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We introduce a version of Stein's method of comparison of operators specifically tailored to the problem of bounding the Wasserstein-1 distance between continuous and discrete distributions on the real line. Our approach rests on a new…

Probability · Mathematics 2023-11-03 Gilles Germain , Yvik Swan

We prove a new lower bound for the first eigenvalue of the Dirac operator on a compact Riemannian spin manifold by refined Weitzenb\"ock techniques. It applies to manifolds with harmonic curvature tensor and depends on the Ricci tensor.…

Differential Geometry · Mathematics 2007-05-23 Thomas Friedrich , Klaus-Dieter Kirchberg

Some significant quantities in mathematics and physics are most naturally expressed as the Fredholm determinant of an integral operator, most notably many of the distribution functions in random matrix theory. Though their numerical values…

Numerical Analysis · Mathematics 2010-06-01 Folkmar Bornemann

Quantum algorithms for scientific computing and their applications have been studied actively. In this paper, we propose a quantum algorithm for estimating the first eigenvalue of a differential operator $\mathcal{L}$ on $\mathbb{R}^d$ and…

Quantum Physics · Physics 2025-06-13 Koichi Miyamoto , Yuichiro Tada

Discretizations of the Feynman-Kac path integral representation of the quantum mechanical density matrix are investigated. Each infinite-dimensional path integral is approximated by a Riemann integral over a finite-dimensional function…

Statistical Mechanics · Physics 2007-05-23 Stephen D. Bond , Brian B. Laird , Benedict J. Leimkuhler

We propose a framework for quantitative evaluation of dynamical tendency for polarization in arbitrary random variable that can be decomposed into a pair of orthogonal subspaces. The method uses measures based on comparisons of given…

High Energy Physics - Lattice · Physics 2011-08-05 Andrei Alexandru , Terrence Draper , Ivan Horvath , Thomas Streuer

In this paper, we present a method for factor analysis of discrete data. This is accomplished by fitting a dependent Poisson model with a factor structure. To be able to analyze ordinal data, we also consider a truncated Poisson…

Methodology · Statistics 2019-03-13 Rolf Larsson

We present some new results on the joint distribution of an arbitrary subset of the ordered eigenvalues of complex Wishart, double Wishart, and Gaussian hermitian random matrices of finite dimensions, using a tensor pseudo-determinant…

Statistics Theory · Mathematics 2020-01-03 Marco Chiani , Alberto Zanella

We propose a new approach to quantize the marginals of the discrete Euler diffusion process. The method is built recursively and involves the conditional distribution of the marginals of the discrete Euler process. Analytically, the method…

Probability · Mathematics 2015-05-25 Gilles Pagès , Abass Sagna

We present two complementary methods, each applicable in a different range, to evaluate the distribution of the lowest eigenvalue of random matrices in a Jacobi ensemble. The first method solves an associated Painleve VI nonlinear…

Classical Analysis and ODEs · Mathematics 2015-05-18 Eduardo Dueñez , Duc Khiem Huynh , Jon P. Keating , Steven J. Miller , Nina C. Snaith

We study the probability distribution of entanglement in the Quantum Symmetric Simple Exclusion Process, a model of fermions hopping with random Brownian amplitudes between neighboring sites. We consider a protocol where the system is…

Statistical Mechanics · Physics 2021-07-30 Denis Bernard , Lorenzo Piroli

Recently there have been increasing interests in learning and inference with implicit distributions (i.e., distributions without tractable densities). To this end, we develop a gradient estimator for implicit distributions based on Stein's…

Machine Learning · Statistics 2018-06-11 Jiaxin Shi , Shengyang Sun , Jun Zhu

We investigate the spectrum of the staggered Dirac operator in 4d quenched U(1) lattice gauge theory and its relationship to random matrix theory. In the confined as well as in the Coulomb phase the nearest-neighbor spacing distribution of…

High Energy Physics - Lattice · Physics 2015-06-25 Bernd A. Berg , Harald Markum , Rainer Pullirsch , Tilo Wettig

We formulate a random matrix model which mimics the chiral phase transition in QCD with two light flavors. Two critical exponents are calculated. We obtain the mean field values $\beta = \frac 12 $ and $\delta = 3$. We also find that the…

High Energy Physics - Phenomenology · Physics 2009-10-28 A. D. Jackson , J. J. M. Verbaarschot

I propose a simple model of the distribution of the small eigenvalues of the QCD Dirac operator well above the finite temperature phase transition where chiral symmetry is restored and the spectral density at zero vanishes. Assuming the…

High Energy Physics - Lattice · Physics 2010-11-11 Tamas G. Kovacs

Chiral perturbation theory for eigenvalue distributions, and equivalently random matrix theory, has recently been extended to include lattice effects for Wilson fermions. We test the predictions by comparison to eigenvalue distributions of…

High Energy Physics - Lattice · Physics 2013-01-15 Poul H. Damgaard , Urs M. Heller , Kim Splittorff

It has been known since the pioneering paper of Mark Kac, that the asymptotics of Fredholm determinants can be studied using probabilistic methods. We demonstrate the efficacy of Kac' approach by studying the Fredholm Pfaffian describing…

Probability · Mathematics 2023-04-06 Will FitzGerald , Roger Tribe , Oleg Zaboronski

We study spectral properties of a one-dimensional Dirac equation with various disorder. We use replicas to calculate the exact density of state and typical localization length of a Dirac particle in several cases. We show that they can be…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 M. Bocquet

Hutchinson's method estimates the trace of a matrix function $f(D)$ stochastically using samples $\tau^Hf(D)\tau$, where the components of the random vectors $\tau$ obey an isotropic probability distribution. Estimating the trace of the…

High Energy Physics - Lattice · Physics 2023-03-22 Andreas Frommer , Mostafa Nasr Khalil

Due to its constrained support, the Dirichlet distribution is uniquely suited to many applications. The constraints that make it powerful, however, can also hinder practical implementations, particularly those utilizing Markov Chain Monte…

Data Analysis, Statistics and Probability · Physics 2015-03-02 M. J. Betancourt
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