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We show that vanishing of asymptotic p-th syzygies implies p-very ampleness for line bundles on arbitrary projective schemes. For smooth surfaces we prove that the converse holds when p is small, by studying the Bridgeland-King-Reid-Haiman…

Algebraic Geometry · Mathematics 2018-05-08 Daniele Agostini

The existence of the Gorenstein projective precovers over $R$ an arbitrary ring, as well as the completeness of the Gorenstein projective cotorsion pair $(\mathcal{GP},\mathcal{GP}^{\perp})$, are open questions. In this paper, we provide…

Rings and Algebras · Mathematics 2026-02-25 Víctor Becerril

We study the gaps between products of two primes in imaginary quadratic number fields using a combination of the methods of Goldston-Graham-Pintz-Yildirim \cite{GGPY}, and Maynard \cite{MAY}. An important consequence of our main theorem is…

Number Theory · Mathematics 2020-08-11 Pranendu Darbar , Anirban Mukhopadhyay , G. K. Viswanadham

We give an estimation of the existence density for the $2d$ different primes by using a new and simple algorithm for getting the $2d$ different primes. The algorithm is a kind of the sieve method, but the remainders are the central numbers…

Number Theory · Mathematics 2014-02-27 Minoru Fujimoto , Kunihiko Uehara

The Selberg sieve provides majorants for certain arithmetic sequences, such as the primes and the twin primes. We prove an L^2-L^p restriction theorem for majorants of this type. An immediate application is to the estimation of exponential…

Number Theory · Mathematics 2007-05-23 Ben Green , Terence Tao

Most results on Stochastic Gradient Descent (SGD) in the convex and smooth setting are presented under the form of bounds on the ergodic function value gap. It is an open question whether bounds can be derived directly on the last iterate…

Optimization and Control · Mathematics 2025-07-21 Guillaume Garrigos , Daniel Cortild , Lucas Ketels , Juan Peypouquet

This note complements a recent paper of Chatzakos, Harcos and Kaneko \cite{CHK}. We use a Dirichlet style Prime Geodesic Theorem to improve the error term estimate in loc. cit. at the cost of lowering the resolution. The proof relies on the…

Number Theory · Mathematics 2025-07-21 Anton Deitmar

In this paper, we introduce a new approach to proving the convergence of the Stochastic Approximation (SA) and the Stochastic Gradient Descent (SGD) algorithms. The new approach is based on a concept called GSLLN (Generalized Strong Law of…

Optimization and Control · Mathematics 2025-11-11 Rajeeva Laxman Karandikar , Bhamidi Visweswara Rao , Mathukumalli Vidyasagar

The purpose of this short article is to prove some potential estimates that naturally arise in the study of subelliptic Sobolev inequalites for functions. This will allow us to prove a local subelliptic Sobolev inequality with the optimal…

Classical Analysis and ODEs · Mathematics 2015-07-14 Po-Lam Yung

We show that for all large enough $x$ the interval $[x,x+x^{1/2}\log^{1.39}x]$ contains numbers with a prime factor $p > x^{18/19}.$ Our work builds on the previous works of Heath-Brown and Jia (1998) and Jia and Liu (2000) concerning the…

Number Theory · Mathematics 2021-01-20 Jori Merikoski

In this work and its sister paper [5] we give a new proof of the famous Linnik theorem bounding the least prime in an arithmetic progression. Using sieve machinery in both papers, we are able to dipense with the log-free zero density bounds…

Number Theory · Mathematics 2023-03-13 John B Friedlander , Henryk Iwaniec

The smoothing technique of Savitzky and Golay is extended to data defined on multidimensional meshes. A smoothness-increasing accuracy-conserving (SIAC) filter is defined that is suitable for use with finite-element computation.

Numerical Analysis · Mathematics 2020-12-29 Teodoro Collin , Gordon Kindlmann , L. Ridgway Scott

The bounded gaps property of the prime numbers, as proven by Yitang Zhang, is considered for sequences of lengths of closed geodesics, which by the theory of Selberg zeta functions are the geometric analogue of the prime numbers. It turns…

Number Theory · Mathematics 2017-12-19 Anton Deitmar

The smoothing parameter $\eta_{\epsilon}(\mathcal{L})$ of a Euclidean lattice $\mathcal{L}$, introduced by Micciancio and Regev (FOCS'04; SICOMP'07), is (informally) the smallest amount of Gaussian noise that "smooths out" the discrete…

Computational Complexity · Computer Science 2014-12-30 Kai-Min Chung , Daniel Dadush , Feng-Hao Liu , Chris Peikert

In a recent work Friedlander studied the problem of how large consecutive prime gaps should be in order that the sum of the reciprocals should be divergent. Supposing a very deep Hypothesis, a generalization of the Hardy--Littlewood prime…

Number Theory · Mathematics 2025-05-13 Akos Magyar , Janos Pintz

The symplectic isotopy conjecture states that every smooth symplectic surface in $CP^2$ is symplectically isotopic to a complex algebraic curve. Progress began with Gromov's pseudoholomorphic curves [Gro85], and progressed further…

Symplectic Geometry · Mathematics 2019-07-17 Laura Starkston

Making predictions and quantifying their uncertainty when the input data is sequential is a fundamental learning challenge, recently attracting increasing attention. We develop SigGPDE, a new scalable sparse variational inference framework…

Machine Learning · Statistics 2021-10-13 Maud Lemercier , Cristopher Salvi , Thomas Cass , Edwin V. Bonilla , Theodoros Damoulas , Terry Lyons

In [Kim05], Kim gave a new proof of Siegel's Theorem that there are only finitely many $S$-integral points on $\mathbb P^1_{\mathbb Z}\setminus\{0,1,\infty\}$. One advantage of Kim's method is that it in principle allows one to actually…

Thompson Sampling (TS) from Gaussian Process (GP) models is a powerful tool for the optimization of black-box functions. Although TS enjoys strong theoretical guarantees and convincing empirical performance, it incurs a large computational…

Machine Learning · Statistics 2021-11-08 Sattar Vakili , Henry Moss , Artem Artemev , Vincent Dutordoir , Victor Picheny

A smoothing algorithm is presented for solving the soft-margin Support Vector Machine (SVM) optimization problem with an $\ell^{1}$ penalty. This algorithm is designed to require a modest number of passes over the data, which is an…

Optimization and Control · Mathematics 2024-01-19 Ibrahim Emirahmetoglu , Jeffrey Hajewski , Suely Oliveira , David E. Stewart