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The problem of assigning probability distributions which objectively reflect the prior information available about experiments is one of the major stumbling blocks in the use of Bayesian methods of data analysis. In this paper the method of…

Data Analysis, Statistics and Probability · Physics 2009-11-10 Ariel Caticha , Roland Preuss

It is shown that, for systems in which the entropy is an extensive function of the energy and volume, the Bekenstein and the holographic entropy bounds predict new results. More explicitly, the Bekenstein entropy bound leads to the entropy…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Gilad Gour

Information plays an important role in our understanding of the physical world. We hence propose an entropic measure of information for any physical theory that admits systems, states and measurements. In the quantum and classical world,…

Quantum Physics · Physics 2010-05-04 Anthony J. Short , Stephanie Wehner

Recently Abe (arXiv:cond-mat/1005.5110v1) claimed that the q-entropy of nonextensive statistical mechanics cannot be generalized for the continuous variables and therefore can be used only in the discrete case. In this letter, we show that…

Statistical Mechanics · Physics 2010-06-22 G. Baris Bagci , Thomas Oikonomou , Ugur Tirnakli

An axiomatic foundation regarding the entropy for complex systems is established. Missing from decades of research was the requirement that entropy must measure the uncertainty at the informational scale of the maximizing distribution,…

Statistical Mechanics · Physics 2026-05-29 Kenric P. Nelson

The paper analyzes the entropy of a system composed by non-interacting and indistinguishable particles whose quantum state numbers are modelled as independent and identically distributed classical random variables. The crucial observation…

Statistical Mechanics · Physics 2023-05-18 Arnaldo Spalvieri

This study shows that the generalized Boltzmann distribution is the only distribution mathematically consistent with thermodynamics when the system is described by an ensemble of a certain mathematical form. This mathematical form is very…

Statistical Mechanics · Physics 2022-02-10 Xiang Gao

The framework of non-extensive statistical mechanics, proposed by Tsallis, has been used to describe a variety of systems. The non-extensive statistical mechanics is usually introduced in a formal way, thus simple models exhibiting some…

Statistical Mechanics · Physics 2014-08-06 Julius Ruseckas

In the works on Statistical Mechanics and Statistical Physics, when deriving the distribution of particles of ideal gases, one uses the method of Lagrange multipliers in a formal way. In this paper we treat rigorously this problem for…

Mathematical Physics · Physics 2016-01-12 Constantin Zalinescu

For more than 100 years, one of the central concepts in statistical mechanics has been the microcanonical ensemble, which provides a way of calculating the thermodynamic entropy for a specified energy. A controversy has recently emerged…

Statistical Mechanics · Physics 2016-07-04 Michael Matty , Lachlan Lancaster , William Griffin , Robert H. Swendsen

Despite well over a century of effort, the proper expression for the classical entropy in statistical mechanics remains a subject of debate. The Boltzmann entropy (calculated from a surface in phase space) has been criticized as not being…

Statistical Mechanics · Physics 2017-09-12 Robert H. Swendsen

Non-extensive systems do not allow to go to the thermodynamic limit. Therefore we have to reformulate statistical mechanics without invoking the thermodynamical limit. I.e. we have to go back to Pre-Gibbsian times. We show that Boltzmann's…

Statistical Mechanics · Physics 2007-05-23 D. H. E. Gross

Albert Einstein's journey to formulate the theory of general relativity involved significant shifts in his approach to gravitational field equations. Starting in 1912, he collaborated with Marcel Grossmann and initially explored broadly…

History and Philosophy of Physics · Physics 2023-11-09 Galina Weinstein

We consider entropy in Generalized Non-Signalling Theory (also known as box world) where the most common definition of entropy is the measurement entropy. In this setting, we completely characterize the set of allowed entropies for a…

Quantum Physics · Physics 2012-11-14 Josh Cadney , Noah Linden

The Boltzmann distribution (the most probable distribution) is one of the most important concepts used in physics, chemistry and biology. Suppose we put the system initially in one of the less probable state then the system will find the…

Statistical Mechanics · Physics 2015-09-23 Aniruddha Chakraborty

It is well known that, for chaotic systems, the production of relevant entropy (Boltzmann-Gibbs) is always linear and the system has strong (exponential) sensitivity to initial conditions. In recent years, various numerical results indicate…

Statistical Mechanics · Physics 2009-11-11 Ahmet Celikoglu , Ugur Tirnakli

I show that non-decreasing entropy provides a necessary and sufficient condition to convert the state of a physical system into a different state by a reversible transformation that acts on the system of interest and a further "catalyst"…

Quantum Physics · Physics 2022-01-06 Henrik Wilming

Gibbs-Boltzmann entropy leads to systems that have a strong dependence on initial conditions. In reality, most materials behave quite independently of initial conditions. Nonextensive entropy or Tsallis entropy leads to nonextensive…

Statistical Mechanics · Physics 2022-07-01 Saman Amiri , Mahdi Mirzaee , Mohammad Mazhari

In the mid-19th century, both the laws of mechanics and thermodynamics were known, and both appeared fundamental. This was changed by Boltzmann and Gibbs, who showed that thermodynamics can be *derived*, by applying mechanics to very large…

Quantum Physics · Physics 2021-07-05 Vyacheslav Lysov , Yasha Neiman

A restricted Boltzmann machine is a generative probabilistic graphic network. A probability of finding the network in a certain configuration is given by the Boltzmann distribution. Given training data, its learning is done by optimizing…

Disordered Systems and Neural Networks · Physics 2020-05-28 Sangchul Oh , Abdelkader Baggag , Hyunchul Nha
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