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Related papers: Generalized pathway entropy and its applications i…

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A generalised notion of exponential families is introduced. It is based on the variational principle, borrowed from statistical physics. It is shown that inequivalent generalised entropy functions lead to distinct generalised exponential…

Mathematical Physics · Physics 2015-05-13 Jan Naudts

Following the work on Shannon entropy together with the principle of maximum entropy, Luo & Singh (J. Hydrol. Eng., 2011, 16(4): 303-315) and Singh & Luo (J. Hydrol. Eng., 2011, 16(9): 725-735) explored the concept of non-extensive Tsallis…

Fluid Dynamics · Physics 2020-08-26 Manotosh Kumbhakar , Rajendra K. Ray , Koeli Ghoshal , Vijay P. Singh

Maximum entropy method for analytic continuation is extended by introducing quantum relative entropy. This new method is formulated in terms of matrix-valued functions and therefore invariant under arbitrary unitary transformation of input…

Strongly Correlated Electrons · Physics 2018-11-05 Jae-Hoon Sim , Myung Joon Han

A general principle called "conservation of the ellipsoid of concentration" is introduced and a generalized entropic form of order 'alpha' is optimized under this principle. It is shown that this can produce a density which can act as a…

Statistical Mechanics · Physics 2014-09-09 H. J. Haubold , A. M. Mathai , S. Thomas

The first aims of this work are to endorse the advent of finitely additive set functions as equilibrium states and the possibility to replace the metric entropy by an upper semi-continuous map associated to a general variational principle.…

Dynamical Systems · Mathematics 2022-04-07 Andrzej Bis , Maria Carvalho , Miguel Mendes , Paulo Varandas

Pathway idea is a switching mechanism by which one can go from one functional form to another, and to yet another. It is shown that through a parameter $\alpha$, called the pathway parameter, one can connect generalized type-1 beta family…

Mathematical Physics · Physics 2013-07-31 Nicy Sebastian , Dhannya P. Joseph , Seema S. Nair

We generalize Einstein's probabilistic method for the Brownian motion to study compressible fluids in porous media. The multi-dimensional case is considered with general probability distribution functions. By relating the expected…

Analysis of PDEs · Mathematics 2025-03-06 Luan Hoang , Akif Ibragimov

The growing interest of different entropy functions proposed so far (like the Bekenstein-Hawking, Tsallis, R\'{e}nyi, Barrow, Sharma-Mittal, Kaniadakis and Loop Quantum Gravity entropies) towards black hole thermodynamics as well as towards…

General Relativity and Quantum Cosmology · Physics 2023-01-04 Sergei D. Odintsov , Tanmoy Paul

Mathematical models of motility are often based on random-walk descriptions of discrete individuals that can move according to certain rules. It is usually the case that large masses concentrated in small regions of space have a great…

Physics and Society · Physics 2022-11-23 Carles Falcó

A consistent generalization of statistical mechanics is obtained by applying the maximum entropy principle to a trace-form entropy and by requiring that physically motivated mathematical properties are preserved. The emerging…

Statistical Mechanics · Physics 2009-11-10 G. Kaniadakis , M. Lissia , A. M. Scarfone

In this thesis we start by providing some detail regarding how we arrived at our present understanding of probabilities and how we manipulate them - the product and addition rules by Cox. We also discuss the modern view of entropy and how…

Data Analysis, Statistics and Probability · Physics 2009-01-21 Adom Giffin

The coincidence method of measuring the entropy of a system, proposed some time ago by Ma, is generalized to include systems out of equilibrium. It is suggested that the method can be adapted to analyze multiparticle states produced in…

High Energy Physics - Phenomenology · Physics 2009-10-31 A. Bialas , W. Czyz

This paper presents an {\it ab initio} derivation of the expression given by irreversible thermodynamics for the rate of entropy production for different classes of diffusive processes. The first class are Lorentz gases, where…

Chaotic Dynamics · Physics 2009-11-07 J. R. Dorfman , P. Gaspard , T. Gilbert

Starting from an algebraic approach of quantum physics it has been shown via the Tomita-Takesaki theorem and the KMS condition that the canonical density matrix contains the dynamics of the system provided we use a rescaling of time. In…

Statistical Mechanics · Physics 2009-02-06 J. P. Badiali

We show that in the continuum limit, the average spectrum method (ASM) is equivalent to maximizing R\'enyi entropies of order $\eta$, of which Shannon entropy is the special case $\eta=1$. The order of R\'enyi entropy is determined by the…

Strongly Correlated Electrons · Physics 2023-07-24 Khaldoon Ghanem , Erik Koch

The design space of discrete-space diffusion or flow generative models are significantly less well-understood than their continuous-space counterparts, with many works focusing only on a simple masked construction. In this work, we aim to…

The concept of entropy connects the number of possible configurations with the number of variables in large stochastic systems. Independent or weakly interacting variables render the number of configurations scale exponentially with the…

Statistical Mechanics · Physics 2020-06-25 Sámuel G. Balogh , Gergely Palla , Péter Pollner , Dániel Czégel

Reaction-diffusion systems driven far from thermodynamic equilibrium through the injection of energy can support multiple distinct spatial patterns that persist as long-lived dynamical phases. The stability of these metastable phases is not…

Statistical Mechanics · Physics 2026-03-13 Eric R. Heller , David T. Limmer

Motivated by entropic optimal transport, time reversal of diffusion processes is revisited. An integration by parts formula is derived for the carr\'e du champ of a Markov process in an abstract space. It leads to a time reversal formula…

Probability · Mathematics 2022-09-05 Patrick Cattiaux , Giovanni Conforti , Ivan Gentil , Christian Léonard

Maximum entropy modeling is a flexible and popular framework for formulating statistical models given partial knowledge. In this paper, rather than the traditional method of optimizing over the continuous density directly, we learn a smooth…

Methodology · Statistics 2017-05-01 Gabriel Loaiza-Ganem , Yuanjun Gao , John P. Cunningham
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