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Extreme value analysis is an essential methodology in the study of rare and extreme events, which hold significant interest in various fields, particularly in the context of environmental sciences. Models that employ the exceedances of…

Methodology · Statistics 2025-07-16 Lorenzo Dell'Oro , Carlo Gaetan

We develop an action principle to construct the field equations for a multi-fluid system containing charge-neutral fluids, plasmas, and dissipation (via resistive interactions), by combining the standard, Maxwell action and minimal coupling…

General Relativity and Quantum Cosmology · Physics 2017-05-31 N. Andersson , G. L. Comer , I. Hawke

The paper begins with a novel variational formulation of Duffing equation using the extended framework of Hamilton's principle (EHP). This formulation properly accounts for initial conditions, and it recovers all the governing differential…

Numerical Analysis · Computer Science 2019-03-18 Jinkyu Kim , Hyeonseok Lee , Jinwon Shin

Monte Carlo methods are widely used importance sampling techniques for studying complex physical systems. Integrating these methods with deep learning has significantly improved efficiency and accuracy in high-dimensional problems and…

Disordered Systems and Neural Networks · Physics 2024-12-24 Yixiong Ren , Jianhui Zhou

The classical Donsker weak invariance principle is extended to a Besov spaces framework. Polygonal line processes build from partial sums of stationary martingale differences as well independent and identically distributed random variables…

Probability · Mathematics 2020-03-10 Davide Giraudo , Alfredas Rackauskas

We introduce a minimization formulation for the determination of a finite-dimensional, time-dependent, orthonormal basis that captures directions of the phase space associated with transient instabilities. While these instabilities have…

Computational Physics · Physics 2016-04-27 Hessam Babaee , Themistoklis Sapsis

We show that in applications of variational theory to quantum field theory it is essential to account for the correct Wegner exponent omega governing the approach to the strong-coupling, or scaling limit. Otherwise the procedure either does…

High Energy Physics - Theory · Physics 2009-11-10 B. Hamprecht , H. Kleinert

This note presents an attempt to provide a conceptual framework for variational formulations of classical physics. Variational principles of physics have all a common source in the {\it principle of virtual work} well known in statics of…

Mathematical Physics · Physics 2007-05-23 Wlodzimierz M. Tulczyjew

We consider mathematical models of the weak decay of the vector bosons $W^{\pm}$ into leptons. The free quantum field hamiltonian is perturbed by an interaction term from the standard model of particle physics. After the introduction of…

Mathematical Physics · Physics 2018-10-04 Benjamin Alvarez , Jérémy Faupin

We derive the equations of nonlinear magnetoelastostatics using several variational formulations involving the mechanical deformation and an independent field representing the magnetic component. An equivalence is also discussed, modulo…

Classical Physics · Physics 2023-12-21 Basant Lal Sharma , Prashant Saxena

Let $(X,d)$ be a compact metric space, $f:X \mapsto X$ be a continuous map with the specification property, and $\varphi: X \mapsto \IR$ be a continuous function. We prove a variational principle for topological pressure (in the sense of…

Dynamical Systems · Mathematics 2014-02-26 Daniel Thompson

In spirit of the principle of least action, which means that when a perturbation is applied to a physical system its reaction is such that it modifies its state to "agree" with the perturbation by "minimal" change of its initial state. In…

Plasma Physics · Physics 2015-07-29 Alexander Rokhlenko

Standard variational methods tend to obtain upper bounds on the ground state energy of quantum many-body systems. Here we study a complementary method that determines lower bounds on the ground state energy in a systematic fashion, scales…

Quantum Physics · Physics 2015-05-28 Tillmann Baumgratz , Martin B. Plenio

The entropy power inequality for independent random vectors is a foundational result of information theory, with deep connections to probability and geometric functional analysis. Several extensions of the entropy power inequality have been…

Information Theory · Computer Science 2025-12-23 Mokshay Madiman , James Melbourne , Cyril Roberto

Determining quantum excited states is crucial across physics and chemistry but presents significant challenges for variational methods, primarily due to the need to enforce orthogonality to lower-energy states, often requiring…

Quantum Physics · Physics 2025-05-01 Shi-Xin Zhang , Lei Wang

Applications of variational methods are typically restricted to conservative systems. Some extensions to dissipative systems have been reported too but require ad hoc techniques such as the artificial doubling of the dynamical variables.…

Plasma Physics · Physics 2017-04-05 I. Y. Dodin , A. I. Zhmoginov , D. E. Ruiz

Consider the motion of a charged, point particle moving in the complement of a Poisson distribution of hard sphere scatterers in two dimensions under the effect of a fixed magnetic field. Building on, and extending a coupling method…

Probability · Mathematics 2024-11-07 Christopher Lutsko , Balint Toth

Dependence among marginally constrained observations can break a finite-sample barrier. To formalize this phenomenon, we introduce the \emph{minimum list entropy coupling} $H(P\|Q_1,\dots,Q_m)$, the minimum conditional entropy…

Information Theory · Computer Science 2026-05-18 Shahab Asoodeh , Jun Chen

We consider $N$ bosons in a box in $\mathbb {R}^d$ with volume $N/\rho$ under the influence of a mutually repellent pair potential. The particle density $\rho\in (0,\infty)$ is kept fixed. Our main result is the identification of the…

Probability · Mathematics 2011-04-20 Stefan Adams , Andrea Collevecchio , Wolfgang König

The goal of these lecture notes is to review the problem of free energy minimization as a unified framework underlying the definition of maximum entropy modelling, generalized Bayesian inference, learning with latent variables, statistical…

Signal Processing · Electrical Eng. & Systems 2020-12-01 Sharu Theresa Jose , Osvaldo Simeone