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Information-theoretic quantities like entropy and mutual information have found numerous uses in machine learning. It is well known that there is a strong connection between these entropic quantities and submodularity since entropy over a…

Machine Learning · Computer Science 2021-03-04 Rishabh Iyer , Ninad Khargonkar , Jeff Bilmes , Himanshu Asnani

Our aim is to make a step towards clarification of foundations for the notion of entanglement (both physical and mathematical) by representing it in the conditional probability framework. In Schr\"odinger's words, this is entanglement of…

Quantum Physics · Physics 2023-11-28 Irina Basieva , Andrei Khrennikov

Similarly to the derivation of the Gibbs-Boltzmann distribution for structureless indistinguishable particles, we consider multi-particle systems some of which are contained (or delimited) inside others (Problem 1), as well as systems of…

Statistical Mechanics · Physics 2021-07-19 Michael Romanovsky

Covariate balance is a conventional key diagnostic for methods used estimating causal effects from observational studies. Recently, there is an emerging interest in directly incorporating covariate balance in the estimation. We study a…

Methodology · Statistics 2017-02-14 Qingyuan Zhao , Daniel Percival

Probability distributions having power-law tails are observed in a broad range of social, economic, and biological systems. We describe here a potentially useful common framework. We derive distribution functions $\{p_k\}$ for situations in…

Physics and Society · Physics 2015-01-07 Jack Peterson , Purushottam D. Dixit , Ken A. Dill

Experimental and theoretical results about entropy limits for macroscopic and single-particle systems are reviewed. It is clarified when it is possible to speak about a quantum of entropy, given by the Boltzmann constant k, and about a…

Quantum Physics · Physics 2023-11-06 Uwe Hohm , Christoph Schiller

The paper shows that, for large number of particles and for distinguishable and non-interacting identical particles, convergence to equiprobability of the $W$ microstates of the famous Boltzmann-Planck entropy formula $S=k \log(W)$ is…

Classical Physics · Physics 2022-04-13 Arnaldo Spalvieri

We demonstrate and characterize a first-principles approach to modeling the mass action dynamics of metabolism. Starting from a basic definition of entropy expressed as a multinomial probability density using Boltzmann probabilities with…

Chemical Physics · Physics 2024-07-10 William R. Cannon , Samuel Britton , Mikahl Banwarth-Kuhn , Mark Alber

When an expert operates a perilous dynamic system, ideal constraint information is tacitly contained in their demonstrated trajectories and controls. The likelihood of these demonstrations can be computed, given the system dynamics and task…

Systems and Control · Electrical Eng. & Systems 2021-02-26 David L. McPherson , Kaylene C. Stocking , S. Shankar Sastry

We introduce hardness in relative entropy, a new notion of hardness for search problems which on the one hand is satisfied by all one-way functions and on the other hand implies both next-block pseudoentropy and inaccessible entropy, two…

Cryptography and Security · Computer Science 2024-11-15 Rohit Agrawal , Yi-Hsiu Chen , Thibaut Horel , Salil Vadhan

We find a sharp combinatorial bound for the metric entropy of sets in R^n and general classes of functions. This solves two basic combinatorial conjectures on the empirical processes. 1. A class of functions satisfies the uniform Central…

Functional Analysis · Mathematics 2016-12-23 Mark Rudelson , Roman Vershynin

An attempt is made to construct composable composite entropy with different $q$ indices of subsystems and address the H-theorem problem of the composite system. Though the H-theorem does not hold in general situations, it is shown that some…

Statistical Mechanics · Physics 2009-10-31 K. Sasaki , M. Hotta

A well-known result across information theory, machine learning, and statistical physics shows that the maximum entropy distribution under a mean constraint has an exponential form called the Gibbs-Boltzmann distribution. This is used for…

Machine Learning · Computer Science 2020-06-26 Amir R. Asadi , Emmanuel Abbe

General probabilistic theories are designed to provide operationally the most general probabilistic models including both classical and quantum theories. In this letter, we introduce a systematic method to construct a series of entropies,…

Quantum Physics · Physics 2016-10-26 Gen Kimura , Junji Ishiguro , Makoto Fukui

We propose a new interpretation of measures of information and disorder by connecting these concepts to group theory in a new way. Entropy and group theory are connected here by their common relation to sets of permutations. A combinatorial…

Information Theory · Computer Science 2019-11-25 David J. Galas

Measure-theoretic slow entropy is a more refined invariant than the classical measure-theoretic entropy to characterize the complexity of dynamical systems with subexponential growth rates of distinguishable orbit types. In this paper we…

Dynamical Systems · Mathematics 2021-09-20 Shilpak Banerjee , Philipp Kunde , Daren Wei

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

We demonstrate that the most probable state of a conserved system with a limited number of entities or molecules is the state where non-Gaussian and non-chi-square distributions govern. We have conducted a thought experiment using a…

Mathematical Physics · Physics 2023-04-20 Jae Wan Shim

We consider the meta-equilibrium state of a composite system made up of independent subsystems satisfying the additive form of external constraints, as recently discussed by Abe [Phys. Rev. E {\bf 63}, 061105 (2001)]. We derive the additive…

Statistical Mechanics · Physics 2009-11-10 Ramandeep S. Johal

This paper investigates the combinatorics that gives rise to the Boltzmann probability distribution. Despite being one of the most important distributions in physics and other fields of science, the mathematics of the underlying model of…

Probability · Mathematics 2025-07-09 Bart Jacobs