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Related papers: A Sieve Method for Shifted Convolution Sums

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If $\mathcal{A}$ is a finite set (alphabet), the shift dynamical system consists of the space $\mathcal{A}^{\mathbb{N}}$ of sequences with entries in $\mathcal{A}$, along with the left shift operator $S$. Closed $S$-invariant subsets are…

Dynamical Systems · Mathematics 2020-03-05 Michael Damron , Jon Fickenscher

Quantum singular value transformation (QSVT) enables the application of polynomial functions to the singular values of near arbitrary linear operators embedded in unitary transforms, and has been used to unify, simplify, and improve most…

Quantum Physics · Physics 2023-04-28 Zane M. Rossi , Victor M. Bastidas , William J. Munro , Isaac L. Chuang

We continue our investigations of bilinear sums with modular square roots and the large sieve for square moduli in our recent article "On bilinear sums with modular square roots and applications II", arXiv:2603.00768. In the present…

Number Theory · Mathematics 2026-04-07 Stephan Baier

In this paper we consider the possibility of application of the quantum inverse scattering method for studying the superconformal field theory and it's integrable perturbations. The classical limit of the considered constructions is based…

High Energy Physics - Theory · Physics 2021-09-28 Petr P. Kulish , Anton M. Zeitlin

A sum rule relating the widths of the decays of mesons belonging to heavy quark multiplets, having the same parity and light quark spin j, into the low lying $0^-$ and $1^-$ multiplet is obtained. As this sum rule follows from properties of…

High Energy Physics - Phenomenology · Physics 2007-05-23 Myron Bander

Inference in expressive probabilistic models is generally intractable, which makes them difficult to learn and limits their applicability. Sum-product networks are a class of deep models where, surprisingly, inference remains tractable even…

Machine Learning · Computer Science 2016-11-14 Abram L. Friesen , Pedro Domingos

We study giant graviton expansions of the superconformal index of 4d orbifold/orientifold theories. In general, a giant graviton expansion is given as a multiple sum over wrapping numbers. It has been known that the expansion can be reduced…

High Energy Physics - Theory · Physics 2024-01-01 Shota Fujiwara , Yosuke Imamura , Tatsuya Mori , Shuichi Murayama , Daisuke Yokoyama

We study the shifted convolution sum of the divisor function and some other arithmetic functions.

Number Theory · Mathematics 2015-02-24 Farzad Aryan

We present a common ground for infinite sums, unordered sums, Riemann/Lebesgue integrals, arc length and some generalized means. It is based on extending functions on finite sets using Hausdorff metric in a natural way.

General Mathematics · Mathematics 2021-10-04 Attila Losonczi

This article presents a squeezing transformation for quantum systems associated to finite vector spaces. The physical idea of squeezing here is taken from the action of the usual squeezing operator over wave functions defined on a real…

Quantum Physics · Physics 2008-02-29 M. Ruzzi

The purpose of this paper is twofold: 1) Applications of Gallagher's larger sieve modulo prime squares do not work. In some relevant cases we can transform the residue class information modulo $p^2$ to more suitable residue information…

Number Theory · Mathematics 2026-03-19 Rainer Dietmann , Christian Elsholtz , Imre Ruzsa

For high volume data streams and large data warehouses, sampling is used for efficient approximate answers to aggregate queries over selected subsets. Mathematically, we are dealing with a set of weighted items and want to support queries…

Data Structures and Algorithms · Computer Science 2007-05-23 Mario Szegedy , Mikkel Thorup

The influx of massive amounts of data from current and upcoming cosmological surveys necessitates compression schemes that can efficiently summarize the data with minimal loss of information. We introduce a method that leverages the…

Cosmology and Nongalactic Astrophysics · Physics 2023-12-18 Aizhan Akhmetzhanova , Siddharth Mishra-Sharma , Cora Dvorkin

In the analysis of large/big data sets, aggregation (replacing values of a variable over a group by a single value) is a standard way of reducing the size (complexity) of the data. Data analysis programs provide different aggregation…

Machine Learning · Computer Science 2023-03-29 Vladimir Batagelj

In this paper, we introduce some adaptive methods for solving variational inequalities with relatively strongly monotone operators. Firstly, we focus on the modification of the recently proposed, in smooth case [1], adaptive numerical…

Optimization and Control · Mathematics 2022-11-01 A. A. Titov , S. S. Ablaev , M. S. Alkousa , F. S. Stonyakin , A. V. Gasnikov

Decentralized optimization methods have been in the focus of optimization community due to their scalability, increasing popularity of parallel algorithms and many applications. In this work, we study saddle point problems of sum type,…

Optimization and Control · Mathematics 2021-10-26 Aleksandr Beznosikov , Alexander Rogozin , Dmitry Kovalev , Alexander Gasnikov

In this paper, we extend recent results on the convergence of ergodic averages along sequences generated by return times to shrinking targets in rapidly mixing systems, partially answering questions posed by the first author, Maass and the…

Dynamical Systems · Mathematics 2026-03-03 Sebastián Donoso , Sovanlal Mondal , Vicente Saavedra-Araya

Let $j\geq 2$ be a given integer. Let $f$ be a normalized primitive holomorphic cusp form of even integral weight for the full modular group $\Gamma=SL(2,\mathbb{Z})$. Denote by $\lambda_{\text{sym}^{j}f}(n)$ the $n$th normalized…

Number Theory · Mathematics 2024-04-12 Youjun Wang

Quantum metrology theory has up to now focused on the resolution gains obtainable thanks to the entanglement among N probes. Typically, a quadratic gain in resolution is achievable, going from the 1/sqrt(N) of the central limit theorem to…

Quantum Physics · Physics 2020-07-15 Lorenzo Maccone , Alberto Riccardi

This paper presents a lower bound for optimizing a finite sum of $n$ functions, where each function is $L$-smooth and the sum is $\mu$-strongly convex. We show that no algorithm can reach an error $\epsilon$ in minimizing all functions from…

Machine Learning · Statistics 2015-10-06 Alekh Agarwal , Leon Bottou