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The main focus of the present work is to study the Feynman's proof of the Maxwell equations using the NC geometry framework. To accomplish this task, we consider two kinds of noncommutativity formulations going along the same lines as…

High Energy Physics - Theory · Physics 2009-11-10 A. Boulahoual , M. B. Sedra

Under the lack of variational structure and nondegeneracy, we investigate three notions of \textit{generalized principal eigenvalue} for a general infinity Laplacian operator with gradient and homogeneous term. A Harnack inequality and…

Analysis of PDEs · Mathematics 2022-02-07 Anup Biswas , Hoang-Hung Vo

Concentration inequalities are fundamental tools in probabilistic combinatorics and theoretical computer science for proving that random functions are near their means. Of particular importance is the case where f(X) is a function of…

Combinatorics · Mathematics 2022-06-01 Lutz Warnke

In this work we design a general method for proving moment inequalities for polynomials of independent random variables. Our method works for a wide range of random variables including Gaussian, Boolean, exponential, Poisson and many…

Probability · Mathematics 2012-06-11 Warren Schudy , Maxim Sviridenko

We provide a simple, general argument to obtain improvements of concentration-type inequalities starting from improvements of their corresponding isoperimetric-type inequalities. We apply this argument to obtain robust improvements of the…

Optimization and Control · Mathematics 2015-07-14 Eric A. Carlen , Francesco Maggi

We obtain a Bernstein type Gaussian concentration inequality for martingales. Our inequality improves the Azuma-Hoeffding inequality for moderate deviations $x$. Following the work of McDiarmid (1989), Talagrand (1996) and Boucheron, Lugosi…

Probability · Mathematics 2017-10-17 Xiequan Fan

This paper deduces exponential matrix concentration from a Poincar\'e inequality via a short, conceptual argument. Among other examples, this theory applies to matrix-valued functions of a uniformly log-concave random vector. The proof…

Probability · Mathematics 2021-01-08 De Huang , Joel A. Tropp

This paper is the first attempt to systematically study properties of the effective Hamiltonian $\overline{H}$ arising in the periodic homogenization of some coercive but nonconvex Hamilton-Jacobi equations. Firstly, we introduce a new and…

Analysis of PDEs · Mathematics 2017-01-05 Jianliang Qian , Hung V. Tran , Yifeng Yu

This paper is concerned with an inverse random source problem for the three-dimensional time-harmonic Maxwell equations. The source is assumed to be a centered complex-valued Gaussian vector field with correlated components, and its…

Analysis of PDEs · Mathematics 2020-02-21 Peijun Li , Xu Wang

We establish a lower bound on the entropy of weighted sums of (possibly dependent) random variables $(X_1, X_2, \dots, X_n)$ possessing a symmetric joint distribution. Our lower bound is in terms of the joint entropy of $(X_1, X_2, \dots,…

Information Theory · Computer Science 2018-01-16 Jing Hao , Varun Jog

We establish mass lower bounds of Penrose-type in the setting of $3$-dimensional initial data sets for the Einstein equations satisfying the dominant energy condition, which are either asymptotically flat or asymptotically hyperboloidal.…

Differential Geometry · Mathematics 2025-04-16 Brian Allen , Edward Bryden , Demetre Kazaras , Marcus Khuri

The martingale method is used to establish concentration inequalities for a class of dependent random sequences on a countable state space, with the constants in the inequalities expressed in terms of certain mixing coefficients. Along the…

Probability · Mathematics 2009-01-22 Leonid , Kontorovich , Kavita Ramanan

We prove new equidistribution results for Galois orbits of Heegner points with respect to reduction maps at inert primes. The arguments are based on two different techniques: primitive representations of integers by quadratic forms and…

Number Theory · Mathematics 2011-04-19 Dimitar Jetchev , Ben Kane

Following recent work, this manuscript clarifies what the Gauss-Appell principle determines in incompressible, inviscid flow and how it connects to classical projection methods. At a fixed time, freezing the velocity and varying only the…

Fluid Dynamics · Physics 2026-04-24 Karthik Duraisamy

We give a new, elementary proof of a key inequality used by Rudelson in the derivation of his well-known bound for random sums of rank-one operators. Our approach is based on Ahlswede and Winter's technique for proving operator Chernoff…

Probability · Mathematics 2010-04-23 Roberto Imbuzeiro Oliveira

We refine the understanding of continuous dependence on coefficients of solution operators under the nonlocal $H$-topology viz Schur topology in the setting of evolutionary equations in the sense of Picard. We show that certain components…

Analysis of PDEs · Mathematics 2025-10-21 Andreas Buchinger , Sebastian Franz , Nathanael Skrepek , Marcus Waurick

Contraction analysis establishes exponential incremental convergence of a nonlinear system by solving a linear matrix inequality for a contraction metric, and has become a standard resource for solving problems in nonlinear control and…

Dynamical Systems · Mathematics 2026-03-03 Winfried Lohmiller , Jean-Jacques Slotine

We show that there is equality in Shannon's Entropy Power Inequality (EPI) if and only if the random variables involved are Gaussian, assuming nothing beyond the existence of differential entropies. This is done by justifying de Bruijn's…

Probability · Mathematics 2025-09-30 Lampros Gavalakis , Ioannis Kontoyiannis

We extend, in the free probability framework, an invariance principle for multilinear homogeneous sums with low influences recently established in [E. Mossel, R. O'Donnell and K. Oleszkiewicz (2010). Noise stability of functions with low…

Probability · Mathematics 2014-03-11 Aurélien Deya , Ivan Nourdin

We study high-dimensional convex empirical risk minimization (ERM) under general non-Gaussian data designs. By heuristically extending the Convex Gaussian Min-Max Theorem (CGMT) to non-Gaussian settings, we derive an asymptotic min-max…

Machine Learning · Statistics 2026-04-06 Chiheb Yaakoubi , Cosme Louart , Malik Tiomoko , Zhenyu Liao
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