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For the inverse source problem with the two-dimensional Helmholtz equation, the singular values of the 'source-to-near field' forward operator reveal a sharp frequency cut-off in the stably recoverable information on the source. We prove…

Analysis of PDEs · Mathematics 2018-03-15 Mirza Karamehmedović

We give a partial negative answer to a question left open in a previous work by Brasco and the first and third-named authors concerning the sharp constant in the fractional Hardy inequality on convex sets. Our approach has a geometrical…

Analysis of PDEs · Mathematics 2025-09-30 Francesca Bianchi , Giorgio Stefani , Anna Chiara Zagati

This paper considers properties of an optimization based sampler for targeting the posterior distribution when the likelihood is intractable and auxiliary statistics are used to summarize information in the data. Our reverse sampler…

Methodology · Statistics 2015-12-02 Jean-Jacques Forneron , Serena Ng

We survey results concerning sharp estimates on volumes of sections and projections of certain convex bodies, mainly $\ell_p$ balls, by and onto lower dimensional subspaces. This subject emerged from geometry of numbers several decades ago…

Functional Analysis · Mathematics 2025-01-28 Piotr Nayar , Tomasz Tkocz

We study the slices or sections of a convex polytope by affine hyperplanes. We present results on two key problems: First, we provide tight bounds on the maximum number of vertices attainable by a hyperplane slice of $d$-polytope (a sort of…

Combinatorics · Mathematics 2025-07-24 Jesús A. De Loera , Gyivan Lopez-Campos , Antonio J. Torres

We review a finite-sampling exponential bound due to Serfling and discuss related exponential bounds for the hypergeometric distribution. We then discuss how such bounds motivate some new results for two-sample empirical processes. Our…

Statistics Theory · Mathematics 2017-02-20 Evan Greene , Jon A. Wellner

Spurred by the influential work of Viola (Journal of Computing 2012), the past decade has witnessed an active line of research into the complexity of (approximately) sampling distributions, in contrast to the traditional focus on the…

Computational Complexity · Computer Science 2024-02-28 Daniel M. Kane , Anthony Ostuni , Kewen Wu

We describe a framework to build distances by measuring the tightness of inequalities, and introduce the notion of proper statistical divergences and improper pseudo-divergences. We then consider the H\"older ordinary and reverse…

Machine Learning · Computer Science 2017-04-05 Frank Nielsen , Ke Sun , Stéphane Marchand-Maillet

We construct a new tail bound for the sum of independent random variables for situations in which the expected value of the sum is known and each random variable lies within a specified interval, which may be different for each variable.…

Probability · Mathematics 2025-03-25 Jackson Loper , Jeffrey Regier

We establish a sharp moment comparison inequality between an arbitrary negative moment and the second moment for sums of independent uniform random variables, which extends Ball's cube slicing inequality.

Probability · Mathematics 2021-11-16 Giorgos Chasapis , Hermann König , Tomasz Tkocz

We obtain Rosenthal-type inequalities with sharp constants for moments of sums of independent random variables which are mixtures of a fixed distribution. We also identify extremisers in log-concave settings when the moments of summands are…

Probability · Mathematics 2025-01-28 Giorgos Chasapis , Alexandros Eskenazis , Tomasz Tkocz

Gr\"unbaum's inequality gives sharp bounds between the volume of a convex body and its part cut off by a hyperplane through the centroid of the body. We provide a generalization of this inequality for hyperplanes that do not necessarily…

Metric Geometry · Mathematics 2024-10-11 Brayden Letwin , Vladyslav Yaskin

We consider an infinite-dimensional stochastic clustering model on $\mathbb{R}$. In discrete time, each point of a unit-intensity simple point process moves halfway toward either of its left or right neighbors, chosen uniformly at random.…

Probability · Mathematics 2026-03-10 Partha S. Dey , S. Rasoul Etesami , Aditya S. Gopalan

Computable and sharp error bounds are derived for asymptotic expansions for linear differential equations having a simple turning point. The expansions involve Airy functions and slowly varying coefficient functions. The sharpness of the…

Classical Analysis and ODEs · Mathematics 2020-09-11 T. M. Dunster , A. Gil , J. Segura

We develop a method for proving sup-norm and H\"older estimates for $\overline{\partial}$ on wide class of finite type pseudoconvex domains in $\mathbb{C}^n$. A fundamental obstruction to proving sup-norm estimates is the possibility of…

Complex Variables · Mathematics 2020-12-10 Dusty Grundmeier , Lars Simon , Berit Stensønes

We study a tight Bennett-type concentration inequality for sums of heterogeneous and independent variables, defined as a one-dimensional minimization. We show that this refinement, which outperforms the standard known bounds, remains…

Optimization and Control · Mathematics 2022-11-23 Quentin Jacquet , Riadh Zorgati

We expand the basic geometric elements of the simplex method to linear programs in locally convex topological vector spaces and provide conditions under which the method converges in value to optimality. This setting generalizes many…

Optimization and Control · Mathematics 2026-04-13 Robert L Smith , Christopher Thomas Ryan

We analyze site percolation on directed and undirected graphs with site-dependent open-site probabilities. We construct upper bounds on cluster susceptibilities, vertex connectivity functions, and the expected number of simple open cycles…

Mathematical Physics · Physics 2016-10-18 Kathleen E. Hamilton , Leonid P. Pryadko

This paper is devoted to a simple and short proof on the sharp upper bound of lifespan of classical solutions to wave equations with the critical power nonlinearities of spatial derivatives of the unknown function. Such a proof is so-called…

Analysis of PDEs · Mathematics 2025-07-30 Takiko Sasaki , Kerun Shao , Hiroyuki Takamura

It has previously been shown that ordinary least squares can be used to estimate the coefficients of the single-index model under only mild conditions. However, the estimator is non-robust leading to poor estimates for some models. In this…

Methodology · Statistics 2022-09-13 Marina Masioti , Joshua Davies , Amanda Shaker , Luke A. Prendergast