1 Introduction
Let $\mu $ and $\Lambda $ denote the Möbius and von Mangoldt functions, respectively, defined by
Also, let $\lambda $ be the Liouville function given by $\lambda (n)=(-1)^{\Omega (n)}$, where $\Omega (n)$ is the total number of prime factors of n with multiplicities. For technical convenience, we extend these functions to the non-positive integers as zero (the choice of the extension makes no difference). Recall that the prime number theorem is equivalent to the average bounds $\sum _{n\le X}\mu (n) = o(X)$ and $\sum _{n\le X}\Lambda (n) = (1+o(1))X$. The influential conjectures of Chowla [Reference Chowla2] and Hardy–Littlewood [Reference Hardy and Littlewood6] assert that for any fixed tuple of distinct integers $h_1,\ldots ,h_k$,
where $\mathcal {H}=\{h_1,\ldots , h_k\}$ and the singular series is given by
where $\nu _p(\mathcal {H}) = |\{h\;(\text {mod }p) : h\in \mathcal {H}\}|$. Both conjectures remain open for any $k\ge 2$.
It is natural to consider the following hybrid conjecture, which, following [Reference Lichtman10] and [Reference Tao and Teräväinen20], we call the Hardy–Littlewood–Chowla conjecture.
Conjecture 1.1 (Hardy–Littlewood–Chowla).
Let $k,\ell \geq 0$, and let $h_1,\ldots ,h_k$, $a_1,\ldots , a_\ell $ be distinct integers. Then we haveFootnote 1
Here, $\mathfrak {S}=\mathfrak {S}(\{a_1,\ldots , a_\ell \})$ as in (1.1) if $k=0$, and $\mathfrak {S}=0$ if $k>0$.
The ‘pure’ cases $k=0$ and $\ell =0$ specialise to the original conjectures of Hardy–Littlewood and of Chowla, respectively. We remark that under the hypothetical assumption of infinitely many Siegel zeros, Conjecture 1.1 was recently verified for $\ell \leq 2$ by Tao and the second author [Reference Tao and Teräväinen20] (generalising works of Heath-Brown [Reference Heath-Brown7] and Chinis [Reference Chinis1]). In the current paper, we will be concerned with unconditional results.
Our main result is an averaged form of Conjecture 1.1 for the genuinely ‘hybrid’ cases $k,\ell \ge 1$.
Theorem 1.2 (Hardy–Littlewood–Chowla on average).
Let $\varepsilon>0$ and $k,\ell \geq 1$ be fixed, and let $h_2,\ldots ,h_{k}$, $a_1,\ldots ,a_{\ell }$ be fixed and distinct positive integers.
(i) Let $(\log X)^{\ell +\varepsilon }\leq H\leq \exp ((\log X)^{a})$ with $a=a(\varepsilon ,\ell )>0$ small enough. Then
(1.3)$$ \begin{align} \sum_{h_1\le H}\bigg|\sum_{n\leq X}\mu(n+h_1)\cdots \mu(n+h_k)\Lambda(n+a_1)\cdots\Lambda(n+a_{\ell})\bigg| \ \ll \ HX\,\frac{\log \log H}{\log H}. \end{align} $$(ii) Let $C\geq 1$ be fixed, and let $(\log X)^{\ell +\varepsilon }\leq H\leq (\log X)^{C}$. There exists an absolute constant $c>0$, such that for any $10^4\ell \varepsilon ^{-1}(\log \log H)/(\log H)\leq \delta \leq c/C$, we have
$$ \begin{align*} \bigg|\sum_{n\leq X}\mu(n+h_1)\cdots \mu(n+h_k)\Lambda(n+a_1)\cdots\Lambda(n+a_{\ell})\bigg|\leq \delta X \end{align*} $$for all except $\ll H^{1-c\delta \varepsilon /\ell }$ values of $h_1\leq H$.
In particular, (1.2) holds for all but $o(H)$ values of $h_1\leq H$ (and the exceptional set can be taken to be nearly power saving).
As is clear from the proof, Theorem 1.2 holds equally well with the Liouville function in place of the Möbius function.
Remark 1.3. It is likely that with some extra effort (in particular, refining Proposition 2.1 for $\mu $ in the spirit of [Reference Lichtman10, Theorem 2.2]), Theorem 1.2(ii) could be extended to the regime $(\log X)^{\ell +\varepsilon }\leq H\leq X$. However, our main interest here is in taking H as small as possible.
Earlier, Matomäki, Radziwiłł and Tao [Reference Matomäki, Radziwiłł and Tao12] proved the case $\ell =0$ of Conjecture 1.1 for almost all $h_1\leq H$, with $H=\psi (X)$ tending to infinity arbitrarily slowly. In [Reference Matomäki, Radziwiłł and Tao13], they considered the case $k=0$, $\ell =2$ and proved the conjecture for almost all $h_1\leq H$, with $H\geq X^{8/33+\varepsilon }$. The first author [Reference Lichtman10] obtained cancellation in the range $H\geq (\log X)^{\psi (X)}$, implied by the stronger quantitative bound
The simplest hybrid case $k=\ell =1$ reduces to the Möbius function on shifted primes. It is a folklore conjecture and a well-known model case for the parity problem in sieve theory that
for any fixed shift $h\neq 0$. This has appeared in print (for $h=1$) at least since Hildebrand [Reference Hildebrand9] (see also Pintz [Reference Pintz18] and Murty–Vatwani [Reference R. Murty and Vatwani16, Equation (1.2)]). Theorem 1.2 directly implies an averaged form of this conjecture for $H\ge (\log X)^{1+\varepsilon }$.
Corollary 1.4. Let $\varepsilon>0$. Then, for $X\geq H\geq (\log X)^{1+\varepsilon }$, we have
for all except $o(H)$ values of $h\leq H$.
This improves on work of the first author [Reference Lichtman10] that established Corollary 1.4 when $H\geq (\log X)^{\psi (X)}$ for any function $\psi (X)$ tending to infinity with X.
1.1 Other multiplicative functions
We also consider a variant of Conjecture 1.1, where the occurrences of the Möbius function are replaced with other 1-bounded multiplicative functions $f_i:\mathbb {N}\to \mathbb {C}$, with $f_1$ not pretending to be a twisted character $\chi (n)n^{it}$ for any $\chi\ \pmod q$ and $t\in \mathbb {R}$. Here, following Granville and Soundararajan [Reference Granville and Soundararajan5], pretentiousness is measured by the pretentious distance
and the related quantity
The following generalisation of Conjecture 1.1 is closely related to Elliott’s conjecture [Reference Elliott3] on correlations of multiplicative functions (in fact, the case $\ell =0$ is precisely Elliott’s conjecture), so we shall call it the Hardy–Littlewood–Elliott conjecture.
Conjecture 1.5 (Hardy–Littlewood–Elliott).
Let $h_1,\ldots , h_k,a_1,\ldots , a_{\ell }$ be distinct integers. Fix 1-bounded multiplicative functions $f_1,\ldots , f_k$. Suppose that $f_1$ is non-pretentious in the sense that
for any $Q\geq 1$. Then we have
The case $\ell =0$ of this is Elliott’s conjecture (in the slightly corrected formulation of [Reference Tao and Teräväinen19, Conjecture 1.3]).
We extend our results to non-pretentious multiplicative functions in the regime $H\ge (\log X)^{\ell +\varepsilon }$.
Theorem 1.6 (Hardy–Littlewood–Elliott on average).
Let $\varepsilon>0$, $k,\ell \geq 1$ be fixed, and let $h_2,\ldots , h_k,a_1,\ldots , a_{\ell }$ be fixed and distinct positive integers. Let $(\log X)^{\ell +\varepsilon }\leq H\leq \exp ((\log X)^{1/1000})$. Let $f_1,\ldots , f_k$ be 1-bounded multiplicative functions. Then we have
In particular, if $(\log X)^{\ell +\varepsilon } \leq H\leq \exp ((\log X)^{1/1000})$ and
then (1.6) holds for all except $o(H)$ values of $h_1\leq H$.
Remark 1.7. As a well-known consequence of the Vinogradov–Korobov zero-free region for L-functions, for any fixed $\epsilon>0$, $A\geq 1$ we have
Hence, the bound of Theorem 1.6 in the case of $f_1=\mu $ simplifies to
for some constant $a=a(\varepsilon ,\ell )>0$. The same holds with $\lambda $ in place of $\mu $, since (1.7) holds equally well for $\lambda $. Restricting to $\exp ((\log X)^{a})\geq H\geq (\log X)^{\ell +\varepsilon }$, the bound simplifies to $\ll HX(\log \log H)/\log H$. Hence, Theorem 1.2(i) is a special case of Theorem 1.6. The rest of the paper is therefore devoted to the proofs of Theorems 1.2(ii) and 1.6.
Theorem 1.6 improves on the range $H\geq \exp ((\log X)^{5/8+\varepsilon })$, which follows (under a slightly different pretentiousness hypothesis) from Fourier uniformity bounds of Matomäki, Radziwiłł, Tao, Ziegler and the second author [Reference Matomäki, Radziwiłł, Tao, Teräväinen and Ziegler15, Theorem 1.8] (see [Reference Lichtman10, Theorem 1.8] for the details of this implication).Footnote 2 We also note that the case $\ell =0$ of Conjecture 1.5 was proven on average by Matomäki–Radziwiłł–Tao [Reference Matomäki, Radziwiłł and Tao12] in the regime $H=\psi (X)\to \infty $.
1.2 Outline of the proof
The proof method of Theorem 1.2 (and Theorem 1.6) is somewhat different from that of [Reference Lichtman10] (or [Reference Matomäki, Radziwiłł and Tao12]). Both proofs begin with Fourier-analytic identities, namely, [Reference Lichtman10, Lemma 2.1] and Proposition 3.2 below. The latter allows one to study mixed 2-point correlations on average, for some functions f and g which satisfy certain technical hypotheses. Crucially, in Proposition 3.2, having qualitative cancellation for the exponential sum of f on average over short intervals $[x,x+H]$ suffices, whereas in [Reference Lichtman10, Lemma 2.1], one needs to save a factor comparable to $((1/X)\sum _{n\leq X}|g(n)|^2)^{-1/2}$ (but no additional hypotheses were required of $f, g$). For intervals of length $H=(\log X)^{O(1)}$, the bound in [Reference Matomäki, Radziwiłł and Tao12] for the exponential sum of a multiplicative f on average over short intervals $[x,x+H]$ saves less than $(\log X)^{-o(1)}$, which is problematic if the mean value of $|g|^2$ is a power of $\log X$, so the weakening of the Fourier assumption on f in Proposition 3.2 is important for us.
One ultimately applies Proposition 3.2 for the choices $f = \mu $ (say) and $g(n) = \mu (n + h_2)\cdots \mu (n+h_k)\Lambda (n+a_1)\cdots \Lambda (n+a_\ell )$, in which case, verifying the technical hypotheses may be reduced to the following problems:
(I) cancellation in short exponential sums of $\mu $ on average,
(II) moment estimates for short exponential sums over primes, that is, for ‘typical’ x,
$$ \begin{align*} \int_{0}^1\bigg|\sum_{x\leq n\leq x+H}\Lambda(n)e(\alpha n)\bigg|^{2m}{\textrm{d}}{\alpha} \ \ll \ H^{2m-1}. \end{align*} $$
Here, (I) is deduced from the work of Matomäki–Radziwiłł–Tao [Reference Matomäki, Radziwiłł and Tao12], with special care paid to the shape of the error terms in order to obtain a power-saving error term in Theorem 1.2(ii). This is carried out in Proposition 2.1.
For (II), the intervals involved are too short for sieve methods to provide us with a strong enough pointwise bound on these moments. However, on average over x, in Proposition 2.7, we show that the moments above are of the expected order of magnitude by applying upper bounds for prime tuples coming from Selberg’s sieve, and by performing an analysis of the resulting singular series.
The method presented is rather flexible and could be applied (with some additional effort) to other correlation problems as well, such as the sums
on average over h (with $P(Y)\in \mathbb {Z}[Y]$). We leave the details of such generalisations to the interested reader.
2 Auxiliary results
2.1 A short exponential sum estimate
As in [Reference Matomäki, Radziwiłł and Tao12], we introduce a set $\mathcal {S}_{P_1,Q_1,X}$ (depending on parameters $10<P_1<Q_1\leq X$) consisting of the ‘typical’ numbers having prime factors from certain long ranges. More precisely, $\mathcal {S}_{P_1,Q_1,X}$ is the set of positive integers having a prime factor in each of the ranges $[P_j,Q_j]$, $j=1,\ldots , J$, where for $j>1$, we define:
and J is the largest index, such that $Q_J\leq \exp (\sqrt {\frac {1}{2}\log X})$. If $\mathcal {S}_{P_1,Q_1,X}^{c}$ denotes the complement of $\mathcal {S}_{P_1,Q_1,X}$ in $\mathbb {N}\cap [1,X]$, then the fundamental lemma of sieve theory [Reference Friedlander and Iwaniec4, Lemma 6.17] tells us that
We then have the following exponential sum estimate (with the supremum outside) for short sums of multiplicative functions, which follows from [Reference Matomäki, Radziwiłł and Tao12, Theorem 2.3].
Proposition 2.1. Let $3\leq H\leq \exp ((\log X)^{1/1000})$ and
Let f be a 1-bounded multiplicative function. Then there exist $10<P_1<Q_1\leq X$, such that
and, such that for $\mathcal {S}=\mathcal {S}_{P_1,Q_1,X}$, we have
where $Q= \min \{(\log X)^{1/125}, (\log H)^5\}$.
Remark 2.2. Applying (1.7), and assuming that $H\leq (\log X)^C$, the bound (2.3) in the case of $f=\mu $ simplifies to
for some $\delta =\delta (C)>0$, and the same holds with $\lambda $ in place of $\mu $. Moreover, (2.2) then simplifies to $(\log P_1)/(\log Q_1)\ll \delta $.
Proof. Without loss of generality, we may assume that $H\geq H_0$ for a large enough constant $H_0$. Denote the integral in (2.3) by $J_f$. Suppose first that
Let
and let $P_1=W^{200}$, $Q_1=H/W^{3}$ be as in [Reference Matomäki, Radziwiłł and Tao12, Theorem 2.3]. Note that $W\ll (\log X)^{1/150}$ by the fact that $M(f;X,Q)\leq 2\log \log X+O(1)$. Note also that $\frac {\log P_1}{\log Q_1}\ll \frac {\log W}{\log H}\ll \delta $ and that all the conditions for W in [Reference Matomäki, Radziwiłł and Tao12, Theorem 2.3] are satisfied (that is, $W\geq (\log H)^5$ and $W\leq \min \{H^{1/250},(\log X)^{1/125}\}$ and $W\leq \exp (M(f;X,Q)/3)$), so we obtain
Suppose then that
Let
and let $P_1=W^{200}$, $Q_1=H/W^3$ as before. We may assume $H_1\geq 1000$, since otherwise, the claim is trivial. Now, by noting that $\frac {\log P_1}{\log Q_1}\ll \exp (-M(f;X,Q)/2000)$ and splitting the sum on H in (2.3) into shorter sums of length in $[H_1/4,H_1/2]$, it suffices to prove that
uniformly for $H'\in [H_1/4,H_1/2]$. Since the conditions for W in [Reference Matomäki, Radziwiłł and Tao12, Theorem 2.3] are satisfied, we can again apply that theorem to obtain the desired bound (noting that $\frac {(\log H_1)^{1/4}(\log \log H_1)}{W^{1/4}}\ll \exp (-M(f;X,Q)/2000)$ in this situation). This completes the proof.
2.2 Upper-bounding correlations of primes
The goal of this subsection is to prove Proposition 2.7 below, which gives optimal bounds for even moments of the short exponential sums associated with correlations of the von Mangoldt function. We first need a few lemmas on tuples of primes and averages of singular series.
Recall for a tuple $\mathcal H$ of integers, $\nu _{p}(\mathcal {H}) = |\{h\pmod {p} : h\in \mathcal H\}|$. A well-known application of Selberg’s sieve upper bounds the number of k-tuples of primes, for fixed k.
Lemma 2.3. Let $k\geq 1$ be fixed, let $X\geq X_0(k)$ and suppose that $h_1,\ldots , h_k\in [-X,X]$ are distinct integers. Denote $\mathcal H = \{h_1,\ldots ,h_k\}$. Then we have
where the singular series is given by
Proof. This is [Reference Friedlander and Iwaniec4, Theorem 7.16].
We have a trivial upper bound for the values of the singular series, which we will need in what follows.
Lemma 2.4. Let $k\geq 1$, and let $\mathcal {H}=\{h_1,\ldots , h_k\}$ be a tuple of distinct integers. Then
Proof. Note that $\nu _{p}(\mathcal {H})\le k$, and that if $\nu _{p}(\mathcal {H})<k$, then p must divide $h_i-h_j$ for some $i<j$. Hence
as claimed.
We will also need an upper bound for the autocorrelations of $h/\varphi (h)$.
Lemma 2.5. Let $H\geq 1$, and let $C,k,r\geq 1$ be fixed. Then we haveFootnote 3
uniformly for any linear functions $L_i(h)=a_ih+b_i$ with $a_i,b_i\in [-C,C]\cap \mathbb {Z}$.
Proof. First note that for $H'\geq 1$ and any integer $m\geq 1$, we have
Then, by Hölder’s inequality and (2.6) with $H'=(C+1)H$, we have
using the fact that $L_i(\cdot )$ takes any integer value at most once.
The previous lemmas lead to the following corollary.
Corollary 2.6. Let $k\geq m\geq 1$ be fixed. Then
where the supremum ranges over affine-linear forms $L_j(h_1,\ldots ,h_m) = a_j+\sum _{i=1}^ma_{i,j}h_i$ with integer coefficients and with $|a_{i,j}|,|a_j|\le A$.
Proof. Denote by $\Sigma $ the sum of interest on the left-hand side. Since there are $O_{k,A}(1)$ many choices of affine-linear forms $L_1,\ldots ,L_k$ with A-bounded coefficients, it suffices to take the supremum outside the sum in $\Sigma $. Then for each $L_1,\ldots ,L_k$, by Lemma 2.4, we bound $\Sigma $ as
since to each $\mathbf {h}\in [0,H]^{m-1}$ we can apply Lemma 2.5 with $r=\binom {k}{2}$, $C = mA$ and linear functions $L_{j,j',\mathbf {h}}(h) := L_j(\mathbf {h},h)-L_{j'}(\mathbf {h},h)$.
Using Corollary 2.6, we can prove the following bound for high moments of short exponential sums associated with the correlations of the von Mangoldt function. This estimate will be needed in Section 4.
Proposition 2.7. Let $\ell \geq 1$, $k\geq 2$ be fixed, and let $a_1,\ldots ,a_{\ell }$ be distinct fixed integers. For $X\geq H\geq 2$ and $|g(n)|\leq 1$, we have
In particular, if $H\geq (\log X)^{\ell k/(k-1)}$, then
Remark 2.8. The bound above for $M_{2k}$ is optimal up to a constant factor, assuming the Hardy–Littlewood prime tuples conjecture. Indeed, one can show that $M_{2k}\gg X H^{2k-1}$ in the case $g(n)\equiv 1$, assuming the Hardy–Littlewood conjecture (this is done by considering the contribution to (2.8) below coming from those $(n_1,\ldots , n_{2k})$ with $H>|n_i-n_j|>\max _{i}|a_i|$ for all $i\neq j$). Similarly, one can show $M_{2k}\gg XH^{k}(\log X)^{k\ell }$ (by considering the contribution to (2.8) below coming from those $(n_1,\ldots , n_{2k})$ with $n_{k+i}=n_i$ for all $i\le k$ and $H>|n_i-n_j|>\max _{i}|a_i|$). Last, one can show $M_{2k}\gg XH(\log X)^{(2k-1)\ell }$ (by considering the contribution to (2.8) below coming from those $(n_1,\ldots , n_{2k})$ with $n_1=\cdots =n_{2k}$).
Proof. Expanding out the definition of $M_{2k}$ using orthogonality, we obtain
and so $|g(n)|\le 1$ implies
For each $n_1,\ldots , n_{2k}\leq X+H$, denote $M=\max _{1\le i,j\le 2k} |n_i-n_j|$, so that
and if we let $n=n_{2k}$, $h_i = n_i-n$ (so $h_{2k}=0$), then (2.9) becomes
Write $\mathcal {A}=\{a_1,\ldots , a_{\ell }\}$ and $\mathcal H=\{0,h_1,\ldots , h_{2k-1}\}$ (note $h_{2k-1}=h_1+\cdots +h_{k-1}-h_{k}-\cdots -h_{2k-2}$). Let $\mathcal {A}+\mathcal {H}$ denote the sumset, and observe that $|\mathcal {A}+\mathcal {H}|\in [\ell ,2k\ell ]$. In what follows, for convenience of notation, we denote $h_0=0$.
Now, we partition the tuples $\mathcal H$ according to $|\mathcal {A}+\mathcal {H}|$, namely, for $m\in [0,(2k-1)\ell ]$, denote
so that by Lemma 2.3,
Let $A=\max _{a\in \mathcal A}|a|$. We claim that
To show this, first note that all the sums $a_j+h_i$, $j\leq \ell $, $i\not \in \mathcal {I}$ are distinct, since if there was a coincidence $a+h_i=a'+h_{i'}$ for some $a,a'\in \mathcal A$, $i'>i$, then $h_i-h_{i'}=a'-a\in [-A,A]$ and so $i\in \mathcal {I}$. Thus, we must have
so $|\mathcal {I}|\geq m/\ell $, as claimed. Now, for $I:=|\mathcal {I}|$, we have a system of $I+1$ linear inequalities constraining the vector $(h_1,\ldots , h_{2k-1})\in [-H,H]^{2k-1}$
where $h_0=0$, and $\sigma (i)\in [i+1,2k-1]$ are some integers.
Let $I'=I+1$ if $I\leq k-1$, and let $I'=I$ if $I\geq k$. Then, by basic linear algebra, the set of $I+1$ linear forms above contains a subset of $I'$ linearly independent forms, so there exists a vector ${\textbf {u}}=(u_1,\ldots , u_{2k-1-I'})\in [-H,H]^{2k-1-I'}$ (depending on $h_i$) and linear forms $L_i:\mathbb {Z}^{2k-2-I'}\to \mathbb {Z}$ with bounded coefficients (and with $L_{0}\equiv 0$), such that by denoting $L_{i,j}({\textbf {u}}) = a_j + L_i({\textbf {u}})$, we have
Thus, by Corollary 2.6 and the fact that $I'\geq \lceil m/\ell \rceil +1_{m\leq (k-1)\ell }$, for each m, we have
Hence, the bound in (2.10) becomes
Finally, the assumption $H \ge (\log X)^{\ell k/(k-1)}$ implies $M_{2k} \ll XH^{2k-1}$ as claimed.
2.3 Correlations of primes and integers having typical factorisation
In this subsection, we will prove Lemma 2.11, which upper bounds the correlations of the von Mangoldt function and the indicator of numbers having prime factors in prescribed intervals.
We first consider a class of multiplicative functions with ‘moderate growth’.
Definition 2.9. Denote the set $\mathcal M$ of multiplicative $f:\mathbb {N}\to \mathbb {R}_{\ge 0}$ with
(i) $f(p^\nu ) \le 2^\nu $ for all primes p, $\nu \ge 1$;
(ii) for all $\varepsilon>0$, there exists $B=B(\varepsilon )$, such that $f(n) \le Bn^{\varepsilon }$ for all $n\ge 1$.
Now, we give a special case of a general bound of Henriot [Reference Henriot8] for the class $\mathcal M$. Henriot’s result refines earlier work of Nair–Tenenbaum [Reference Nair and Tenenbaum17], and importantly, it is uniform in the discriminant.
Lemma 2.10. Given $k\ge 1$ and a tuple $\mathcal H=\{h_1,\ldots ,h_k\}\subset [1,X]$, denote $\nu _p(\mathcal {H}) = |\{h\,(\text {mod }p) : h\in \mathcal H\}|$. Then for any multiplicative functions $f_j\in \mathcal M$,
where $D=D(\mathcal H)=\prod _{i<j}(h_j-h_i)^2$, and
In particular, if $|f(p)|\leq 1$ for all p, we have $\Delta _D \le \prod _{p\mid D}(1+ 2^k/p)$.
Proof. This is [Reference Henriot8, Theorem 3] in the special case of $x=\sqrt {X}$, $y=X$, $\delta = 1/(2k)$, with linear polynomials $Q_j(n)=n+h_j$, $Q(n) = \prod _{j=1}^k Q_j(n)$, and the multiplicative function $F(n_1,\ldots ,n_k)=\prod _{j=1}^k f_j(n_j)$. Note, that the discriminant of the polynomial Q is $\prod _{i<j}(h_i-h_j)^2=D$ and the sum of coefficients is $\|Q\| \ll \prod _{j=1}^k h_j \ll X^{k}$.
We remark that the bound (2.13) is of the correct order of magnitude when the functions $f_j$ are not too small, for example, $f_j(n) \ge \eta ^{\Omega (n)}$ for some $\eta>0$ (see [Reference Henriot8, Theorem 6].
As mentioned, we will need in Section 4 a simple upper bound for the correlations of the primes and integers with prescribed factorisation patterns.
Lemma 2.11. Let $\ell \geq 1$ be fixed, and let $a_1,\ldots , a_{\ell }$ be fixed and distinct. Let $X\geq 2$ and $1\leq h\leq X$ with $h\neq a_j$ for all $1\leq j\leq \ell $. Let $\mathcal {I}\subset [1,X]$, and let $\mathcal {N}$ be the set of positive integers having no prime factors from $\mathcal {I}$. Then we have
Proof. Let $P(z)=\prod _{p< z} p$. We may assume that the summation in (2.14) runs over $(2X)^{1/2}\leq n\leq X$, since the contribution of $n<(2X)^{1/2}$ is negligible. Therefore, the proof of (2.14) has been reduced to showing:
Note that all the indicator functions above are multiplicative. Denote $D=\prod _{1\le i<j\le \ell }(a_i-a_j)\prod _{j\leq \ell } (h-a_j)$. Now, by Lemma 2.10, we have
where $\Delta _D$ is crudely bounded as
Now, (2.15) follows by noting that by Euler products and Mertens’s theorem
and also by Mertens’s theorem
3 A Fourier-analytic argument
Our main theorems will be a consequence of the propositions in the previous section and Proposition 3.2 below on correlations on average under suitable hypotheses. We begin by formulating the necessary hypotheses.
In the rest of the paper, given a function $f:\mathbb {N}\to \mathbb {C}$, let $E_f$ be a convenient upper bound for the average of f, so that
For example, we may simply take $E_f=O(1)$ if f is bounded, or if $f=\Lambda $.
Definition 3.1. Let $X,H,C,p>1$ and $\eta>0$, and let $f:\mathbb {N}\to \mathbb {C}$. We say that f satisfies hypothesis $\mathsf {H}_1(X,H,C,p)$ if
We say that f satisfies hypothesis $\mathsf {H}_2(X,H,\eta )$ if
Proposition 3.2. Let $X\geq H\geq 2$. Let $C\geq 1$, $p\geq 2$ and $\eta>0$. Let $f:\mathbb {N}\to \mathbb {C}$ be any function supported on $[0,X]$ and satisfying $\mathsf {H}_2(X,H,\eta )$, and let $g:\mathbb {N}\to \mathbb {C}$ be any function satisfying $\mathsf {H}_1(X,H,C,p)$. Then we have
Note that if $|f(n)|\leq 1$, we can simply take $E_{|f|+|f|^2}(X)=O(E_{|f|}(X))$.
Proof. Let us denote
Then the task is to show that if f satisfies $\mathsf {H}_2(X,H,\eta )$ and g satisfies $\mathsf {H}_1(X,H,C,p)$, then
For proving this, we first note that
We introduce unimodular coefficients $c(h)$ to denote the phase of $\sum _{n\le X}f(n+h)g(n)$, so that
where we used the orthogonality relation ${\mathbf 1}_{n=0}=\int _0^1 e(n\alpha ){\textrm {d}}{\alpha }$. Therefore, we have the upper bound
where in the triple convolution integral, the three exponential sums are
By Fubini’s theorem, the triangle inequality and Cauchy–Schwarz, from (3.1), we deduce that
Let q satisfy $1/p+1/q=1/2$. By taking the supremum of the integral with $F_x(-\alpha )$ to the power $1/p$ and applying Hölder’s inequality with exponents $(2,q,p)$, we obtain
say. Since f satisfies $\mathsf {H}_2(X,H,\eta )$, we have
By Parseval, we have
Last, using Hölder’s inequality and the fact that g satisfies $\mathsf {H}_1(X,H,C,p)$, we have
Combining the bounds, we see that
as desired.
4 Proofs of the main theorems
We are now ready to prove Theorem 1.6. As already discussed in Remark 1.7, Theorem 1.2(i) concerning the Möbius case follows immediately as a special case. As we shall see, Theorem 1.2(ii) also follows with essentially the same proof.
Proof of Theorem 1.6.
Fix $\varepsilon \in (0,1)$ and $k,\ell \geq 1$, and let $2\leq (\log X)^{\ell +\varepsilon }\leq H\leq \exp ((\log X)^{1/1000})$. Let:
Set:
where $\mathcal {S}$ is the set of positive integers having a prime factor in each of the intervals $[P_i, Q_i]$, with $P_i,Q_i$ as in Proposition 2.1 and $\delta $ as above. Then, by Lemma 2.11 (and the fact that $\mathcal {S}^c\subset \bigcup _{j\leq J}\mathcal {S}_j^c$, where $\mathcal {S}_j^c$ is the set of integers having no prime factors in $[P_j,Q_j]$), for all $X\geq 2$, we have
By (2.1), we have
Also, by Lemma 2.5, we have
and so plugging back into (4.1) gives
Let
In view of (4.2), to prove Theorem 1.6, it suffices to show that
since we can crudely estimate $2000p<10\, 000\ell /\varepsilon $. Note that by Lemma 2.3, we can take
and we can trivially take $E_{f}(X), E_{|f|+|f|^2}(X)\asymp 1$, so it suffices to prove (4.3) with an extra factor of $E_{|f|+|f|^2}(X)E_{g}(X)$ on the right-hand side.
By Proposition 2.7 (and the fact that p is even and satisfies $\ell +\varepsilon> \ell p/(p-2)$), there exists a constant $B=B_{\ell ,\varepsilon }>0$, for which
Therefore, g satisfies hypothesis $\mathsf {H}_1(X,H,B',p)$ for some $B'\ll 1$.
We also note that by Proposition 2.1, f satisfies $\mathsf {H}_2(X,H,\eta )$ with
Now, applying Proposition 3.2 with the choices of $f,g$ above, we obtain
Thus, since $\delta = 10^4\ell \varepsilon ^{-1}(\log \log H)/(\log H)$, this gives (4.3), as desired. The proof of Theorem 1.6 (and, hence, of Theorem 1.2(i)) is now complete.
Proof of Theorem 1.2(ii).
Let $\delta $ be as in the theorem, so that, in particular, $\delta \leq c/C$ with $c>0$ be small enough. Take $c=1/10\, 000$. Applying (4.4) and Markov’s inequality, we see that
for all but $\ll H^{1-\delta /(2p)}$ integers $h\leq H$. By (1.7), we have $M(\mu ;X,Q)\geq \frac {1}{4}\log \log X+O(1)$, so we see that
and the claim follows.
Acknowledgements
The first author was supported by a Clarendon Scholarship. The second author was supported by a Titchmarsh Fellowship and Academy of Finland grant no. 340098. The authors would like to thank the anonymous referee for detailed feedback and corrections.
Conflict of Interest
The authors have no conflicts of interest to declare.