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We develop the stochastic approach to thermodynamics based on the stochastic dynamics, which can be discrete (master equation) continuous (Fokker-Planck equation), and on two assumptions concerning entropy. The first is the definition of…

Statistical Mechanics · Physics 2015-06-11 Tânia Tomé , Mário J. de Oliveira

We present a new and efficient optimization method to determine the structure of disordered systems in agreement with available experimental data. Our approach permits the application of accurate electronic structure calculations within the…

Materials Science · Physics 2014-06-23 Jan H. Los , Thomas D. Kühne

Metaheuristics, as the simulated annealing used in the optimization of disordered systems, goes beyond physics, and the traveling salesman is a paradigmatic NP-complete problem that allows inferring important theoretical properties of the…

Disordered Systems and Neural Networks · Physics 2021-09-14 Roberto da Silva , Eliseu Venites Filho , Alexandre Alves

Nested simulation is a natural approach to tackle nested estimation problems in operations research and financial engineering. The outer-level simulation generates outer scenarios and the inner-level simulations are run in each outer…

Risk Management · Quantitative Finance 2022-03-31 Kun Zhang , Ben Mingbin Feng , Guangwu Liu , Shiyu Wang

In systems with detailed balance, the stationary distribution and the equilibrium distribution are identical, creating a clear connection between energetic and entropic quantities. Many driven systems violate detailed balance and still pose…

Statistical Mechanics · Physics 2025-01-22 Markus Hofer , Jan Korbel , Rudolf Hanel , Stefan Thurner

In the process of analyzing the axiomatic principles underlying statistical physics, when modeling the most probable stationary macrostates of non-ergodic closed systems, a forecast was obtained about a possible limitation purview of the…

Statistical Mechanics · Physics 2022-09-07 Vladimir Savukov

We introduce a novel approach based on stochastic optimization to find the optimal sampling distribution for the data-driven stability analysis of switched linear systems. Our goal is to address limitations of existing approaches, in…

Optimization and Control · Mathematics 2025-09-01 Alexis Vuille , Guillaume O. Berger , Raphaël M. Jungers

We introduce a novel method of quantum emulation of a classical reversible cellular automaton. By applying this method to a chaotic cellular automaton, the obtained quantum many-body system thermalizes while all the energy eigenstates and…

Statistical Mechanics · Physics 2018-07-03 Naoto Shiraishi

Quantum annealing is a computational paradigm in which optimisation problems are mapped onto the energy landscape of an interacting quantum system and explored through its dynamical evolution. By continuously transforming a simple initial…

Quantum Physics · Physics 2026-05-11 Steven Abel , Andrei Constantin , Luca A. Nutricati

By contrasting the performance of two quantum annealers operating at different temperatures, we address recent questions related to the role of temperature in these devices and their function as `Boltzmann samplers'. Using a method to…

Quantum Physics · Physics 2018-01-03 Jeffrey Marshall , Eleanor G. Rieffel , Itay Hen

Low-order thermoacoustic models are qualitatively correct, but they are typically quantitatively inaccurate. We propose a time-domain bias-aware method to make qualitatively low--order models quantitatively (more) accurate. First, we…

Fluid Dynamics · Physics 2022-11-10 Andrea Nóvoa , Luca Magri

Optimisation problems in science and engineering typically involve finding the ground state (i.e. the minimum energy configuration) of a cost function with respect to many variables. If the variables are corrupted by noise then this…

Quantum Physics · Physics 2016-03-08 Nicholas Chancellor , Szilard Szoke , Walter Vinci , Gabriel Aeppli , Paul A. Warburton

We present a novel approach to investigate the long-time stochastic dynamics of multi-dimensional classical systems, in contact with a heat-bath. When the potential energy landscape is rugged, the kinetics displays a decoupling of short and…

Soft Condensed Matter · Physics 2013-05-29 O. Corradini , P. Faccioli , H. Orland

Thermodynamic computing exploits fluctuations and dissipation in physical systems to efficiently solve various mathematical problems. For example, it was recently shown that certain linear algebra problems can be solved thermodynamically,…

Statistical Mechanics · Physics 2024-01-08 Samuel Duffield , Maxwell Aifer , Gavin Crooks , Thomas Ahle , Patrick J. Coles

We propose a computational framework to quantify (measure) and to optimize the reliability of complex systems. The approach uses a graph representation of the system that is subject to random failures of its components (nodes and edges).…

Optimization and Control · Mathematics 2021-06-25 Joshua L. Pulsipher , Victor M. Zavala

Classical approaches to experimental design assume that intervening on one unit does not affect other units. There are many important settings, however, where this non-interference assumption does not hold, as when running experiments on…

Optimization and Control · Mathematics 2020-07-01 Stefan Wager , Kuang Xu

Several approximations are made to study the microcanonical formalism that are valid in the thermodynamics limit. Usually it is assumed that: 1)Stirling approximation can be used to evaluate the number of microstates; 2) the surface entropy…

General Physics · Physics 2015-10-07 E. N. Miranda , Dalia S. Bertoldi

Stochastic Thermodynamics (ST) extends the notions of classical thermodynamics to trajectories taken from a nonequilibrium ensemble. This extension yields a simple approach to fluctuation relations in small systems. Multiple time- and…

Statistical Mechanics · Physics 2012-10-19 Bernhard Altaner

It is a known fact that not all controllable systems can be asymptotically stabilized by a continuous static feedback. Several approaches have been developed throughout the last decades, including time-varying, dynamical and even…

Optimization and Control · Mathematics 2018-06-25 Pavel Osinenko , Lukas Beckenbach , Stefan Streif

Analog quantum simulation is a promising path towards solving classically intractable problems in many-body physics on near-term quantum devices. However, the presence of noise limits the size of the system and the length of time that can…

Quantum Physics · Physics 2024-10-22 Yiyi Cai , Yu Tong , John Preskill