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Related papers: Unification of the complex Langevin method and the…

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A new complexity measure named as Lattice Complexity is presented for finite symbolic sequences. This measure is based on the symbolic dynamics of one-dimensional iterative maps and Lempel-Ziv Complexity. To make Lattice Complexity…

Chaotic Dynamics · Physics 2008-04-05 Da-Guan Ke , Hong Zhang , Qin-Ye Tong

A general method is proposed which allows one to estimate drift and diffusion coefficients of a stochastic process governed by a Langevin equation. It extends a previously devised approach [R. Friedrich et al., Physics Letters A 271, 217…

Data Analysis, Statistics and Probability · Physics 2009-11-11 D. Kleinhans , R. Friedrich , A. Nawroth , J. Peinke

We define a class of dynamical systems by modifying a construction due to Tao, which includes certain Furstenburg limits arising from the Liouville function. Most recent progress on the Chowla conjectures and sign patterns of the Mobius and…

Number Theory · Mathematics 2018-09-11 Will Sawin

We present a general technique for addressing sign problems that arise in Monte Carlo simulations of field theories. This method deforms the domain of the path integral to a manifold in complex field space that maximizes the average sign…

High Energy Physics - Lattice · Physics 2018-06-06 Andrei Alexandru , Paulo Bedaque , Henry Lamm , Scott Lawrence

The classical (overdamped) Langevin dynamics provide a natural algorithm for sampling from its invariant measure, which uniquely minimizes an energy functional over the space of probability measures, and which concentrates around the…

Probability · Mathematics 2023-09-26 Giovanni Conforti , Daniel Lacker , Soumik Pal

It is shown that the solution of generalized Langevin equation can be obtained on the basis of simple comparison of the time scale for the velocity autocorrelation function of a particle (atom, molecule) and of the time scale for the…

Statistical Mechanics · Physics 2017-02-28 Anatolii V. Mokshin , Bulat N. Galimzyanov

The measured time series from complex systems are renowned for their intricate stochastic behavior, characterized by random fluctuations stemming from external influences and nonlinear interactions. These fluctuations take diverse forms,…

Statistical Mechanics · Physics 2025-03-19 Pyei Phyo Lin , Matthias Wächter , Joachim Peinke , M. Reza Rahimi Tabar

This paper discusses the theory and numerical method of two-scale analysis for the multiscale Landau-Lifshitz-Gilbert equation in composite ferromagnetic materials. The novelty of this work can be summarized in three aspects: Firstly, the…

Numerical Analysis · Mathematics 2024-03-25 Xiaofei Guan , Hang Qi , Zhiwei Sun

We show how to construct the optimum superstatistical dynamical model for a given experimentally measured time series. For this purpose we generalise the superstatistics concept and study a Langevin equation with a memory kernel whose…

Statistical Mechanics · Physics 2011-01-10 Erik Van der Straeten , Christian Beck

For a system at given temperature, with energy known as a function of a set of variables, we obtain the thermal fluctuation of the evolution of the variables by replacing the phase-space with a lattice and invoking the principle of detailed…

Statistical Mechanics · Physics 2010-07-26 Jorge Berger

We propose a novel method for sampling from unnormalized Boltzmann densities based on a probability flow ordinary differential equation (ODE) derived from linear stochastic interpolants. The key innovation of our approach is the use of a…

Numerical Analysis · Mathematics 2026-03-12 Chenguang Duan , Yuling Jiao , Gabriele Steidl , Christian Wald , Jerry Zhijian Yang , Ruizhe Zhang

In this review we present the current state-of-the-art on complex Langevin simulations and their implications for the QCD phase diagram. After a short summary of the complex Langevin method, we present and discuss recent developments. Here…

High Energy Physics - Lattice · Physics 2020-10-28 Felipe Attanasio , Benjamin Jäger , Felix P. G. Ziegler

Simulation-based inference (SBI) enables Bayesian analysis when the likelihood is intractable but model simulations are available. Recent advances in statistics and machine learning, including Approximate Bayesian Computation and deep…

Methodology · Statistics 2025-09-15 Haoyu Jiang , Yuexi Wang , Yun Yang

The dynamics of a sphere fluidized in a nearly-levitating upflow of air were previously found to be identical to those of a Brownian particle in a two-dimensional harmonic trap, consistent with a Langevin equation [Ojha {\it et al.}, Nature…

Statistical Mechanics · Physics 2016-08-31 R. P. Ojha , A. R. Abate , D. J. Durian

A key task in Bayesian machine learning is sampling from distributions that are only specified up to a partition function (i.e., constant of proportionality). One prevalent example of this is sampling posteriors in parametric distributions,…

Machine Learning · Computer Science 2020-09-10 Rong Ge , Holden Lee , Andrej Risteski

Sign-based stochastic methods have gained attention due to their ability to achieve robust performance despite using only the sign information for parameter updates. However, the current convergence analysis of sign-based methods relies on…

Machine Learning · Computer Science 2023-10-24 Tao Sun , Congliang Chen , Peng Qiao , Li Shen , Xinwang Liu , Dongsheng Li

We discuss two problems in complexified auxiliary fields in fermionic effective models, the auxiliary sign problem associated with the repulsive vector-field and the choice of the cut for the scalar field appearing from the logarithmic…

High Energy Physics - Lattice · Physics 2018-04-18 Yuto Mori , Kouji Kashiwa , Akira Ohnishi

Basing on our results [1] on a representation of solutions to the Cauchy problem for multidimensional non-viscous Burgers equation obtained by a method of stochastic perturbation of the associated Langevin system, we deduce an explicit…

Analysis of PDEs · Mathematics 2013-10-29 Olga S. Rozanova

We propose a novel stochastic method to generate paths conditioned to start in an initial state and end in a given final state during a certain time $t_{f}$. These paths are weighted with a probability given by the overdamped Langevin…

Statistical Mechanics · Physics 2015-05-27 Henri Orland

In order to understand the dynamical mechanism of the friction phenomena, we heavily rely on the numerical analysis using various methods: molecular dynamics, Langevin equation, lattice Boltzmann method, Monte Carlo, e.t.c.. We propose a…

High Energy Physics - Theory · Physics 2013-05-28 Shoichi Ichinose