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We propose a new Monte Carlo method for efficiently sampling trajectories with fixed initial and final conditions in a system with discrete degrees of freedom. The method can be applied to any stochastic process with local interactions,…

Statistical Mechanics · Physics 2012-03-30 Thierry Mora , Aleksandra M. Walczak , Francesco Zamponi

When a system is driven out of equilibrium by a time-dependent protocol that modifies the Hamiltonian, it follows a nonequilibrium path. Samples of these paths can be used in nonequilibrium work theorems to estimate equilibrium quantities,…

Statistical Mechanics · Physics 2009-05-29 David D. L. Minh

Atomistic modelling of phase transitions, chemical reactions, or other rare events that involve overcoming high free energy barriers usually entails prohibitively long simulation times. Introducing a bias potential as a function of an…

Computational Physics · Physics 2019-11-06 Federico Giberti , Bingqing Cheng , Gareth Aneurin Tribello , Michele Ceriotti

Shortcut schemes can accelerate quasi-static processes in passive systems by adding auxiliary controls to realize swift transitions between equilibrium states. In active systems, however, inherently directed motion driven by free energy…

Statistical Mechanics · Physics 2026-04-08 Guodong Cheng , Z. C. Tu , Geng Li

Counter-diabatic driving protocols were proposed as a means to do fast changes in the Hamiltonian without exciting transitions. Such driving in principle allows one to realize arbitrarily fast annealing protocols or implement fast…

Quantum Physics · Physics 2017-05-11 Dries Sels , Anatoli Polkovnikov

Big data is ubiquitous in practices, and it has also led to heavy computation burden. To reduce the calculation cost and ensure the effectiveness of parameter estimators, an optimal subset sampling method is proposed to estimate the…

Methodology · Statistics 2023-11-16 Haohui Han , Liya Fu

Optimal control theory deals with finding protocols to steer a system between assigned initial and final states, such that a trajectory-dependent cost function is minimized. The application of optimal control to stochastic systems is an…

Statistical Mechanics · Physics 2024-09-18 Julia Sanders , Marco Baldovin , Paolo Muratore-Ginanneschi

We describe a method that focuses sampling effort on a user-defined selection of a large system, which can lead to substantial decreases in computational effort by speeding up the calculation of nonbonded interactions. A naive approach can…

Statistical Mechanics · Physics 2023-08-28 Joshua Fass , Forrest York , Matthew Wittmann , Joseph Kaus , Yutong Zhao

Free energy landscapes encode the kinetics, intermediates, and transition states that govern molecular processes and are thus a key target of single biomolecule research. Typical approaches to deriving optimal, error-minimizing,…

Biological Physics · Physics 2025-11-25 Oliver Cheng , Zosia Adamska , Michael P. Brenner , Megan C. Engel

For systems in an externally controllable time-dependent potential, the optimal protocol minimizes the mean work spent in a finite-time transition between given initial and final values of a control parameter. For an initially thermalized…

Statistical Mechanics · Physics 2015-05-13 Tim Schmiedl , Eckhard Dieterich , Peter-Simon Dieterich , Udo Seifert

We introduce Adjoint Sampling, a highly scalable and efficient algorithm for learning diffusion processes that sample from unnormalized densities, or energy functions. It is the first on-policy approach that allows significantly more…

Annealing algorithms such as simulated annealing and population annealing are widely used both for sampling the Gibbs distribution and solving optimization problems (i.e. finding ground states). For both statistical mechanics and…

Statistical Mechanics · Physics 2024-05-13 Amin Barzegar , Firas Hamze , Christopher Amey , Jonathan Machta

When a system deviates from equilibrium, it is possible to manipulate and control it to drive it towards equilibrium within a finite time $t_f$, even reducing its natural relaxation time scale $\tau_{relax}$. Although numerous theoretical…

Statistical Mechanics · Physics 2024-02-26 Diego Rengifo , Gabriel Téllez

Optimal prediction approximates the average solution of a large system of ordinary differential equations by a smaller system. We present how optimal prediction can be applied to a typical problem in the field of molecular dynamics, in…

Mathematical Physics · Physics 2008-11-15 Benjamin Seibold

We investigate adaptive protocols for the elimination or reduction of the use of medications or addictive substances. We formalize this problem as online optimization, minimizing the cumulative dose subject to constraints on well-being. We…

Optimization and Control · Mathematics 2023-09-22 Paula Gradu , Benjamin Recht

Rare event simulation and estimation for systems in equilibrium are among the most challenging topics in molecular dynamics. As was shown by Jarzynski and others, nonequilibrium forcing can theoretically be used to obtain equilibrium rare…

Optimization and Control · Mathematics 2015-06-11 Carsten Hartmann , Christof Schütte

We show that the numerical method based on the off-equilibrium fluctuation-dissipation relation does work and is very useful and powerful in the study of disordered systems which show a very slow dynamics. We have verified that it gives the…

Disordered Systems and Neural Networks · Physics 2009-10-31 Giorgio Parisi , Federico Ricci-Tersenghi , Juan J. Ruiz-Lorenzo

A simple, general and practically exact method is developed for the equilibrium properties of the macroscopic physical systems with translational symmetry. Applied to the Ising model in two and three dimension, a modest calculation gives…

Strongly Correlated Electrons · Physics 2015-05-19 S. G. Chung

In this note we address the problem of indirect adaptive (regulation or tracking) control of nonlinear, input affine dissipative systems. It is assumed that the supply rate, the storage and the internal dissipation functions may be…

Systems and Control · Electrical Eng. & Systems 2022-01-19 Romeo Ortega , Rafael Cisneros , Lei Wang , Arjan van der Schaft

System performance for networks composed of interconnected subsystems can be increased if the traditionally separated subsystems are jointly optimized. Recently, parallel and distributed optimization methods have emerged as a powerful tool…

Optimization and Control · Mathematics 2013-02-14 Ion Necoara , Valentin Nedelcu , Ioan Dumitrache