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In this paper we analyze the entropy and entropy production of a non-isolated quantum system described within the quantum Brownian motion framework. This is a very general and paradigmatic framework for describing non-isolated quantum…

Statistical Mechanics · Physics 2020-09-09 G. A. Weiderpass , A. O. Caldeira

Influence maximization in social networks has typically been studied in the context of contagion models and irreversible processes. In this paper, we consider an alternate model that treats individual opinions as spins in an Ising system at…

Disordered Systems and Neural Networks · Physics 2017-02-21 Christopher Lynn , Daniel D. Lee

We study the expectation value of the logarithm of the partition function of large binary-to-binary lattice-gas Restricted Boltzmann Machines (RBMs) within a replica-symmetric ansatz, averaging over the disorder represented by the…

Disordered Systems and Neural Networks · Physics 2023-01-25 David C. Hoyle

Random matrix ensembles (RME) of quantum statistical Hamiltonian operators, {\em e.g.} Gaussian random matrix ensembles (GRME) and Ginibre random matrix ensembles (Ginibre RME), found applications in literature in study of following quantum…

Statistical Mechanics · Physics 2007-05-23 Maciej M. Duras

Biological information processing networks consist of many components, which are coupled by an even larger number of complex multivariate interactions. However, analyses of data sets from fields as diverse as neuroscience, molecular…

Quantitative Methods · Quantitative Biology 2016-03-23 Lina Merchan , Ilya Nemenman

We develop a method using a coarse graining of the energy fluctuations of an equilibrium quantum system which produces simple parameterizations for the behaviour of the system. As an application, we use these methods to gain more…

Statistical Mechanics · Physics 2007-05-23 Jani Lukkarinen

We present a universal thermodynamic framework for quantum systems that may be strongly coupled to thermal environments. Unlike previous approaches, our method enables a clear definition of thermostatic properties while preserving the same…

Quantum Physics · Physics 2026-04-16 Ignacio González , Sagnik Chakraborty , Ángel Rivas

A new approach to maximum likelihood learning of discrete graphical models and RBM in particular is introduced. Our method, Perturb and Descend (PD) is inspired by two ideas (I) perturb and MAP method for sampling (II) learning by…

Neural and Evolutionary Computing · Computer Science 2014-05-08 Siamak Ravanbakhsh , Russell Greiner , Brendan Frey

The thermodynamic maximum principle for the Boltzmann-Gibbs-Shannon (BGS) entropy is reconsidered by combining elements from group and measure theory. Our analysis starts by noting that the BGS entropy is a special case of relative entropy.…

Statistical Mechanics · Physics 2008-11-26 Jörn Dunkel , Peter Talkner , Peter Hänggi

Exploring the bulk-boundary correspondences and the boundary-induced phenomena in the strongly-correlated quantum systems belongs to the most fundamental topics of condensed matter physics. In this work, we study the bulk-boundary…

Quantum Physics · Physics 2023-10-18 Ding-Zu Wang , Guo-Feng Zhang , Maciej Lewenstein , Shi-Ju Ran

Building a good generative model for image has long been an important topic in computer vision and machine learning. Restricted Boltzmann machine (RBM) is one of such models that is simple but powerful. However, its restricted form also has…

Machine Learning · Computer Science 2016-11-24 Hengyuan Hu , Lisheng Gao , Quanbin Ma

The geometric Brownian motion (GBM) is widely employed for modeling stochastic processes, yet its solutions are characterized by the log-normal distribution. This comprises predictive capabilities of GBM mainly in terms of forecasting…

Data Analysis, Statistics and Probability · Physics 2024-03-19 Rishabh Gupta , Ewa A. Drzazga-Szczȩśniak , Sabre Kais , Dominik Szczȩśniak

Machine learning representations of many-body quantum states have recently been introduced as an ansatz to describe the ground states and unitary evolutions of many-body quantum systems. We explore one of the most important representations,…

Quantum Physics · Physics 2019-01-10 Zhih-Ahn Jia , Yuan-Hang Zhang , Yu-Chun Wu , Liang Kong , Guang-Can Guo , Guo-Ping Guo

The Restricted Boltzmann Machine (RBM), an important tool used in machine learning in particular for unsupervized learning tasks, is investigated from the perspective of its spectral properties. Starting from empirical observations, we…

Disordered Systems and Neural Networks · Physics 2018-01-17 Aurélien Decelle , Giancarlo Fissore , Cyril Furtlehner

Most of the existing classification methods are aimed at minimization of empirical risk (through some simple point-based error measured with loss function) with added regularization. We propose to approach this problem in a more information…

Machine Learning · Computer Science 2015-01-22 Wojciech Marian Czarnecki , Jacek Tabor

We investigate the maximum caliber variational principle as an inference algorithm used to predict dynamical properties of complex nonequilibrium, stationary, statistical systems in the presence of incomplete information. Specifically, we…

Statistical Mechanics · Physics 2016-12-28 Carlo Cafaro , Sean Alan Ali

Temperature of a finite-sized system fluctuates due to the thermal fluctuations. However, a systematic mathematical framework for measuring or estimating the temperature is still underdeveloped. Here, we incorporate the estimation theory in…

Statistical Mechanics · Physics 2026-03-17 Shaoyong Zhang , Zhaoyu Fei , Xiaoguang Wang

The physical origin of the backbendings in the equations of state of finite but not necessarily small systems is studied in the Ising model with fixed magnetization (IMFM) by means of the topological properties of the observable…

Statistical Mechanics · Physics 2009-11-10 F. Gulminelli , J. M. Carmona , Ph. Chomaz , J. Richert , S. Jimenez , V. Regnard

Isolated quantum systems follow the unitary evolution, which guarantees the full many body state always keeps a constant entropy as its initial one. In comparison, the local subsystems exhibit relaxation behavior and evolve towards certain…

Statistical Mechanics · Physics 2023-08-29 Tai Kang , Sheng-Wen Li

This paper draws attention to a hardware system which can be engineered so that its intrinsic physics is described by the generalized Ising model and can encode the solution to many important NP-hard problems as its ground state. The basic…

Mesoscale and Nanoscale Physics · Physics 2017-03-28 Brian Sutton , Kerem Yunus Camsari , Behtash Behin-Aein , Supriyo Datta
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