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Microcanonical equations for several thermodynamic properties of a system, suitable for molecular dynamics simulations, are derived from the nonextensive Tsallis entropy functional. Two possible definitions of temperature, the usual one and…

Statistical Mechanics · Physics 2011-03-21 J. Carrete , L. M. Varela , L. J. Gallego

We show that for any perfect fluid in a static spacetime, if the Einstein constraint equation is satisfied and the temperature of the fluid obeys Tolman's law, then the other components of Einstein's equation are implied by the assumption…

General Relativity and Quantum Cosmology · Physics 2015-06-18 Xiongjun Fang , Sijie Gao

We show how generalized Gibbs-Shannon entropies can provide new insights on the statistical properties of texts. The universal distribution of word frequencies (Zipf's law) implies that the generalized entropies, computed at the word level,…

Physics and Society · Physics 2017-02-15 Eduardo G. Altmann , Laercio Dias , Martin Gerlach

The physical foundations of a variety of emerging technologies --- ranging from the applications of quantum entanglement in quantum information to the applications of nonequilibrium bulk and interface phenomena in microfluidics, biology,…

Quantum Physics · Physics 2014-03-25 Gian Paolo Beretta , Enzo Zanchini

Entropy can signify different things: For instance, heat transfer in thermodynamics or a measure of information in data analysis. Many entropies have been introduced and it can be difficult to ascertain their different importance and…

Mathematical Physics · Physics 2025-07-10 Henrik Jeldtoft Jensen , Piergiulio Tempesta

For statistical systems that violate one of the four Shannon-Khinchin axioms, entropy takes a more general form than the Boltzmann-Gibbs entropy. The framework of superstatistics allows one to formulate a maximum entropy principle with…

Classical Physics · Physics 2012-11-13 Rudolf Hanel , Stefan Thurner , Murray Gell-Mann

The tests of the constancy of the fundamental constants are tests of the local position invariance and thus of the equivalence principle. We summarize the various constraints that have been obtained and then describe the connection between…

General Relativity and Quantum Cosmology · Physics 2015-05-13 Jean-Philippe Uzan

The notion of $\Delta$-weakly mixing set is introduced, which shares similar properties of weakly mixing sets. It is shown that if a dynamical system has positive topological entropy, then the collection of $\Delta$-weakly mixing sets is…

Dynamical Systems · Mathematics 2016-11-08 Wen Huang , Jian Li , Xiangdong Ye , Xiaoyao Zhou

We study the nonequilibrium statistical mechanics of a finite classical system subjected to nongradient forces $\xi$ and maintained at fixed kinetic energy (Hoover-Evans isokinetic thermostat). We assume that the microscopic dynamics is…

Statistical Mechanics · Physics 2007-05-23 David Ruelle

We develop the argument that the Gibbs-von Neumann entropy is the appropriate statistical mechanical generalisation of the thermodynamic entropy, for macroscopic and microscopic systems, whether in thermal equilibrium or not, as a…

Quantum Physics · Physics 2008-01-23 O. J. E. Maroney

The information-theoretic approach to Bell's theorem is developed with use of the conditional $q$-entropies. The $q$-entropic measures fulfill many similar properties to the standard Shannon entropy. In general, both the locality and…

Quantum Physics · Physics 2014-11-11 Alexey E. Rastegin

Entropy is useful in statistical problems as a measure of irreversibility, randomness, mixing, dispersion, and number of microstates. However, there remains ambiguity over the precise mathematical formulation of entropy, generalized beyond…

Statistical Mechanics · Physics 2023-08-21 Vladimir Zhdankin

We addressed the problem of generalizing the extensive postulates of the standard thermodynamics in order to extend it to the study of nonextensive systems. We did it in analogy with the traditional analysis, starting from the…

Statistical Mechanics · Physics 2007-05-23 L. Velazquez , F. Guzman

We introduce generalized $(\alpha,\beta)$-transformations, which include all $(\alpha,\beta)$ and generalized $\beta$-transformations, and prove that all transitive generalized $(\alpha,\beta)$-transformations satisfy the level-2 large…

Dynamical Systems · Mathematics 2022-06-22 Mao Shinoda , Kenichiro Yamamoto

Minimum divergence estimators provide a natural choice of estimators in a statistical inference problem. Different properties of various families of these divergence measures such as Hellinger distance, power divergence, density power…

Statistics Theory · Mathematics 2025-07-08 Subhrajyoty Roy , Supratik Basu , Abhik Ghosh , Ayanendranath Basu

Recently, the author and collaborators proposed a method to construct a new conserved charge different from the Noether one for general relativistic field theory on curved space-time with energy-momentum tensor covariantly conserved, and…

High Energy Physics - Theory · Physics 2023-12-21 Shuichi Yokoyama

The present paper studies a large class of temperature dependent probability distributions and shows that entropy and energy can be defined in such a way that these probability distributions are the equilibrium states of a generalized…

Statistical Mechanics · Physics 2015-06-24 Jan Naudts

For general metric theories of gravity, we compare the approach that describes-derives the field equations of gravity as a thermodynamic identity with the one which looks at them from entropy bounds. The comparison is made through the…

General Relativity and Quantum Cosmology · Physics 2015-10-28 Alessandro Pesci

The notion of metric plays a key role in machine learning problems such as classification, clustering or ranking. However, it is worth noting that there is a severe lack of theoretical guarantees that can be expected on the generalization…

Machine Learning · Computer Science 2015-04-01 Maria-Irina Nicolae , Marc Sebban , Amaury Habrard , Éric Gaussier , Massih-Reza Amini

Many spatial models exhibit locality structures that effectively reduce their intrinsic dimensionality, enabling efficient approximation and sampling of high-dimensional distributions. However, existing approximation techniques primarily…

Machine Learning · Statistics 2026-02-02 Tiangang Cui , Shuigen Liu , Xin T. Tong