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We use Madan-Yor's argument to construct associated submartingales to a class of two-parameter processes that are ordered by the increasing convex dominance. This class includes processes which have MTP$_2$ integrated survival functions. We…

Probability · Mathematics 2025-10-14 Antoine-Marie Bogso

Standard methods used for computing the dynamics of a quantum many-body system are the mean-field (MF) approximations such as the time-dependent Hartree-Fock (TDHF) approach. Even though MF approaches are quite successful, they suffer some…

Nuclear Theory · Physics 2019-11-13 Ibrahim Ulgen , Bulent Yilmaz , Denis Lacroix

Asymptotic expansions with explicit upper bounds for remainders are given for stationary distributions of nonlinearly perturbed semi-Markov processes with finite phase spaces. The corresponding algorithms are based on a special technique of…

Probability · Mathematics 2016-03-16 Dmitrii Silvestrov , Sergei Silvestrov

The work fluctuation theorem (FT) is a symmetry connecting the moment generating functions (MGFs) of the work extracted in a given process and in its time-reversed counterpart. We show that, equivalently, the FT for work in isolated quantum…

Quantum Physics · Physics 2023-11-29 Vasco Cavina , Sadeq S. Kadijani , Massimiliano Esposito , Thomas Schmidt

We present a stochastic description of a model of N mutually repelling active spheres in the presence of external fields and characterize its steady state behavior. To reproduce the effects of the experimentally observed persistence of the…

Soft Condensed Matter · Physics 2015-11-03 Umberto Marini Bettolo Marconi , Claudio Maggi

Using a method mixing Mellin-Barnes representation and Borel resummation we show how to obtain hyperasymptotic expansions from the (divergent) formal power series which follow from the perturbative evaluation of arbitrary "$N$-point"…

High Energy Physics - Theory · Physics 2014-11-20 Samuel Friot , David Greynat

We propose to interpret machine learning functions as physical observables, opening up the possibility to apply "standard" statistical-mechanical methods to outputs from neural networks. This includes histogram reweighting and finite-size…

High Energy Physics - Lattice · Physics 2021-09-20 Gert Aarts , Dimitrios Bachtis , Biagio Lucini

The primitive model describes ions by point charges with an additional hard-core interaction. In classical density-functional theory the mean-field electrostatic contribution can be obtained from the first order of a functional perturbation…

Soft Condensed Matter · Physics 2022-04-06 Moritz Bültmann , Andreas Härtel

This paper studies the rate of convergence of a family of continuous-time Markov chains (CTMC) to a mean-field model. When the mean-field model is a finite-dimensional dynamical system with a unique equilibrium point, an analysis based on…

Performance · Computer Science 2015-10-06 Lei Ying

We consider time-continuous Markovian discrete-state dynamics on random networks of interacting agents and study the large population limit. The dynamics are projected onto low-dimensional collective variables given by the shares of each…

Probability · Mathematics 2026-03-19 Marvin Lücke , Jobst Heitzig , Péter Koltai , Nora Molkenthin , Stefanie Winkelmann

The goal of this work is to formally abstract a Markov process evolving in discrete time over a general state space as a finite-state Markov chain, with the objective of precisely approximating its state probability distribution in time,…

Logic in Computer Science · Computer Science 2017-01-11 Sadegh Esmaeil Zadeh Soudjani , Alessandro Abate

In arXiv:1004.1407, Flandoli, Gubinelli, and Priola proposed a stochastic variant of the classical point vortex system of Helmholtz and Kirchoff in which multiplicative noise of transport-type is added to the dynamics. An open problem in…

Probability · Mathematics 2020-11-25 Matthew Rosenzweig

Queueing networks are systems of theoretical interest that find widespread use in the performance evaluation of interconnected resources. In comparison to counterpart models in genetics or mathematical biology, the stochastic (jump)…

Methodology · Statistics 2019-06-28 Iker Perez , Giuliano Casale

Asymptotic statistical theory for estimating functions is reviewed in a generality suitable for stochastic processes. Conditions concerning existence of a consistent estimator, uniqueness, rate of convergence, and the asymptotic…

Statistics Theory · Mathematics 2018-09-06 Jean Jacod , Michael Sørensen

We study mean-field control (MFC) problems with common noise using the control randomisation framework, where we substitute the control process with an independent Poisson point process, controlling its intensity instead. To address the…

Optimization and Control · Mathematics 2024-12-31 Robert Denkert , Idris Kharroubi , Huyên Pham

We prove asymptotic results for a modification of the cross-entropy estimator originally introduced by Ziv and Merhav in the Markovian setting in 1993. Our results concern a more general class of decoupled measures on shift spaces over a…

Probability · Mathematics 2024-03-26 Nicholas Barnfield , Raphaël Grondin , Gaia Pozzoli , Renaud Raquépas

In this paper, a posteriori error estimates of functional type for a stationary diffusion problem with nonsymmetric coefficients are derived. The estimate is guaranteed and does not depend on any particular numerical method. An algorithm…

Numerical Analysis · Mathematics 2014-11-24 Olli Mali

We consider application of the analytic functional approach to the conformal field theories associated with mean field theory and Wilson-Fisher fixed point. We study the constraints imposed by the crossing symmetry on the coefficients of…

High Energy Physics - Theory · Physics 2026-01-13 Bhaskar Jyoti Khanikar , Subir Mukhopadhyay

Semi-Markov processes play an important role in the effective description of partially accessible systems in stochastic thermodynamics. They occur, for instance, in coarse-graining procedures such as state lumping and when analyzing waiting…

Statistical Mechanics · Physics 2026-01-19 Alexander M. Maier , Jonas H. Fritz , Udo Seifert

The formulation of Mean Field Games (MFG) typically requires continuous differentiability of the Hamiltonian in order to determine the advective term in the Kolmogorov--Fokker--Planck equation for the density of players. However, in many…

Numerical Analysis · Mathematics 2024-04-03 Yohance A. P. Osborne , Iain Smears