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We develop a simple Quantile Spacing (QS) method for accurate probabilistic estimation of one-dimensional entropy from equiprobable random samples, and compare it with the popular Bin-Counting (BC) method. In contrast to BC, which uses…

Non-equilibrium dynamics of classical random Ising spin chains are studied using asymptotically exact real space renormalization group. Specifically the random field Ising model with and without an applied field (and the Ising spin glass…

Condensed Matter · Physics 2009-10-31 Daniel S. Fisher , Pierre Le Doussal , Cecile Monthus

Bayesian nonparametric mixture models are widely used to cluster observations. However, one major drawback of the approach is that the estimated partition often presents unbalanced clusters' frequencies with only a few dominating clusters…

Methodology · Statistics 2026-02-03 Beatrice Franzolini , Giovanni Rebaudo

The microcanonical statistical mechanics of a set of self-gravitating particles is analyzed in mean-field approach. In order to deal with an upper bounded entropy functional, a softened gravitational potential is used. The softening is…

Statistical Mechanics · Physics 2008-11-26 Eduardo Follana , Victor Laliena

We develop a factor analysis for mixed continuous and binary observed variables. To this end, we utilized a recently developed multivariate probability distribution for mixed-type random variables, the Gaussian-Grassmann distribution. In…

Methodology · Statistics 2025-12-12 Takashi Arai

In this work, we propose a local Fourier analysis for multigrid methods with coarsening by a factor of three for the staggered finite-difference method applied to the Stokes equations. In [21], local Fourier analysis has been applied to a…

Numerical Analysis · Mathematics 2022-03-10 Yunhui He

This paper presents a detailed theoretical analysis of the three stochastic approximation proximal gradient algorithms proposed in our companion paper [49] to set regularization parameters by marginal maximum likelihood estimation. We prove…

Statistics Theory · Mathematics 2020-08-14 Valentin De Bortoli , Alain Durmus , Ana F. Vidal , Marcelo Pereyra

We consider the problem of algorithmically sampling from the Gibbs measure of a mixed $p$-spin spherical spin glass. We give a polynomial-time algorithm that samples from the Gibbs measure up to vanishing total variation error, for any…

Probability · Mathematics 2024-04-25 Brice Huang , Andrea Montanari , Huy Tuan Pham

We extend the self-consistent Ornstein-Zernike approximation (SCOZA), first formulated in the context of liquid-state theory, to the study of the random field Ising model. Within the replica formalism, we treat the quenched random field as…

Disordered Systems and Neural Networks · Physics 2015-06-25 E. Kierlik , M. L. Rosinberg , G. Tarjus

A method is provided for designing and training noise-driven recurrent neural networks as models of stochastic processes. The method unifies and generalizes two known separate modeling approaches, Echo State Networks (ESN) and Linear…

Adaptation and Self-Organizing Systems · Physics 2014-04-14 Mathieu N. Galtier , Camille Marini , Gilles Wainrib , Herbert Jaeger

The efficiency of time dependent density matrix renormalization group methods is intrinsically connected with the rate of entanglement growth. We introduce a new measure of entanglement in the space of operators and show, for transverse…

Quantum Physics · Physics 2009-03-04 Tomaz Prosen , Iztok Pizorn

Building on the recent derivation of a bare factorization theorem for the $b$-quark induced contribution to the $h\to\gamma\gamma$ decay amplitude based on soft-collinear effective theory, we derive the first renormalized factorization…

High Energy Physics - Phenomenology · Physics 2021-02-03 Ze Long Liu , Bianka Mecaj , Matthias Neubert , Xing Wang

Entropy production in stochastic mechanical systems is examined here with strict bounds on its rate. Stochastic mechanical systems include pure diffusions in Euclidean space or on Lie groups, as well as systems evolving on phase space for…

Mathematical Physics · Physics 2022-01-12 Gregory S. Chirikjian

We obtain entropy formulas for SRB measures with finite entropy given by inducing schemes. In the first part of the work, we obtain Pesin entropy formula for the class of noninvertible systems whose SRB measures are given by Gibbs-Markov…

Dynamical Systems · Mathematics 2021-05-06 Jose F. Alves , David Mesquita

We prove new concentration inequalities for quantum spin systems which apply to any local observable measured on any product state or on any state with exponentially decaying correlations. Our results do not require the spins to be arranged…

Mathematical Physics · Physics 2025-06-17 Giacomo De Palma , Davide Pastorello

We study a finite-inventory risk-sensitive market making problem in which a dealer controls bid and ask quotes, faces Brownian midprice risk, and receives liquidity-taking orders through point processes with quote-dependent intensities. The…

Trading and Market Microstructure · Quantitative Finance 2026-05-26 Tenghan Zhong

We consider a random time evolution operator composed of a circuit of random unitaries coupling even and odd neighboring spins on a chain in turn. In spirit of Floquet evolution, the circuit is time-periodic; each timestep is repeated with…

Statistical Mechanics · Physics 2018-10-31 Christoph Sünderhauf , David Pérez-García , David A. Huse , Norbert Schuch , J. Ignacio Cirac

This paper addresses the design of linear and nonlinear stabilization procedures for high-order continuous Galerkin (CG) finite element discretizations of scalar conservation laws. We prove that the standard CG method is entropy…

Numerical Analysis · Mathematics 2020-05-19 Dmitri Kuzmin , Manuel Quezada de Luna

We study the scaling properties of the entanglement entropy (EE) near quantum critical points in interacting random antiferromagnetic (AF) spin chains. Using density-matrix renormalization group, we compute the half-chain EE near the…

Disordered Systems and Neural Networks · Physics 2024-03-05 Prashant Kumar , R. N. Bhatt

Bayesian optimal experimental design provides a principled framework for selecting experimental settings that maximize obtained information. In this work, we focus on estimating the expected information gain in the setting where the…

Machine Learning · Statistics 2025-10-02 Chuntao Chen , Tapio Helin , Nuutti Hyvönen , Yuya Suzuki