frac{1}{L'(\beta,\chi)} \prod_{p

(this constant ends up being of size ${O(1)}$ and plays only a minor role in the analysis). This is a rather complicated formula, but it seems to be virtually the only choice of approximant that allows for bounds such as (7) to hold. (This is the one aspect of the problem where the von Mangoldt theory is simpler than the Möbius theory, as in the former one only needs to work with very rough numbers for which one does not need to make any special accommodations for the behavior at small primes when introducing the Siegel correction term.) With this starting point it is then possible to repeat the analysis of my previous papers with Ben and obtain the pseudopolynomial discorrelation bound

$\displaystyle \mathop{\bf E}_{n \in [N]} (\mu - \mu_{\hbox{Siegel}})(n) \overline{F}(g(n) \Gamma) \ll \exp(-\log^c N)$

for ${F(g(n)\Gamma)}$ as before, which when combined with Manners’ inverse theorem gives the doubly logarithmic bound

$\displaystyle \| \mu - \mu_{\hbox{Siegel}} \|_{U^k([N])} \ll (\log\log N)^{-c_k}.$

Meanwhile, a direct sieve-theoretic computation ends up giving the singly logarithmic bound

$\displaystyle \| \mu_{\hbox{Siegel}} \|_{U^k([N])} \ll \log^{-c_k} N$

(indeed, there is a good chance that one could improve the bounds even further, though it is not helpful for this current argument to do so). Theorem 1 then follows from the triangle inequality for the Gowers norm. It is interesting that the Siegel approximant ${\mu_{\hbox{Siegel}}}$ seems to play a rather essential component in the proof, even if it is absent in the final statement. We note that this approximant seems to be a useful tool to explore the “illusory world” of the Siegel zero further; see for instance the recent paper of Chinis for some work in this direction.

For the analogous problem with the von Mangoldt function (assuming a Siegel zero for sake of discussion), the approximant ${\Lambda_{\hbox{Siegel}}}$ is simpler; we ended up using

$\displaystyle \Lambda_{\hbox{Siegel}}(n) = \Lambda_{\hbox{Cram\'er}}(n) (1 - n^{\beta-1} \chi(n))$

which allows one to state the standard prime number theorem in arithmetic progressions with classical error term and Siegel zero term compactly as

$\displaystyle \| (\Lambda - \Lambda_{\hbox{Siegel}}) 1_{a \hbox{ mod } q}\|_{U^1([N])} \ll \exp(-\log^c N).$

Routine modifications of previous arguments also give

$\displaystyle \mathop{\bf E}_{n \in [N]} (\Lambda - \Lambda_{\hbox{Siegel}})(n) \overline{F}(g(n) \Gamma) \ll \exp(-\log^c N) \ \ \ \ \ (8)$

and

$\displaystyle \| \Lambda_{\hbox{Siegel}} \|_{U^k([N])} \ll \log^{-c_k} N.$

The one tricky new step is getting from the discorrelation estimate (8) to the Gowers uniformity estimate

$\displaystyle \| \Lambda - \Lambda_{\hbox{Siegel}} \|_{U^k([N])} \ll (\log\log N)^{-c_k}.$

One cannot directly apply Manners’ inverse theorem here because ${\Lambda}$ and ${\Lambda_{\hbox{Siegel}}}$ are unbounded. There is a standard tool for getting around this issue, now known as the dense model theorem, which is the standard engine powering the transference principle from theorems about bounded functions to theorems about certain types of unbounded functions. However the quantitative versions of the dense model theorem in the literature are expensive and would basically weaken the doubly logarithmic gain here to a triply logarithmic one. Instead, we bypass the dense model theorem and directly transfer the inverse theorem for bounded functions to an inverse theorem for unbounded functions by using the densification approach to transference introduced by Conlon, Fox, and Zhao. This technique turns out to be quantitatively quite efficient (the dependencies of the main parameters in the transference are polynomial in nature), and also has the technical advantage of avoiding the somewhat tricky “correlation condition” present in early transference results which are also not beneficial for quantitative bounds.

In principle, the above results can be improved for ${k=3}$ due to the stronger quantitative inverse theorems in the ${U^3}$ setting. However, there is a bottleneck that prevents us from achieving this, namely that the equidistribution theory of two-step nilmanifolds has exponents which are exponential in the dimension rather than polynomial in the dimension, and as a consequence we were unable to improve upon the doubly logarithmic results. Specifically, if one is given a sequence of bracket quadratics such as ${\lfloor \alpha_1 n \rfloor \beta_1 n, \dots, \lfloor \alpha_d n \rfloor \beta_d n}$ that fails to be ${\delta}$-equidistributed, one would need to establish a nontrivial linear relationship modulo 1 between the ${\alpha_1,\beta_1,\dots,\alpha_d,\beta_d}$ (up to errors of ${O(1/N)}$), where the coefficients are of size ${O(\delta^{-d^{O(1)}})}$; current methods only give coefficient bounds of the form ${O(\delta^{-\exp(d^{O(1)})})}$. An old result of Schmidt demonstrates proof of concept that these sorts of polynomial dependencies on exponents is possible in principle, but actually implementing Schmidt’s methods here seems to be a quite non-trivial task. There is also another possible route to removing a logarithm, which is to strengthen the inverse ${U^3}$ theorem to make the dimension of the nilmanifold logarithmic in the uniformity parameter ${\delta}$ rather than polynomial. Again, the Freiman-Bilu theorem (see for instance this paper of Ben and myself) demonstrates proof of concept that such an improvement in dimension is possible, but some work would be needed to implement it.

Kaisa Matomäki, Maksym Radziwill, Xuancheng Shao, Joni Teräväinen, and myself have just uploaded to the arXiv our preprint “Singmaster’s conjecture in the interior of Pascal’s triangle“. This paper leverages the theory of exponential sums over primes to make progress on a well known conjecture of Singmaster which asserts that any natural number larger than ${1}$ appears at most a bounded number of times in Pascal’s triangle. That is to say, for any integer ${t \geq 2}$, there are at most ${O(1)}$ solutions to the equation

$\displaystyle \binom{n}{m} = t \ \ \ \ \ (1)$

with ${1 \leq m < n}$. Currently, the largest number of solutions that is known to be attainable is eight, with ${t}$ equal to

$\displaystyle 3003 = \binom{3003}{1} = \binom{78}{2} = \binom{15}{5} = \binom{14}{6} = \binom{14}{8} = \binom{15}{10}$

$\displaystyle = \binom{78}{76} = \binom{3003}{3002}.$

Because of the symmetry ${\binom{n}{m} = \binom{n}{n-m}}$ of Pascal’s triangle it is natural to restrict attention to the left half ${1 \leq m \leq n/2}$ of the triangle.

Our main result settles this conjecture in the “interior” region of the triangle:

Theorem 1 (Singmaster’s conjecture in the interior of the triangle) If ${0 < \varepsilon < 1}$ and ${t}$ is sufficiently large depending on ${\varepsilon}$, there are at most two solutions to (1) in the region

$\displaystyle \exp( \log^{2/3+\varepsilon} n ) \leq m \leq n/2 \ \ \ \ \ (2)$

and hence at most four in the region

$\displaystyle \exp( \log^{2/3+\varepsilon} n ) \leq m \leq n - \exp( \log^{2/3+\varepsilon} n ).$

Also, there is at most one solution in the region

$\displaystyle \exp( \log^{2/3+\varepsilon} n ) \leq m \leq n/\exp(\log^{1-\varepsilon} n ).$

To verify Singmaster’s conjecture in full, it thus suffices in view of this result to verify the conjecture in the boundary region

$\displaystyle 2 \leq m < \exp(\log^{2/3+\varepsilon} n) \ \ \ \ \ (3)$

(or equivalently ${n - \exp(\log^{2/3+\varepsilon} n) < m \leq n}$); we have deleted the ${m=1}$ case as it of course automatically supplies exactly one solution to (1). It is in fact possible that for ${t}$ sufficiently large there are no further collisions ${\binom{n}{m} = \binom{n'}{m'}=t}$ for ${(n,m), (n',m')}$ in the region (3), in which case there would never be more than eight solutions to (1) for sufficiently large ${t}$. This is latter claim known for bounded values of ${m,m'}$ by Beukers, Shorey, and Tildeman, with the main tool used being Siegel’s theorem on integral points.

The upper bound of two here for the number of solutions in the region (2) is best possible, due to the infinite family of solutions to the equation

$\displaystyle \binom{n+1}{m+1} = \binom{n}{m+2} \ \ \ \ \ (4)$

coming from ${n = F_{2j+2} F_{2j+3}-1}$, ${m = F_{2j} F_{2j+3}-1}$ and ${F_j}$ is the ${j^{th}}$ Fibonacci number.

The appearance of the quantity ${\exp( \log^{2/3+\varepsilon} n )}$ in Theorem 1 may be familiar to readers that are acquainted with Vinogradov’s bounds on exponential sums, which ends up being the main new ingredient in our arguments. In principle this threshold could be lowered if we had stronger bounds on exponential sums.

To try to control solutions to (1) we use a combination of “Archimedean” and “non-Archimedean” approaches. In the “Archimedean” approach (following earlier work of Kane on this problem) we view ${n,m}$ primarily as real numbers rather than integers, and express (1) in terms of the Gamma function as

$\displaystyle \frac{\Gamma(n+1)}{\Gamma(m+1) \Gamma(n-m+1)} = t.$

One can use this equation to solve for ${n}$ in terms of ${m,t}$ as

$\displaystyle n = f_t(m)$

for a certain real analytic function ${f_t}$ whose asymptotics are easily computable (for instance one has the asymptotic ${f_t(m) \asymp m t^{1/m}}$). One can then view the problem as one of trying to control the number of lattice points on the graph ${\{ (m,f_t(m)): m \in {\bf R} \}}$. Here we can take advantage of the fact that in the regime ${m \leq f_t(m)/2}$ (which corresponds to working in the left half ${m \leq n/2}$ of Pascal’s triangle), the function ${f_t}$ can be shown to be convex, but not too convex, in the sense that one has both upper and lower bounds on the second derivative of ${f_t}$ (in fact one can show that ${f''_t(m) \asymp f_t(m) (\log t/m^2)^2}$). This can be used to preclude the possibility of having a cluster of three or more nearby lattice points on the graph ${\{ (m,f_t(m)): m \in {\bf R} \}}$, basically because the area subtended by the triangle connecting three of these points would lie between ${0}$ and ${1/2}$, contradicting Pick’s theorem. Developing these ideas, we were able to show

Proposition 2 Let ${\varepsilon>0}$, and suppose ${t}$ is sufficiently large depending on ${\varepsilon}$. If ${(m,n)}$ is a solution to (1) in the left half ${m \leq n/2}$ of Pascal’s triangle, then there is at most one other solution ${(m',n')}$ to this equation in the left half with

$\displaystyle |m-m'| + |n-n'| \ll \exp( (\log\log t)^{1-\varepsilon} ).$

Again, the example of (4) shows that a cluster of two solutions is certainly possible; the convexity argument only kicks in once one has a cluster of three or more solutions.

To finish the proof of Theorem 1, one has to show that any two solutions ${(m,n), (m',n')}$ to (1) in the region of interest must be close enough for the above proposition to apply. Here we switch to the “non-Archimedean” approach, in which we look at the ${p}$-adic valuations ${\nu_p( \binom{n}{m} )}$ of the binomial coefficients, defined as the number of times a prime ${p}$ divides ${\binom{n}{m}}$. From the fundamental theorem of arithmetic, a collision

$\displaystyle \binom{n}{m} = \binom{n'}{m'}$

between binomial coefficients occurs if and only if one has agreement of valuations

$\displaystyle \nu_p( \binom{n}{m} ) = \nu_p( \binom{n'}{m'} ). \ \ \ \ \ (5)$

From the Legendre formula

$\displaystyle \nu_p(n!) = \sum_{j=1}^\infty \lfloor \frac{n}{p^j} \rfloor$

we can rewrite this latter identity (5) as

$\displaystyle \sum_{j=1}^\infty \{ \frac{m}{p^j} \} + \{ \frac{n-m}{p^j} \} - \{ \frac{n}{p^j} \} = \sum_{j=1}^\infty \{ \frac{m'}{p^j} \} + \{ \frac{n'-m'}{p^j} \} - \{ \frac{n'}{p^j} \}, \ \ \ \ \ (6)$

where ${\{x\} := x - \lfloor x\rfloor}$ denotes the fractional part of ${x}$. (These sums are not truly infinite, because the summands vanish once ${p^j}$ is larger than ${\max(n,n')}$.)

A key idea in our approach is to view this condition (6) statistically, for instance by viewing ${p}$ as a prime drawn randomly from an interval such as ${[P, P + P \log^{-100} P]}$ for some suitably chosen scale parameter ${P}$, so that the two sides of (6) now become random variables. It then becomes advantageous to compare correlations between these two random variables and some additional test random variable. For instance, if ${n}$ and ${n'}$ are far apart from each other, then one would expect the left-hand side of (6) to have a higher correlation with the fractional part ${\{ \frac{n}{p}\}}$, since this term shows up in the summation on the left-hand side but not the right. Similarly if ${m}$ and ${m'}$ are far apart from each other (although there are some annoying cases one has to treat separately when there is some “unexpected commensurability”, for instance if ${n'-m'}$ is a rational multiple of ${m}$ where the rational has bounded numerator and denominator). In order to execute this strategy, it turns out (after some standard Fourier expansion) that one needs to get good control on exponential sums such as

$\displaystyle \sum_{P \leq p \leq P + P\log^{-100} P} e( \frac{N}{p} + \frac{M}{p^j} )$

for various choices of parameters ${P, N, M, j}$, where ${e(\theta) := e^{2\pi i \theta}}$. Fortunately, the methods of Vinogradov (which more generally can handle sums such as ${\sum_{n \in I} e(f(n))}$ and ${\sum_{p \in I} e(f(p))}$ for various analytic functions ${f}$) can give useful bounds on such sums as long as ${N}$ and ${M}$ are not too large compared to ${P}$; more specifically, Vinogradov’s estimates are non-trivial in the regime ${N,M \ll \exp( \log^{3/2-\varepsilon} P )}$, and this ultimately leads to a distance bound

$\displaystyle m' - m \ll_\varepsilon \exp( \log^{2/3 +\varepsilon}(n+n') )$

between any colliding pair ${(n,m), (n',m')}$ in the left half of Pascal’s triangle, as well as the variant bound

$\displaystyle n' - n \ll_\varepsilon \exp( \log^{2/3 +\varepsilon}(n+n') )$

$\displaystyle m', m \geq \exp( \log^{2/3 +\varepsilon}(n+n') ).$

Comparing these bounds with Proposition 2 and using some basic estimates about the function ${f_t}$, we can conclude Theorem 1.

A modification of the arguments also gives similar results for the equation

$\displaystyle (n)_m = t \ \ \ \ \ (7)$

where ${(n)_m := n (n-1) \dots (n-m+1)}$ is the falling factorial:

Theorem 3 If ${0 < \varepsilon < 1}$ and ${t}$ is sufficiently large depending on ${\varepsilon}$, there are at most two solutions to (7) in the region

$\displaystyle \exp( \log^{2/3+\varepsilon} n ) \leq m < n. \ \ \ \ \ (8)$

Again the upper bound of two is best possible, thanks to identities such as

$\displaystyle (a^2-a)_{a^2-2a} = (a^2-a-1)_{a^2-2a+1}.$

Kaisa Matomäki, Maksym Radziwill, Joni Teräväinen, Tamar Ziegler and I have uploaded to the arXiv our paper Higher uniformity of bounded multiplicative functions in short intervals on average. This paper (which originated from a working group at an AIM workshop on Sarnak’s conjecture) focuses on the local Fourier uniformity conjecture for bounded multiplicative functions such as the Liouville function ${\lambda}$. One form of this conjecture is the assertion that

$\displaystyle \int_0^X \| \lambda \|_{U^k([x,x+H])}\ dx = o(X) \ \ \ \ \ (1)$

as ${X \rightarrow \infty}$ for any fixed ${k \geq 0}$ and any ${H = H(X) \leq X}$ that goes to infinity as ${X \rightarrow \infty}$, where ${U^k([x,x+H])}$ is the (normalized) Gowers uniformity norm. Among other things this conjecture implies (logarithmically averaged version of) the Chowla and Sarnak conjectures for the Liouville function (or the Möbius function), see this previous blog post.

The conjecture gets more difficult as ${k}$ increases, and also becomes more difficult the more slowly ${H}$ grows with ${X}$. The ${k=0}$ conjecture is equivalent to the assertion

$\displaystyle \int_0^X |\sum_{x \leq n \leq x+H} \lambda(n)| \ dx = o(HX)$

which was proven (for arbitrarily slowly growing ${H}$) in a landmark paper of Matomäki and Radziwill, discussed for instance in this blog post.

For ${k=1}$, the conjecture is equivalent to the assertion

$\displaystyle \int_0^X \sup_\alpha |\sum_{x \leq n \leq x+H} \lambda(n) e(-\alpha n)| \ dx = o(HX). \ \ \ \ \ (2)$

This remains open for sufficiently slowly growing ${H}$ (and it would be a major breakthrough in particular if one could obtain this bound for ${H}$ as small as ${\log^\varepsilon X}$ for any fixed ${\varepsilon>0}$, particularly if applicable to more general bounded multiplicative functions than ${\lambda}$, as this would have new implications for a generalization of the Chowla conjecture known as the Elliott conjecture). Recently, Kaisa, Maks and myself were able to establish this conjecture in the range ${H \geq X^\varepsilon}$ (in fact we have since worked out in the current paper that we can get ${H}$ as small as ${\exp(\log^{5/8+\varepsilon} X)}$). In our current paper we establish Fourier uniformity conjecture for higher ${k}$ for the same range of ${H}$. This in particular implies local orthogonality to polynomial phases,

$\displaystyle \int_0^X \sup_{P \in \mathrm{Poly}_{\leq k-1}({\bf R} \rightarrow {\bf R})} |\sum_{x \leq n \leq x+H} \lambda(n) e(-P(n))| \ dx = o(HX) \ \ \ \ \ (3)$

where ${\mathrm{Poly}_{\leq k-1}({\bf R} \rightarrow {\bf R})}$ denotes the polynomials of degree at most ${k-1}$, but the full conjecture is a bit stronger than this, establishing the more general statement

$\displaystyle \int_0^X \sup_{g \in \mathrm{Poly}({\bf R} \rightarrow G)} |\sum_{x \leq n \leq x+H} \lambda(n) \overline{F}(g(n) \Gamma)| \ dx = o(HX) \ \ \ \ \ (4)$

for any degree ${k}$ filtered nilmanifold ${G/\Gamma}$ and Lipschitz function ${F: G/\Gamma \rightarrow {\bf C}}$, where ${g}$ now ranges over polynomial maps from ${{\bf R}}$ to ${G}$. The method of proof follows the same general strategy as in the previous paper with Kaisa and Maks. (The equivalence of (4) and (1) follows from the inverse conjecture for the Gowers norms, proven in this paper.) We quickly sketch first the proof of (3), using very informal language to avoid many technicalities regarding the precise quantitative form of various estimates. If the estimate (3) fails, then we have the correlation estimate

$\displaystyle |\sum_{x \leq n \leq x+H} \lambda(n) e(-P_x(n))| \gg H$

for many ${x \sim X}$ and some polynomial ${P_x}$ depending on ${x}$. The difficulty here is to understand how ${P_x}$ can depend on ${x}$. We write the above correlation estimate more suggestively as

$\displaystyle \lambda(n) \sim_{[x,x+H]} e(P_x(n)).$

Because of the multiplicativity ${\lambda(np) = -\lambda(p)}$ at small primes ${p}$, one expects to have a relation of the form

$\displaystyle e(P_{x'}(p'n)) \sim_{[x/p,x/p+H/p]} e(P_x(pn)) \ \ \ \ \ (5)$

for many ${x,x'}$ for which ${x/p \approx x'/p'}$ for some small primes ${p,p'}$. (This can be formalised using an inequality of Elliott related to the Turan-Kubilius theorem.) This gives a relationship between ${P_x}$ and ${P_{x'}}$ for “edges” ${x,x'}$ in a rather sparse “graph” connecting the elements of say ${[X/2,X]}$. Using some graph theory one can locate some non-trivial “cycles” in this graph that eventually lead (in conjunction to a certain technical but important “Chinese remainder theorem” step to modify the ${P_x}$ to eliminate a rather serious “aliasing” issue that was already discussed in this previous post) to obtain functional equations of the form

$\displaystyle P_x(a_x \cdot) \approx P_x(b_x \cdot)$

for some large and close (but not identical) integers ${a_x,b_x}$, where ${\approx}$ should be viewed as a first approximation (ignoring a certain “profinite” or “major arc” term for simplicity) as “differing by a slowly varying polynomial” and the polynomials ${P_x}$ should now be viewed as taking values on the reals rather than the integers. This functional equation can be solved to obtain a relation of the form

$\displaystyle P_x(t) \approx T_x \log t$

for some real number ${T_x}$ of polynomial size, and with further analysis of the relation (5) one can make ${T_x}$ basically independent of ${x}$. This simplifies (3) to something like

$\displaystyle \int_0^X \sup_{P \in \mathrm{Poly}_{\leq k-1}({\bf R} \rightarrow {\bf R})} |\sum_{x \leq n \leq x+H} \lambda(n) n^{-iT}| \ dx = o(HX)$

and this is now of a form that can be treated by the theorem of Matomäki and Radziwill (because ${n \mapsto \lambda(n) n^{-iT}}$ is a bounded multiplicative function). (Actually because of the profinite term mentioned previously, one also has to insert a Dirichlet character of bounded conductor into this latter conclusion, but we will ignore this technicality.)

Now we apply the same strategy to (4). For abelian ${G}$ the claim follows easily from (3), so we focus on the non-abelian case. One now has a polynomial sequence ${g_x \in \mathrm{Poly}({\bf R} \rightarrow G)}$ attached to many ${x \sim X}$, and after a somewhat complicated adaptation of the above arguments one again ends up with an approximate functional equation

$\displaystyle g_x(a_x \cdot) \Gamma \approx g_x(b_x \cdot) \Gamma \ \ \ \ \ (6)$

where the relation ${\approx}$ is rather technical and will not be detailed here. A new difficulty arises in that there are some unwanted solutions to this equation, such as

$\displaystyle g_x(t) = \gamma^{\frac{\log(a_x t)}{\log(a_x/b_x)}}$

for some ${\gamma \in \Gamma}$, which do not necessarily lead to multiplicative characters like ${n^{-iT}}$ as in the polynomial case, but instead to some unfriendly looking “generalized multiplicative characters” (think of ${e(\lfloor \alpha \log n \rfloor \beta \log n)}$ as a rough caricature). To avoid this problem, we rework the graph theory portion of the argument to produce not just one functional equation of the form (6)for each ${x}$, but many, leading to dilation invariances

$\displaystyle g_x((1+\theta) t) \Gamma \approx g_x(t) \Gamma$

for a “dense” set of ${\theta}$. From a certain amount of Lie algebra theory (ultimately arising from an understanding of the behaviour of the exponential map on nilpotent matrices, and exploiting the hypothesis that ${G}$ is non-abelian) one can conclude that (after some initial preparations to avoid degenerate cases) ${g_x(t)}$ must behave like ${\gamma_x^{\log t}}$ for some central element ${\gamma_x}$ of ${G}$. This eventually brings one back to the multiplicative characters ${n^{-iT}}$ that arose in the polynomial case, and the arguments now proceed as before.

We give two applications of this higher order Fourier uniformity. One regards the growth of the number

$\displaystyle s(k) := |\{ (\lambda(n+1),\dots,\lambda(n+k)): n \in {\bf N} \}|$

of length ${k}$ sign patterns in the Liouville function. The Chowla conjecture implies that ${s(k) = 2^k}$, but even the weaker conjecture of Sarnak that ${s(k) \gg (1+\varepsilon)^k}$ for some ${\varepsilon>0}$ remains open. Until recently, the best asymptotic lower bound on ${s(k)}$ was ${s(k) \gg k^2}$, due to McNamara; with our result, we can now show ${s(k) \gg_A k^A}$ for any ${A}$ (in fact we can get ${s(k) \gg_\varepsilon \exp(\log^{8/5-\varepsilon} k)}$ for any ${\varepsilon>0}$). The idea is to repeat the now-standard argument to exploit multiplicativity at small primes to deduce Chowla-type conjectures from Fourier uniformity conjectures, noting that the Chowla conjecture would give all the sign patterns one could hope for. The usual argument here uses the “entropy decrement argument” to eliminate a certain error term (involving the large but mean zero factor ${p 1_{p|n}-1}$). However the observation is that if there are extremely few sign patterns of length ${k}$, then the entropy decrement argument is unnecessary (there isn’t much entropy to begin with), and a more low-tech moment method argument (similar to the derivation of Chowla’s conjecture from Sarnak’s conjecture, as discussed for instance in this post) gives enough of Chowla’s conjecture to produce plenty of length ${k}$ sign patterns. If there are not extremely few sign patterns of length ${k}$ then we are done anyway. One quirk of this argument is that the sign patterns it produces may only appear exactly once; in contrast with preceding arguments, we were not able to produce a large number of sign patterns that each occur infinitely often.

The second application is to obtain cancellation for various polynomial averages involving the Liouville function ${\lambda}$ or von Mangoldt function ${\Lambda}$, such as

$\displaystyle {\bf E}_{n \leq X} {\bf E}_{m \leq X^{1/d}} \lambda(n+P_1(m)) \lambda(n+P_2(m)) \dots \lambda(n+P_k(m))$

or

$\displaystyle {\bf E}_{n \leq X} {\bf E}_{m \leq X^{1/d}} \lambda(n+P_1(m)) \Lambda(n+P_2(m)) \dots \Lambda(n+P_k(m))$

where ${P_1,\dots,P_k}$ are polynomials of degree at most ${d}$, no two of which differ by a constant (the latter is essential to avoid having to establish the Chowla or Hardy-Littlewood conjectures, which of course remain open). Results of this type were previously obtained by Tamar Ziegler and myself in the “true complexity zero” case when the polynomials ${P}$ had distinct degrees, in which one could use the ${k=0}$ theory of Matomäki and Radziwill; now that higher ${k}$ is available at the scale ${H=X^{1/d}}$ we can now remove this restriction.

Joni Teräväinen and I have just uploaded to the arXiv our paper “Value patterns of multiplicative functions and related sequences“, submitted to Forum of Mathematics, Sigma. This paper explores how to use recent technology on correlations of multiplicative (or nearly multiplicative functions), such as the “entropy decrement method”, in conjunction with techniques from additive combinatorics, to establish new results on the sign patterns of functions such as the Liouville function ${\lambda}$. For instance, with regards to length 5 sign patterns

$\displaystyle (\lambda(n+1),\dots,\lambda(n+5)) \in \{-1,+1\}^5$

of the Liouville function, we can now show that at least ${24}$ of the ${32}$ possible sign patterns in ${\{-1,+1\}^5}$ occur with positive upper density. (Conjecturally, all of them do so, and this is known for all shorter sign patterns, but unfortunately ${24}$ seems to be the limitation of our methods.)

The Liouville function can be written as ${\lambda(n) = e^{2\pi i \Omega(n)/2}}$, where ${\Omega(n)}$ is the number of prime factors of ${n}$ (counting multiplicity). One can also consider the variant ${\lambda_3(n) = e^{2\pi i \Omega(n)/3}}$, which is a completely multiplicative function taking values in the cube roots of unity ${\{1, \omega, \omega^2\}}$. Here we are able to show that all ${27}$ sign patterns in ${\{1,\omega,\omega^2\}}$ occur with positive lower density as sign patterns ${(\lambda_3(n+1), \lambda_3(n+2), \lambda_3(n+3))}$ of this function. The analogous result for ${\lambda}$ was already known (see this paper of Matomäki, Radziwiłł, and myself), and in that case it is even known that all sign patterns occur with equal logarithmic density ${1/8}$ (from this paper of myself and Teräväinen), but these techniques barely fail to handle the ${\lambda_3}$ case by itself (largely because the “parity” arguments used in the case of the Liouville function no longer control three-point correlations in the ${\lambda_3}$ case) and an additional additive combinatorial tool is needed. After applying existing technology (such as entropy decrement methods), the problem roughly speaking reduces to locating patterns ${a \in A_1, a+r \in A_2, a+2r \in A_3}$ for a certain partition ${G = A_1 \cup A_2 \cup A_3}$ of a compact abelian group ${G}$ (think for instance of the unit circle ${G={\bf R}/{\bf Z}}$, although the general case is a bit more complicated, in particular if ${G}$ is disconnected then there is a certain “coprimality” constraint on ${r}$, also we can allow the ${A_1,A_2,A_3}$ to be replaced by any ${A_{c_1}, A_{c_2}, A_{c_3}}$ with ${c_1+c_2+c_3}$ divisible by ${3}$), with each of the ${A_i}$ having measure ${1/3}$. An inequality of Kneser just barely fails to guarantee the existence of such patterns, but by using an inverse theorem for Kneser’s inequality in this previous paper of mine we are able to identify precisely the obstruction for this method to work, and rule it out by an ad hoc method.

The same techniques turn out to also make progress on some conjectures of Erdös-Pomerance and Hildebrand regarding patterns of the largest prime factor ${P^+(n)}$ of a natural number ${n}$. For instance, we improve results of Erdös-Pomerance and of Balog demonstrating that the inequalities

$\displaystyle P^+(n+1) < P^+(n+2) < P^+(n+3)$

and

$\displaystyle P^+(n+1) > P^+(n+2) > P^+(n+3)$

each hold for infinitely many ${n}$, by demonstrating the stronger claims that the inequalities

$\displaystyle P^+(n+1) < P^+(n+2) < P^+(n+3) > P^+(n+4)$

and

$\displaystyle P^+(n+1) > P^+(n+2) > P^+(n+3) < P^+(n+4)$

each hold for a set of ${n}$ of positive lower density. As a variant, we also show that we can find a positive density set of ${n}$ for which

$\displaystyle P^+(n+1), P^+(n+2), P^+(n+3) > n^\gamma$

for any fixed ${\gamma < e^{-1/3} = 0.7165\dots}$ (this improves on a previous result of Hildebrand with ${e^{-1/3}}$ replaced by ${e^{-1/2} = 0.6065\dots}$. A number of other results of this type are also obtained in this paper.

In order to obtain these sorts of results, one needs to extend the entropy decrement technology from the setting of multiplicative functions to that of what we call “weakly stable sets” – sets ${A}$ which have some multiplicative structure, in the sense that (roughly speaking) there is a set ${B}$ such that for all small primes ${p}$, the statements ${n \in A}$ and ${pn \in B}$ are roughly equivalent to each other. For instance, if ${A}$ is a level set ${A = \{ n: \omega(n) = 0 \hbox{ mod } 3 \}}$, one would take ${B = \{ n: \omega(n) = 1 \hbox{ mod } 3 \}}$; if instead ${A}$ is a set of the form ${\{ n: P^+(n) \geq n^\gamma\}}$, then one can take ${B=A}$. When one has such a situation, then very roughly speaking, the entropy decrement argument then allows one to estimate a one-parameter correlation such as

$\displaystyle {\bf E}_n 1_A(n+1) 1_A(n+2) 1_A(n+3)$

with a two-parameter correlation such as

$\displaystyle {\bf E}_n {\bf E}_p 1_B(n+p) 1_B(n+2p) 1_B(n+3p)$

(where we will be deliberately vague as to how we are averaging over ${n}$ and ${p}$), and then the use of the “linear equations in primes” technology of Ben Green, Tamar Ziegler, and myself then allows one to replace this average in turn by something like

$\displaystyle {\bf E}_n {\bf E}_r 1_B(n+r) 1_B(n+2r) 1_B(n+3r)$

where ${r}$ is constrained to be not divisible by small primes but is otherwise quite arbitrary. This latter average can then be attacked by tools from additive combinatorics, such as translation to a continuous group model (using for instance the Furstenberg correspondence principle) followed by tools such as Kneser’s inequality (or inverse theorems to that inequality).

Joni Teräväinen and I have just uploaded to the arXiv our paper “The structure of correlations of multiplicative functions at almost all scales, with applications to the Chowla and Elliott conjectures“. This is a sequel to our previous paper that studied logarithmic correlations of the form

$\displaystyle f(a) := \lim^*_{x \rightarrow \infty} \frac{1}{\log \omega(x)} \sum_{x/\omega(x) \leq n \leq x} \frac{g_1(n+ah_1) \dots g_k(n+ah_k)}{n},$

where ${g_1,\dots,g_k}$ were bounded multiplicative functions, ${h_1,\dots,h_k \rightarrow \infty}$ were fixed shifts, ${1 \leq \omega(x) \leq x}$ was a quantity going off to infinity, and ${\lim^*}$ was a generalised limit functional. Our main technical result asserted that these correlations were necessarily the uniform limit of periodic functions ${f_i}$. Furthermore, if ${g_1 \dots g_k}$ (weakly) pretended to be a Dirichlet character ${\chi}$, then the ${f_i}$ could be chosen to be ${\chi}$isotypic in the sense that ${f_i(ab) = f_i(a) \chi(b)}$ whenever ${a,b}$ are integers with ${b}$ coprime to the periods of ${\chi}$ and ${f_i}$; otherwise, if ${g_1 \dots g_k}$ did not weakly pretend to be any Dirichlet character ${\chi}$, then ${f}$ vanished completely. This was then used to verify several cases of the logarithmically averaged Elliott and Chowla conjectures.

The purpose of this paper was to investigate the extent to which the methods could be extended to non-logarithmically averaged settings. For our main technical result, we now considered the unweighted averages

$\displaystyle f_d(a) := \lim^*_{x \rightarrow \infty} \frac{1}{x/d} \sum_{n \leq x/d} g_1(n+ah_1) \dots g_k(n+ah_k),$

where ${d>1}$ is an additional parameter. Our main result was now as follows. If ${g_1 \dots g_k}$ did not weakly pretend to be a twisted Dirichlet character ${n \mapsto \chi(n) n^{it}}$, then ${f_d(a)}$ converged to zero on (doubly logarithmic) average as ${d \rightarrow \infty}$. If instead ${g_1 \dots g_k}$ did pretend to be such a twisted Dirichlet character, then ${f_d(a) d^{it}}$ converged on (doubly logarithmic) average to a limit ${f(a)}$ of ${\chi}$-isotypic functions ${f_i}$. Thus, roughly speaking, one has the approximation

$\displaystyle \lim^*_{x \rightarrow \infty} \frac{1}{x/d} \sum_{n \leq x/d} g_1(n+ah_1) \dots g_k(n+ah_k) \approx f(a) d^{-it}$

for most ${d}$.

Informally, this says that at almost all scales ${x}$ (where “almost all” means “outside of a set of logarithmic density zero”), the non-logarithmic averages behave much like their logarithmic counterparts except for a possible additional twisting by an Archimedean character ${d \mapsto d^{it}}$ (which interacts with the Archimedean parameter ${d}$ in much the same way that the Dirichlet character ${\chi}$ interacts with the non-Archimedean parameter ${a}$). One consequence of this is that most of the recent results on the logarithmically averaged Chowla and Elliott conjectures can now be extended to their non-logarithmically averaged counterparts, so long as one excludes a set of exceptional scales ${x}$ of logarithmic density zero. For instance, the Chowla conjecture

$\displaystyle \lim_{x \rightarrow\infty} \frac{1}{x} \sum_{n \leq x} \lambda(n+h_1) \dots \lambda(n+h_k) = 0$

is now established for ${k}$ either odd or equal to ${2}$, so long as one excludes an exceptional set of scales.

In the logarithmically averaged setup, the main idea was to combine two very different pieces of information on ${f(a)}$. The first, coming from recent results in ergodic theory, was to show that ${f(a)}$ was well approximated in some sense by a nilsequence. The second was to use the “entropy decrement argument” to obtain an approximate isotopy property of the form

$\displaystyle f(a) g_1 \dots g_k(p)\approx f(ap)$

for “most” primes ${p}$ and integers ${a}$. Combining the two facts, one eventually finds that only the almost periodic components of the nilsequence are relevant.

In the current situation, each ${a \mapsto f_d(a)}$ is approximated by a nilsequence, but the nilsequence can vary with ${d}$ (although there is some useful “Lipschitz continuity” of this nilsequence with respect to the ${d}$ parameter). Meanwhile, the entropy decrement argument gives an approximation basically of the form

$\displaystyle f_{dp}(a) g_1 \dots g_k(p)\approx f_d(ap)$

for “most” ${d,p,a}$. The arguments then proceed largely as in the logarithmically averaged case. A key lemma to handle the dependence on the new parameter ${d}$ is the following cohomological statement: if one has a map ${\alpha: (0,+\infty) \rightarrow S^1}$ that was a quasimorphism in the sense that ${\alpha(xy) = \alpha(x) \alpha(y) + O(\varepsilon)}$ for all ${x,y \in (0,+\infty)}$ and some small ${\varepsilon}$, then there exists a real number ${t}$ such that ${\alpha(x) = x^{it} + O(\varepsilon)}$ for all small ${\varepsilon}$. This is achieved by applying a standard “cocycle averaging argument” to the cocycle ${(x,y) \mapsto \alpha(xy) \alpha(x)^{-1} \alpha(y)^{-1}}$.

It would of course be desirable to not have the set of exceptional scales. We only know of one (implausible) scenario in which we can do this, namely when one has far fewer (in particular, subexponentially many) sign patterns for (say) the Liouville function than predicted by the Chowla conjecture. In this scenario (roughly analogous to the “Siegel zero” scenario in multiplicative number theory), the entropy of the Liouville sign patterns is so small that the entropy decrement argument becomes powerful enough to control all scales rather than almost all scales. On the other hand, this scenario seems to be self-defeating, in that it allows one to establish a large number of cases of the Chowla conjecture, and the full Chowla conjecture is inconsistent with having unusually few sign patterns. Still it hints that future work in this direction may need to split into “low entropy” and “high entropy” cases, in analogy to how many arguments in multiplicative number theory have to split into the “Siegel zero” and “no Siegel zero” cases.

Joni Teräväinen and I have just uploaded to the arXiv our paper “Odd order cases of the logarithmically averaged Chowla conjecture“, submitted to J. Numb. Thy. Bordeaux. This paper gives an alternate route to one of the main results of our previous paper, and more specifically reproves the asymptotic

$\displaystyle \sum_{n \leq x} \frac{\lambda(n+h_1) \dots \lambda(n+h_k)}{n} = o(\log x) \ \ \ \ \ (1)$

for all odd ${k}$ and all integers ${h_1,\dots,h_k}$ (that is to say, all the odd order cases of the logarithmically averaged Chowla conjecture). Our previous argument relies heavily on some deep ergodic theory results of Bergelson-Host-Kra, Leibman, and Le (and was applicable to more general multiplicative functions than the Liouville function ${\lambda}$); here we give a shorter proof that avoids ergodic theory (but instead requires the Gowers uniformity of the (W-tricked) von Mangoldt function, established in several papers of Ben Green, Tamar Ziegler, and myself). The proof follows the lines sketched in the previous blog post. In principle, due to the avoidance of ergodic theory, the arguments here have a greater chance to be made quantitative; however, at present the known bounds on the Gowers uniformity of the von Mangoldt function are qualitative, except at the ${U^2}$ level, which is unfortunate since the first non-trivial odd case ${k=3}$ requires quantitative control on the ${U^3}$ level. (But it may be possible to make the Gowers uniformity bounds for ${U^3}$ quantitative if one assumes GRH, although when one puts everything together, the actual decay rate obtained in (1) is likely to be poor.)

Joni Teräväinen and I have just uploaded to the arXiv our paper “The structure of logarithmically averaged correlations of multiplicative functions, with applications to the Chowla and Elliott conjectures“, submitted to Duke Mathematical Journal. This paper builds upon my previous paper in which I introduced an “entropy decrement method” to prove the two-point (logarithmically averaged) cases of the Chowla and Elliott conjectures. A bit more specifically, I showed that

$\displaystyle \lim_{m \rightarrow \infty} \frac{1}{\log \omega_m} \sum_{x_m/\omega_m \leq n \leq x_m} \frac{g_0(n+h_0) g_1(n+h_1)}{n} = 0$

whenever ${1 \leq \omega_m \leq x_m}$ were sequences going to infinity, ${h_0,h_1}$ were distinct integers, and ${g_0,g_1: {\bf N} \rightarrow {\bf C}}$ were ${1}$-bounded multiplicative functions which were non-pretentious in the sense that

$\displaystyle \liminf_{X \rightarrow \infty} \inf_{|t_j| \leq X} \sum_{p \leq X} \frac{1-\mathrm{Re}( g_j(p) \overline{\chi_j}(p) p^{it_j})}{p} = \infty \ \ \ \ \ (1)$

for all Dirichlet characters ${\chi_j}$ and for ${j=0,1}$. Thus, for instance, one had the logarithmically averaged two-point Chowla conjecture

$\displaystyle \sum_{n \leq x} \frac{\lambda(n) \lambda(n+h)}{n} = o(\log x)$

for fixed any non-zero ${h}$, where ${\lambda}$ was the Liouville function.

One would certainly like to extend these results to higher order correlations than the two-point correlations. This looks to be difficult (though perhaps not completely impossible if one allows for logarithmic averaging): in a previous paper I showed that achieving this in the context of the Liouville function would be equivalent to resolving the logarithmically averaged Sarnak conjecture, as well as establishing logarithmically averaged local Gowers uniformity of the Liouville function. However, in this paper we are able to avoid having to resolve these difficult conjectures to obtain partial results towards the (logarithmically averaged) Chowla and Elliott conjecture. For the Chowla conjecture, we can obtain all odd order correlations, in that

$\displaystyle \sum_{n \leq x} \frac{\lambda(n+h_1) \dots \lambda(n+h_k)}{n} = o(\log x) \ \ \ \ \ (2)$

for all odd ${k}$ and all integers ${h_1,\dots,h_k}$ (which, in the odd order case, are no longer required to be distinct). (Superficially, this looks like we have resolved “half of the cases” of the logarithmically averaged Chowla conjecture; but it seems the odd order correlations are significantly easier than the even order ones. For instance, because of the Katai-Bourgain-Sarnak-Ziegler criterion, one can basically deduce the odd order cases of (2) from the even order cases (after allowing for some dilations in the argument ${n}$).

For the more general Elliott conjecture, we can show that

$\displaystyle \lim_{m \rightarrow \infty} \frac{1}{\log \omega_m} \sum_{x_m/\omega_m \leq n \leq x_m} \frac{g_1(n+h_1) \dots g_k(n+h_k)}{n} = 0$

for any ${k}$, any integers ${h_1,\dots,h_k}$ and any bounded multiplicative functions ${g_1,\dots,g_k}$, unless the product ${g_1 \dots g_k}$ weakly pretends to be a Dirichlet character ${\chi}$ in the sense that

$\displaystyle \sum_{p \leq X} \frac{1 - \hbox{Re}( g_1 \dots g_k(p) \overline{\chi}(p)}{p} = o(\log\log X).$

This can be seen to imply (2) as a special case. Even when ${g_1,\dots,g_k}$ does pretend to be a Dirichlet character ${\chi}$, we can still say something: if the limits

$\displaystyle f(a) := \lim_{m \rightarrow \infty} \frac{1}{\log \omega_m} \sum_{x_m/\omega_m \leq n \leq x_m} \frac{g_1(n+ah_1) \dots g_k(n+ah_k)}{n}$

exist for each ${a \in {\bf Z}}$ (which can be guaranteed if we pass to a suitable subsequence), then ${f}$ is the uniform limit of periodic functions ${f_i}$, each of which is ${\chi}$isotypic in the sense that ${f_i(ab) = f_i(a) \chi(b)}$ whenever ${a,b}$ are integers with ${b}$ coprime to the periods of ${\chi}$ and ${f_i}$. This does not pin down the value of any single correlation ${f(a)}$, but does put significant constraints on how these correlations may vary with ${a}$.

Among other things, this allows us to show that all ${16}$ possible length four sign patterns ${(\lambda(n+1),\dots,\lambda(n+4)) \in \{-1,+1\}^4}$ of the Liouville function occur with positive density, and all ${65}$ possible length four sign patterns ${(\mu(n+1),\dots,\mu(n+4)) \in \{-1,0,+1\}^4 \backslash \{-1,+1\}^4}$ occur with the conjectured logarithmic density. (In a previous paper with Matomaki and Radziwill, we obtained comparable results for length three patterns of Liouville and length two patterns of Möbius.)

To describe the argument, let us focus for simplicity on the case of the Liouville correlations

$\displaystyle f(a) := \lim_{X \rightarrow \infty} \frac{1}{\log X} \sum_{n \leq X} \frac{\lambda(n) \lambda(n+a) \dots \lambda(n+(k-1)a)}{n}, \ \ \ \ \ (3)$

assuming for sake of discussion that all limits exist. (In the paper, we instead use the device of generalised limits, as discussed in this previous post.) The idea is to combine together two rather different ways to control this function ${f}$. The first proceeds by the entropy decrement method mentioned earlier, which roughly speaking works as follows. Firstly, we pick a prime ${p}$ and observe that ${\lambda(pn)=-\lambda(n)}$ for any ${n}$, which allows us to rewrite (3) as

$\displaystyle (-1)^k f(a) = \lim_{X \rightarrow \infty} \frac{1}{\log X}$

$\displaystyle \sum_{n \leq X} \frac{\lambda(pn) \lambda(pn+ap) \dots \lambda(pn+(k-1)ap)}{n}.$

Making the change of variables ${n' = pn}$, we obtain

$\displaystyle (-1)^k f(a) = \lim_{X \rightarrow \infty} \frac{1}{\log X}$

$\displaystyle \sum_{n' \leq pX} \frac{\lambda(n') \lambda(n'+ap) \dots \lambda(n'+(k-1)ap)}{n'} p 1_{p|n'}.$

The difference between ${n' \leq pX}$ and ${n' \leq X}$ is negligible in the limit (here is where we crucially rely on the log-averaging), hence

$\displaystyle (-1)^k f(a) = \lim_{X \rightarrow \infty} \frac{1}{\log X} \sum_{n \leq X} \frac{\lambda(n) \lambda(n+ap) \dots \lambda(n+(k-1)ap)}{n} p 1_{p|n}$

and thus by (3) we have

$\displaystyle (-1)^k f(a) = f(ap) + \lim_{X \rightarrow \infty} \frac{1}{\log X}$

$\displaystyle \sum_{n \leq X} \frac{\lambda(n) \lambda(n+ap) \dots \lambda(n+(k-1)ap)}{n} (p 1_{p|n}-1).$

The entropy decrement argument can be used to show that the latter limit is small for most ${p}$ (roughly speaking, this is because the factors ${p 1_{p|n}-1}$ behave like independent random variables as ${p}$ varies, so that concentration of measure results such as Hoeffding’s inequality can apply, after using entropy inequalities to decouple somewhat these random variables from the ${\lambda}$ factors). We thus obtain the approximate isotopy property

$\displaystyle (-1)^k f(a) \approx f(ap) \ \ \ \ \ (4)$

for most ${a}$ and ${p}$.

On the other hand, by the Furstenberg correspondence principle (as discussed in these previous posts), it is possible to express ${f(a)}$ as a multiple correlation

$\displaystyle f(a) = \int_X g(x) g(T^a x) \dots g(T^{(k-1)a} x)\ d\mu(x)$

for some probability space ${(X,\mu)}$ equipped with a measure-preserving invertible map ${T: X \rightarrow X}$. Using results of Bergelson-Host-Kra, Leibman, and Le, this allows us to obtain a decomposition of the form

$\displaystyle f(a) = f_1(a) + f_2(a) \ \ \ \ \ (5)$

where ${f_1}$ is a nilsequence, and ${f_2}$ goes to zero in density (even along the primes, or constant multiples of the primes). The original work of Bergelson-Host-Kra required ergodicity on ${X}$, which is very definitely a hypothesis that is not available here; however, the later work of Leibman removed this hypothesis, and the work of Le refined the control on ${f_1}$ so that one still has good control when restricting to primes, or constant multiples of primes.

Ignoring the small error ${f_2(a)}$, we can now combine (5) to conclude that

$\displaystyle f(a) \approx (-1)^k f_1(ap).$

Using the equidistribution theory of nilsequences (as developed in this previous paper of Ben Green and myself), one can break up ${f_1}$ further into a periodic piece ${f_0}$ and an “irrational” or “minor arc” piece ${f_3}$. The contribution of the minor arc piece ${f_3}$ can be shown to mostly cancel itself out after dilating by primes ${p}$ and averaging, thanks to Vinogradov-type bilinear sum estimates (transferred to the primes). So we end up with

$\displaystyle f(a) \approx (-1)^k f_0(ap),$

which already shows (heuristically, at least) the claim that ${f}$ can be approximated by periodic functions ${f_0}$ which are isotopic in the sense that

$\displaystyle f_0(a) \approx (-1)^k f_0(ap).$

But if ${k}$ is odd, one can use Dirichlet’s theorem on primes in arithmetic progressions to restrict to primes ${p}$ that are ${1}$ modulo the period of ${f_0}$, and conclude now that ${f_0}$ vanishes identically, which (heuristically, at least) gives (2).

The same sort of argument works to give the more general bounds on correlations of bounded multiplicative functions. But for the specific task of proving (2), we initially used a slightly different argument that avoids using the ergodic theory machinery of Bergelson-Host-Kra, Leibman, and Le, but replaces it instead with the Gowers uniformity norm theory used to count linear equations in primes. Basically, by averaging (4) in ${p}$ using the “${W}$-trick”, as well as known facts about the Gowers uniformity of the von Mangoldt function, one can obtain an approximation of the form

$\displaystyle (-1)^k f(a) \approx {\bf E}_{b: (b,W)=1} f(ab)$

where ${b}$ ranges over a large range of integers coprime to some primorial ${W = \prod_{p \leq w} p}$. On the other hand, by iterating (4) we have

$\displaystyle f(a) \approx f(apq)$

for most semiprimes ${pq}$, and by again averaging over semiprimes one can obtain an approximation of the form

$\displaystyle f(a) \approx {\bf E}_{b: (b,W)=1} f(ab).$

For ${k}$ odd, one can combine the two approximations to conclude that ${f(a)=0}$. (This argument is not given in the current paper, but we plan to detail it in a subsequent one.)