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We propose a general strategy to discretize the Dyson series without applying direct numerical quadrature to high-dimensional integrals, and extend this framework to open quantum systems. The resulting discretization can also be interpreted…

Quantum Physics · Physics 2025-10-20 Zhenning Cai , Yixiao Sun , Geshuo Wang

Simulation of quantum chemistry is expected to be a principal application of quantum computing. In quantum simulation, a complicated Hamiltonian describing the dynamics of a quantum system is decomposed into its constituent terms, where the…

Quantum Physics · Physics 2020-03-04 Yingkai Ouyang , David R. White , Earl T. Campbell

A new approach for enhancing the process-variation tolerance of digital circuits is described. We extend recent advances in statistical timing analysis into an optimization framework. Our objective is to reduce the performance variance of a…

Hardware Architecture · Computer Science 2011-11-09 Osama Neiroukh , Xiaoyu Song

The behavior of materials is influenced by a wide range of phenomena occurring across various time and length scales. To better understand the impact of microstructure on macroscopic response, multiscale modeling strategies are essential.…

Importance sampling of trajectories has proved a uniquely successful strategy for exploring rare dynamical behaviors of complex systems in an unbiased way. Carrying out this sampling, however, requires an ability to propose changes to…

Statistical Mechanics · Physics 2015-07-01 Todd R. Gingrich , Phillip L. Geissler

This work derives how the convergence of stochastic Lagrangian/Eulerian simulations depends on the number of computational parcels, particularly for the case of spray modeling. A new, simple, formula is derived that can be used for managing…

Fluid Dynamics · Physics 2018-01-31 David P. Schmidt , Frederick Bedford

Longitudinal models with dynamics governed by differential equations may require numerical integration alongside parameter estimation. We have identified a situation where the numerical integration introduces error in such a way that it…

Other Statistics · Statistics 2026-02-10 Tess O'Brien , Matthew T. Moores , David Warton , Daniel Falster

An issue for molecular dynamics simulations is that events of interest often involve timescales that are much longer than the simulation time step, which is set by the fastest timescales of the model. Because of this timescale separation,…

Statistical Mechanics · Physics 2024-08-15 John Strahan , Chatipat Lorpaiboon , Jonathan Weare , Aaron R. Dinner

Optimization of expensive computer models with the help of Gaussian process emulators in now commonplace. However, when several (competing) objectives are considered, choosing an appropriate sampling strategy remains an open question. We…

Optimization and Control · Mathematics 2013-10-03 Victor Picheny

The Lagrangian probability-density-function model, proposed in Part I for dense particle-laden turbulent flows, is validated here against Eulerian-Lagrangian direct numerical simulation (EL) data for different homogeneous flows, namely…

Fluid Dynamics · Physics 2018-03-02 Alessio Innocenti , Rodney O Fox , Maria Vittoria Salvetti , Sergio Chibbaro

This paper considers the strong error analysis of the Euler and fast Euler methods for nonlinear overdamped generalized Langevin equations driven by the fractional noise. The main difficulty lies in handling the interaction between the…

Numerical Analysis · Mathematics 2023-02-21 Xinjie Dai , Jialin Hong , Derui Sheng , Tau Zhou

This paper presents a solution for recovering full trajectory information, via the calculation of the posterior of the set of trajectories, from a sequence of multitarget (unlabelled) filtering densities and the multitarget dynamic model.…

Signal Processing · Electrical Eng. & Systems 2021-02-23 Yuxuan Xia , Lennart Svensson , Ángel F. García-Fernández , Karl Granström , Jason L. Williams

We consider numerical schemes for computing the linear response of steady-state averages of stochastic dynamics with respect to a perturbation of the drift part of the stochastic differential equation. The schemes are based on Girsanov's…

Numerical Analysis · Mathematics 2019-12-18 Petr Plechac , Gabriel Stoltz , Ting Wang

This work proposes a Bayesian inference method for the reduced-order modeling of time-dependent systems. Informed by the structure of the governing equations, the task of learning a reduced-order model from data is posed as a Bayesian…

Numerical Analysis · Mathematics 2023-01-18 Mengwu Guo , Shane A. McQuarrie , Karen E. Willcox

Electron collisions, described by stochastic differential equations (SDEs), were simulated using a second-order weak convergence algorithm. Using stochastic analysis, we constructed an SDE for energetic electrons in Lorentz plasma to…

Plasma Physics · Physics 2018-11-15 Wentao Wu , Jian Liu , Hong Qin

In engineering, it is a common desire to couple existing simulation tools together into one big system by passing information from subsystems as parameters into the subsystems under influence. As executed at fixed time points, this data…

Numerical Analysis · Mathematics 2017-04-25 Thilo Moshagen

The development of numerical methods capable of simulating realistic materials with strongly correlated electrons, with controllable errors, is a central challenge in quantum many-body physics. Here we describe how a hybrid between…

Strongly Correlated Electrons · Physics 2015-04-23 Alexei A. Kananenka , Emanuel Gull , Dominika Zgid

We study counting statistics of number of transitions in a stochastic process. For mesoscopic systems, a path integral formulation for the counting statistics has already been derived. We here show that it is also possible to derive the…

Statistical Mechanics · Physics 2009-07-21 Jun Ohkubo

Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among many complex systems in science and engineering. The existence of a strange attractor in the turbulent…

Fluid Dynamics · Physics 2018-02-23 Andrew J. Majda , Di Qi

We establish a large deviation principle for time dependent trajectories (paths) of the empirical density of $N$ particles with long range interactions, for homogeneous systems. This result extends the classical kinetic theory that leads to…

Statistical Mechanics · Physics 2022-01-19 Ouassim Feliachi , Freddy Bouchet