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Thermodynamic description of a model system with magnetoelastic coupling is presented. The elastic, vibrational, electronic and magnetic energy contributions are taken into account. The long-range RKKY interaction is considered together…

Statistical Mechanics · Physics 2018-02-01 T. Balcerzak , K. Szałowski , M. Jaščur

In the past decade, matrix factorization has been extensively researched and has become one of the most popular techniques for personalized recommendations. Nevertheless, the dot product adopted in matrix factorization based recommender…

Information Retrieval · Computer Science 2018-06-05 Shuai Zhang , Lina Yao , Yi Tay , Xiwei Xu , Xiang Zhang , Liming Zhu

We propose utilizing entropy as a diagnostic tool to distinguish between constant and dynamical dark energy models. Entropy, a measure of the system's disorder or information content, captures the complexity and evolution of the universe.…

General Relativity and Quantum Cosmology · Physics 2025-07-16 Tanisha Joshi

Comparison of the thermodynamic entropy with Boltzmann's principle shows that under conditions of constant volume the total number of arrangements in simple thermodynamic systems with temperature-independent heat capacities is TC/k. A…

General Physics · Physics 2009-11-13 David Sands

The metriplectic formalism is useful for describing complete dynamical systems which conserve energy and produce entropy. This creates challenges for model reduction, as the elimination of high-frequency information will generally not…

Numerical Analysis · Mathematics 2022-12-28 Anthony Gruber , Max Gunzburger , Lili Ju , Zhu Wang

We propose a new method for analyzing a set of parameters in a multiple criteria ranking method. Unlike the existing techniques, we do not use any optimization technique, instead incorporating and extending a Segmenting Description…

Artificial Intelligence · Computer Science 2019-03-06 Milosz Kadzinski , Jan Badura , Jose Rui Figueira

We consider the problem of ranking $n$ experts according to their abilities, based on the correctness of their answers to $d$ questions. This is modeled by the so-called crowd-sourcing model, where the answer of expert $i$ on question $k$…

Statistics Theory · Mathematics 2025-12-25 Alexandra Carpentier , Nicolas Verzelen

Multiple-try Metropolis (MTM) is a popular Markov chain Monte Carlo method with the appealing feature of being amenable to parallel computing. At each iteration, it samples several candidates for the next state of the Markov chain and…

Computation · Statistics 2023-08-25 Philippe Gagnon , Florian Maire , Giacomo Zanella

Improvement of thermoelectric systems in terms of performance and range of applications relies on progress in materials science and optimization of device operation. In this chapter, we focuse on optimization by taking into account the…

Classical Physics · Physics 2013-09-02 H. Ouerdane , C. Goupil , Y. Apertet , A. Michot , A. Abbout

In this work, a composite economic model predictive control (CEMPC) is proposed for the optimal operation of a stand-alone integrated energy system (IES). Time-scale multiplicity exists in IESs dynamics is taken into account and addressed…

Systems and Control · Electrical Eng. & Systems 2022-05-24 Long Wu , Xunyuan Yin , Lei Pan , Jinfeng Liu

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

Enzyme kinetics is very often characterised by the irreversible Michaelis-Menten (MM) equation. However, in open chemical reaction networks such as metabolic pathways, this approach can lead to significant kinetic and thermodynamic…

Biological Physics · Physics 2020-06-12 Valérie Voorsluijs , Francesco Avanzini , Massimiliano Esposito

Diffusion models (DMs) have recently gained significant interest for their exceptional potential in recommendation tasks. This stems primarily from their prominent capability in distilling, modeling, and generating comprehensive user…

Information Retrieval · Computer Science 2025-11-26 Ximing Chen , Pui Ieng Lei , Yijun Sheng , Yanyan Liu , Zhiguo Gong

We develop a thermodynamic theory for machine learning (ML) systems. Similar to physical thermodynamic systems which are characterized by energy and entropy, ML systems possess these characteristics as well. This comparison inspire us to…

Machine Learning · Computer Science 2024-04-23 Dong Zhang

One of the key objectives in investigating small stochastic systems is the development of micrometer-sized engines and the understanding of their thermodynamics. However, the primary mathematical tool used for this purpose, the overdamped…

Statistical Mechanics · Physics 2025-03-31 Shakul Awasthi , Hyunggyu Park , Jae Sung Lee

The TODIM method (an acronym in Portuguese for interactive and multiple criteria decision-making) with entropy weights is influenced by rank reversal, a phenomenon where the order of two alternatives changes following the addition of…

Optimization and Control · Mathematics 2025-09-11 Lisheng Jiang , Tianyu Zhang , Shiyu Yan , Ran Fang

Information-processing systems that coordinate multiple agents and objectives face fundamental thermodynamic constraints. We show that solutions with maximum utility to act as coordination focal points have a much higher selection pressure…

Artificial Intelligence · Computer Science 2025-10-16 Atma Anand

For long time the measurement of innovation has been in the forefront of policy makers' and researchers' agenda worldwide. Therefore, there is an ongoing debate about which indicators should be used to measure innovation. Recent approaches…

General Finance · Quantitative Finance 2019-05-31 Salvatore Corrente , Ana Garcia-Bernabeu , Salvatore Greco , Teemu Makkonen

This paper presents a conceptual model describing the medium and long-term co-evolution of natural and socio-economic subsystems of Earth. An economy is viewed as an out-of-equilibrium dissipative structure that can only be maintained with…

General Economics · Economics 2022-05-09 Éric Herbert , and Gael Giraud , Aurélie Louis-Napoléon , Christophe Goupil

We have formulated a family of machine learning problems as the time evolution of Parametric Probabilistic Models (PPMs), inherently rendering a thermodynamic process. Our primary motivation is to leverage the rich toolbox of thermodynamics…

Machine Learning · Computer Science 2024-01-31 Shervin Sadat Parsi