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We study the phenomena that arise when we combine the standard pseudodifferential operators with those operators that appear in the study of some sub-elliptic estimates, and on strongly pseudoconvex domains. The algebra of operators we…

Classical Analysis and ODEs · Mathematics 2014-12-12 Elias M. Stein , Po-Lam Yung

Realistic physical phenomena exhibit random fluctuations across many scales in the input and output processes. Models of these phenomena require stochastic PDEs. For three-dimensional coupled (vector-valued) stochastic PDEs (SPDEs), for…

Computational Engineering, Finance, and Science · Computer Science 2022-08-24 Ajit Desai , Mohammad Khalil , Chris L. Pettit , Dominique Poirel , Abhijit Sarkar

In quantum mechanics some properties are maximally incompatible, such as the position and momentum of a particle or the vertical and horizontal projections of a 2-level spin. Given any definite state of one property the other property is…

Quantum Physics · Physics 2009-11-13 A. J. Skinner , V. A. Newell , R. Sanchez

The study of Fourier transforms of probability measures on fractal sets plays an important role in recent research. Faster decay rates are known to yield enhanced results in areas such as metric number theory. This paper focuses on…

Classical Analysis and ODEs · Mathematics 2024-12-24 Ying Wai Lee

Spectrahedra are sets defined by linear matrix inequalities. Projections of spectrahedra are called semidefinitely representable sets. Both kinds of sets are of practical use in polynomial optimization, since they occur as feasible sets in…

Optimization and Control · Mathematics 2009-12-17 Tim Netzer

We revisit the phenomenon where, for certain domains $D$, if the squeezing function $s_D$ extends continuously to a point $p\in \partial{D}$ with value $1$, then $\partial{D}$ is strongly pseudoconvex around $p$. In $\mathbb{C}^2$, we…

Complex Variables · Mathematics 2023-02-24 Gautam Bharali

Dualities are hidden symmetries that map seemingly unrelated physical systems onto each other. The goal of this work is to systematically construct families of Hamiltonians endowed with a given duality and to provide a universal description…

Applied Physics · Physics 2021-08-26 Michel Fruchart , Claudia Yao , Vincenzo Vitelli

In this paper, we are concerned with the relationship among the lower Assouad type dimensions. For uniformly perfect sets in doubling metric spaces, we obtain a variational result between two different but closely related lower Assouad…

Classical Analysis and ODEs · Mathematics 2020-03-05 Haipeng Chen , Min Wu , Yuanyang Chang

This paper revisits the notion of classical orthogonal polynomials from a broader functional-analytic point of view. It is intended neither as a survey of known results nor as a review of the literature, but rather as a conceptual…

Classical Analysis and ODEs · Mathematics 2026-05-28 K. Castillo

Necessary and sufficient conditions for convexity and strong convexity, respectively, of sublevel sets that are defined by finitely many real-valued $C^{1,1}$-maps are presented. A novel characterization of strongly convex sets in terms of…

Optimization and Control · Mathematics 2017-01-03 Alexander Weber , Gunther Reissig

We propose a novel polyhedral uncertainty set for robust optimization, termed the smooth uncertainty set, which captures dependencies of uncertain parameters by constraining their pairwise differences. The bounds on these differences may be…

Optimization and Control · Mathematics 2025-10-13 Noam Goldberg , Michael Poss , Shimrit Shtern

This paper presents a new family of localized orthonormal bases - sinlets - which are well suited for both signal and image processing and analysis. One-dimensional sinlets are related to specific solutions of the time-dependent harmonic…

Multimedia · Computer Science 2012-09-19 Alexander Y. Davydov

We explore a very simple distribution of unitaries: random (binary) phase -- Hadamard -- random (binary) phase -- random computational-basis permutation. We show that this distribution is statistically indistinguishable from random Haar…

Quantum Physics · Physics 2024-04-18 Zvika Brakerski , Nir Magrafta

Contrary to prevailing notion we find that the spectrum associated with the extended states in a complex system may belong to the Poisson universality class if the system is subjected to a specific set of constraints. Our results are based…

Statistical Mechanics · Physics 2017-06-07 Triparna Mondal , Suchetana Sadhukhan , Pragya Shukla

Higher order random walks (HD-walks) on high dimensional expanders (HDX) have seen an incredible amount of study and application since their introduction by Kaufman and Mass [KM16], yet their broader combinatorial and spectral properties…

Computational Complexity · Computer Science 2021-07-20 Mitali Bafna , Max Hopkins , Tali Kaufman , Shachar Lovett

This paper deals with the alternative mathematical modeling of the two-side platform. Two-sided platforms are specific multi-sided platforms that bring together two distinct groups of a model. The stochastic modeling by adapting various…

Probability · Mathematics 2022-12-29 Song-Kyoo Kim

Coboundary expansion is a high dimensional generalization of the Cheeger constant to simplicial complexes. Originally, this notion was motivated by the fact that it implies topological expansion, but nowadays a significant part of the…

Combinatorics · Mathematics 2024-11-06 Tali Kaufman , Izhar Oppenheim , Shmuel Weinberger

In this paper we discuss constraints on two-dimensional quantum-mechanical systems living in domains with boundaries. The constrains result from the requirement of hermicity of corresponding Hamiltonians. We construct new two-dimensional…

Mathematical Physics · Physics 2015-06-26 Sergey Klishevich

In this article we introduce associative Look-Up Tables. With their help, pseudo sums are correctly determined. The set of limit distributions in a pseudo-summation scheme of i.i.d. random variables is described. Also, two special cases…

Probability · Mathematics 2023-06-02 Ivan Alexeev , Ignat Melnikov , Artem Uglovski

Many applications of machine learning on discrete domains, such as learning preference functions in recommender systems or auctions, can be reduced to estimating a set function that is sparse in the Fourier domain. In this work, we present…

Machine Learning · Computer Science 2021-05-11 Chris Wendler , Andisheh Amrollahi , Bastian Seifert , Andreas Krause , Markus Püschel