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Classical thermodynamics treats temperature as a state variable characterizing systems in equilibrium with idealized infinite reservoirs. We argue that this framing, while computationally exact, obscures an essential physical reality: any…

Quantum Physics · Physics 2026-04-14 David Vaknin

Bond rating Transition Probability Matrices (TPMs) are built over a one-year time-frame and for many practical purposes, like the assessment of risk in portfolios or the computation of banking Capital Requirements (e.g. the new IFRS 9…

Risk Management · Quantitative Finance 2017-10-17 Greig Smith , Goncalo dos Reis

We consider the problem of approximating the stationary distribution of an ergodic Markov chain given a set of sampled transitions. Classical simulation-based approaches assume access to the underlying process so that trajectories of…

Machine Learning · Computer Science 2020-03-03 Junfeng Wen , Bo Dai , Lihong Li , Dale Schuurmans

This paper presents a new concept of controlled dissipativity as an extension of the standard dissipativity property to systems with parameter-varying storage functions under the framework of economic model predictive control (EMPC). Based…

Optimization and Control · Mathematics 2023-02-22 Zihang Dong , David Angeli , Goran Strbac

We study the entanglement entropy between the two outgoing particles in an elastic scattering process. It is formulated within an S-matrix formalism using the partial wave expansion of two-body states, which plays a significant role in our…

High Energy Physics - Theory · Physics 2016-07-08 Robi Peschanski , Shigenori Seki

In a scattering process, the final state is determined by an initial state and an S-matrix. We focus on two-particle scattering processes and consider the entanglement between these particles. For two types initial states; i.e., an…

High Energy Physics - Theory · Physics 2015-05-20 I. Y. Park , Shigenori Seki , Sang-Jin Sin

The contact process is an emblematic model of a non-equilibrium system, containing a phase transition between inactive and active dynamical regimes. In the epidemiological context, the model is known as the susceptible-infected-susceptible…

Statistical Mechanics · Physics 2023-05-12 Wout Merbis , Clélia de Mulatier , Philippe Corboz

We revisit textbook claims that entropy must increase and show that, under time-reversal invariant microscopic dynamics, no universal trajectory-wise or statistical assertion that the coarse-grained entropy $S(t)$ is non-decreasing can…

Statistical Mechanics · Physics 2026-03-06 Ting Peng

We consider the problem of minimizing the entropy, energy, or exergy production for state transitions of irreversible port-Hamiltonian systems subject to control constraints. Via a dissipativity-based analysis we show that optimal solutions…

Optimization and Control · Mathematics 2022-02-21 Bernhard Maschke , Friedrich Philipp , Manuel Schaller , Karl Worthmann , Timm Faulwasser

New sampling algorithms based on simulating continuous-time stochastic processes called piece-wise deterministic Markov processes (PDMPs) have shown considerable promise. However, these methods can struggle to sample from multi-modal or…

Methodology · Statistics 2022-05-31 Matthew Sutton , Robert Salomone , Augustin Chevallier , Paul Fearnhead

We consider continuous-time, finite-horizon, optimal quadratic control of semi-Markov jump linear systems (S-MJLS), and develop principled approximations through Markov-like representations for the holding-time distributions. We adopt a…

Systems and Control · Computer Science 2017-11-07 Saeid Jafari , Ketan Savla

Transfer entropy has been used to quantify the directed flow of information between source and target variables in many complex systems. While transfer entropy was originally formulated in discrete time, in this paper we provide a framework…

Information Theory · Computer Science 2017-04-05 Richard E. Spinney , Mikhail Prokopenko , Joseph T. Lizier

Markov chain Monte Carlo (MCMC) methods to sample from a probability distribution $\pi$ defined on a space $(\Theta,\mathcal{T})$ consist of the simulation of realisations of Markov chains $\{\theta_{n},n\geq1\}$ of invariant distribution…

Computation · Statistics 2021-01-06 Christophe Andrieu , Sinan Yıldırım , Arnaud Doucet , Nicolas Chopin

Continuous-time Markov chains are mathematical models that are used to describe the state-evolution of dynamical systems under stochastic uncertainty, and have found widespread applications in various fields. In order to make these models…

Probability · Mathematics 2017-06-22 Thomas Krak , Jasper De Bock , Arno Siebes

Markov chain Monte Carlo (MCMC) methods are frequently used to approximately simulate high-dimensional, multimodal probability distributions. In adaptive MCMC methods, the transition kernel is changed "on the fly" in the hope to speed up…

Probability · Mathematics 2014-06-04 Winfried Barta

A new variational method for studying the equilibrium states of an interacting particles system has been proposed. The statistical description of the system is realized by means of a density matrix. This method is used for description of…

General Physics · Physics 2014-12-19 Boris Bondarev

The reduced density matrix that characterises the state of an open quantum system is a projection from the full density matrix of the quantum system and its environment, and there are many full density matrices consistent with a given…

Quantum Physics · Physics 2024-11-28 Claudia L. Clarke , Ian J. Ford

The Markovian evolution of an open quantum system is characterized by a positive entropy production, while the global entropy gets redistributed between the system and the environment degrees of freedom. Starting from these premises, we…

Entanglement entropy in topologically ordered matter phases has been computed extensively using various methods. In this paper, we study the entanglement entropy of topological phases in two-spaces from a new perspective---the perspective…

Strongly Correlated Electrons · Physics 2019-06-14 Yuting Hu , Yidun Wan

Systems with quenched disorder possess complex energy landscapes that are challenging to explore under the conventional Monte Carlo method. In this work, we implement an efficient entropy sampling scheme for accurate computation of the…

Disordered Systems and Neural Networks · Physics 2025-05-08 Yi Liu , Ding Wang , Xin Wang , Dao-Xin Yao , Lei-Han Tang
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