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Stochastic processes that are randomly reset to an initial condition serve as a showcase to investigate non-equilibrium steady states. However, all existing results have been restricted to the special case of memoryless resetting protocols.…

Statistical Mechanics · Physics 2016-03-23 Stephan Eule , Jakob Metzger

The mathematical physics of mechanical systems in thermal equilibrium is a well studied, and relatively easy, subject, because the Gibbs distribution is in general an adequate guess for the equilibrium state. On the other hand, the…

Mathematical Physics · Physics 2007-05-23 Jean-Pierre Eckmann

The energy test is a powerful binning-free, multi-dimensional and distribution-free tool that can be applied to compare a measurement to a given prediction (goodness-of-fit) or to check whether two data samples originate from the same…

Data Analysis, Statistics and Probability · Physics 2018-04-30 G. Zech

This thesis is devoted to the theoretical study of slow thermodynamic processes in non-equilibrium stochastic systems. Its main result is a physically and mathematically consistent construction of relevant thermodynamic quantities in the…

Statistical Mechanics · Physics 2014-07-29 Jiří Pešek

The so-called 'energy test' is a frequentist technique used in experimental particle physics to decide whether two samples are drawn from the same distribution. Its usage requires a good understanding of the distribution of the test…

Data Analysis, Statistics and Probability · Physics 2019-03-12 Thomas P. S. Gillam , Christopher G. Lester

In this paper, we focus on activating only a few sensors, among many available, to estimate the state of a stochastic process of interest. This problem is important in applications such as target tracking and simultaneous localization and…

Systems and Control · Computer Science 2016-09-28 Vasileios Tzoumas , Nikolay A. Atanasov , Ali Jadbabaie , George J. Pappas

A general formulation of stochastic thermodynamics is presented for open systems exchanging energy and particles with multiple reservoirs. By introducing a partition in terms of "macrostates" (e.g. sets of "microstates"), the consequence on…

Statistical Mechanics · Physics 2015-06-03 Massimiliano Esposito

It is shown that a small system in thermodynamic equilibrium with a finite thermostat can have a q-exponential probability distribution which closely depends on the energy nonextensivity and the particle number of the thermostat. The…

Statistical Mechanics · Physics 2008-11-13 Congjie Ou , Wei Li , Jiulin Du , Francois Tsobnang , Jincan Chen , Alain Le Mehaute , Qiuping A. Wang

Energy system optimization models are becoming increasingly popular for analyzing energy markets, such as the impact of new policies or interactions between energy carriers. One key challenge of these models is the trade-off between…

Optimization and Control · Mathematics 2025-08-26 Beltrán Castro Gómez , Yannick Werner , Sonja Wogrin

We develop an optimization algorithm, using simulated annealing for the quantification of patterns in astronomical data based on techniques developed for robotic vision applications. The methodology falls in the category of cost…

Instrumentation and Methods for Astrophysics · Physics 2020-09-09 Maria Chira , Manolis Plionis

Boltzmann generators approach the sampling problem in many-body physics by combining a normalizing flow and a statistical reweighting method to generate samples of a physical system's equilibrium density. The equilibrium distribution is…

Computational Physics · Physics 2020-12-02 Manuel Dibak , Leon Klein , Frank Noé

Non-equilibrium states of a thermodynamic statistical system are investigated using the thermodynamic parameter of the system lifetime, first-passage time, the time before degeneration of the system under influence of fluctuations.…

Statistical Mechanics · Physics 2020-03-19 V. V. Ryazanov

Uncertainty in optimization is often represented as stochastic parameters in the optimization model. In Predict-Then-Optimize approaches, predictions of a machine learning model are used as values for such parameters, effectively…

Machine Learning · Computer Science 2025-12-03 Pieter Smet

Random perturbations applied in tandem to an ensemble of oscillating objects can synchronize their motion. We study multiple copies of an arbitrary dynamical system in a stable limit cycle, described via a standard phase reduction picture.…

Statistical Mechanics · Physics 2024-02-23 Yunxiang Song , Thomas A. Witten

An algorithmic limit of compressed sensing or related variable-selection problems is analytically evaluated when a design matrix is given by an overcomplete random matrix. The replica method from statistical mechanics is employed to derive…

Disordered Systems and Neural Networks · Physics 2018-11-14 Tomoyuki Obuchi , Yoshinori Nakanishi-Ohno , Masato Okada , Yoshiyuki Kabashima

A numerical technique is introduced that reduces exponentially the time required for Monte Carlo simulations of non-equilibrium systems. Results for the quasi-stationary probability distribution in two model systems are compared with the…

Adaptation and Self-Organizing Systems · Physics 2009-11-07 A. Bandrivskyy , S. Beri , D. G. Luchinsky , R. Mannella , P. V. E. McClintock

Stochastic process discovery is concerned with deriving a model capable of reproducing the stochastic character of observed executions of a given process, stored in a log. This leads to an optimisation problem in which the model's parameter…

Formal Languages and Automata Theory · Computer Science 2025-05-01 Pierre Cry , Paolo Ballarini , András Horváth , Pascale Le Gall

A strongly non-integrable system is expected to satisfy the eigenstate thermalization hypothesis, which states that the expectation value of an observable in an energy eigenstate is the same as the thermal value. This must be revised if the…

Statistical Mechanics · Physics 2015-11-04 Keith R. Fratus , Mark Srednicki

New continuous and stochastic extensions of the minority game, devised as a fundamental model for a market of competitive agents, are introduced and studied in the context of statistical physics. The new formulation reproduces the key…

Statistical Mechanics · Physics 2009-10-31 Andrea Cavagna , Juan P. Garrahan , Irene Giardina , David Sherrington

Autoregressive surrogate models (or \textit{emulators}) of spatiotemporal systems provide an avenue for fast, approximate predictions, with broad applications across science and engineering. At inference time, however, these models are…

Machine Learning · Computer Science 2025-07-10 Chris Pedersen , Laure Zanna , Joan Bruna