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Recently a generalized master equation was derived that extends the Lindblad theory to highly non-Markovian quantum processes (H.-P. Breuer, Phys. Rev. A \textbf{75}, 022103 (2007)). We perform a stochastic unravelling of this master…

Quantum Physics · Physics 2009-04-23 Mervlyn Moodley , Francesco Petruccione

An extension and generalization of a recently presented approach for the analysis of Langevin-type stochastic processes in the presence of strong measurement noise is presented. For a stochastic process in N dimensions which is superimposed…

Data Analysis, Statistics and Probability · Physics 2012-10-23 B. Lehle

We proposed a new technique to accelerate sampling methods for solving difficult optimization problems. Our method investigates the intrinsic connection between posterior distribution sampling and optimization with Langevin dynamics, and…

Machine Learning · Computer Science 2023-01-31 Junlong Lyu , Zhitang Chen , Wenlong Lyu , Jianye Hao

We consider the class of two-lag linear delay differential equations and develop a series expansion to solve for the roots of the nonlinear characteristic equation. Supporting numerical results are presented along with application of our…

Classical Analysis and ODEs · Mathematics 2012-06-28 David Bortz

We study a multigrid method for solving large linear systems of equations with tensor product structure. Such systems are obtained from stochastic finite element discretization of stochastic partial differential equations such as the…

Numerical Analysis · Mathematics 2017-04-11 Howard C. Elman , Tengfei Su

Stochastic Langevin dynamics has been traditionally used as a tool to describe non-equilibrium processes. When utilized in systems with collective modes, traditional Langevin dynamics relaxes all modes indiscriminately, regardless of their…

Statistical Mechanics · Physics 2018-06-06 A. Tamm , M. Caro , A. Caro , G. Samolyuk , M. Klintenberg , A. A. Correa

First-order stochastic methods are the state-of-the-art in large-scale machine learning optimization owing to efficient per-iteration complexity. Second-order methods, while able to provide faster convergence, have been much less explored…

Machine Learning · Statistics 2017-12-01 Naman Agarwal , Brian Bullins , Elad Hazan

We prove existence, regularity in H\"older classes and estimates from above and below of the fundamental solution of the stochastic Langevin equation. This degenerate SPDE satisfies the weak H\"ormander condition. We use a Wentzell's…

Probability · Mathematics 2019-10-14 Andrea Pascucci , Antonello Pesce

The complex Langevin method and the generalized Lefschetz-thimble method are two closely related approaches to the sign problem, which are both based on complexification of the original dynamical variables. The former can be viewed as a…

High Energy Physics - Lattice · Physics 2017-06-28 Jun Nishimura , Shinji Shimasaki

We introduce a continuous policy-value iteration algorithm where the approximations of the value function of a stochastic control problem and the optimal control are simultaneously updated through Langevin-type dynamics. This framework…

Optimization and Control · Mathematics 2025-06-11 Qi Feng , Gu Wang

A natural method for the introduction of second-order derivatives of the log likelihood into MCMC algorithms is introduced, based on Taylor expansion of the Langevin equation followed by exact solution of the truncated system.

Computation · Statistics 2015-07-24 Thomas House

We introduce a numerical method for Brownian dynamics with position dependent diffusion tensor which is second order accurate for sampling the invariant measure while requiring only one force evaluation per timestep. Analysis of the…

Numerical Analysis · Mathematics 2025-01-09 Eugen Bronasco , Benedict Leimkuhler , Dominic Phillips , Gilles Vilmart

A stochastic leap-frog algorithm for the numerical integration of Brownian motion stochastic differential equations with multiplicative noise is proposed and tested. The algorithm has a second-order convergence of moments in a finite time…

Computational Physics · Physics 2009-10-31 Ji Qiang , Salman Habib

In this paper we propose and analyze finite element discontinuous Galerkin methods for the one- and two-dimensional stochastic Maxwell equations with multiplicative noise. The discrete energy law of the semi-discrete DG methods were…

Numerical Analysis · Mathematics 2022-04-21 Jiawei Sun , Chi-Wang Shu , Yulong Xing

The Langevin equation with a multiplicative L\'evy white noise is solved. The noise amplitude and the drift coefficient have a power-law form. A validity of ordinary rules of the calculus for the Stratonovich interpretation is discussed.…

Statistical Mechanics · Physics 2015-05-18 Tomasz Srokowski

We present a new class of numerical methods for solving stochastic differential equations with additive noise on general Riemannian manifolds with high weak order of accuracy. In opposition to the popular approach with projection methods,…

Numerical Analysis · Mathematics 2025-06-19 Eugen Bronasco , Adrien Busnot Laurent , Baptiste Huguet

We present a perturbation method for determining the moment stability of linear ordinary differential equations with parametric forcing by colored noise. In particular, the forcing arises from passing white noise through an $n$th order…

Mathematical Physics · Physics 2013-01-11 Timothy Blass , L. A. Romero

It is well known that second order homogeneous linear ordinary differential equations with slowly varying coefficients admit slowly varying phase functions. This observation underlies the Liouville-Green method and many other techniques for…

Numerical Analysis · Mathematics 2022-11-28 Kirill Serkh , James Bremer

The generalized Langevin equation is used as a model for various coarse-grained physical processes, e.g., the time evolution of the velocity of a given larger particle in an implicitly represented solvent, when the relevant time scales of…

Statistical Mechanics · Physics 2025-11-13 Niklas Bockius , Maximilian Braun , Kay Hofmann , Friederike Schmid , Martin Hanke

Inspired by path-integral solutions to the quantum relaxation problem, we develop a numerical method to solve classical stochastic differential equations with multiplicative noise that avoids averaging over trajectories. To test the method,…

Statistical Mechanics · Physics 2023-12-12 Ryan T. Grimm , Joel D. Eaves
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