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We prove that the maximum speed and the entropy of a one-tape Turing machine are computable, in the sense that we can approximate them to any given precision $\epsilon$. This is contrary to popular belief, as all dynamical properties are…

Formal Languages and Automata Theory · Computer Science 2013-02-06 Emmanuel Jeandel

The remaining min-entropy of a secret generated by fuzzy extraction from a Physical Unclonable Function is typically estimated under the assumption of independent and identically distributed PUF responses, but this assumption does not hold…

Signal Processing · Electrical Eng. & Systems 2020-01-23 Florian Wilde , Christoph Frisch , Michael Pehl

The channel output entropy of a transmitted word is the entropy of the possible channel outputs and similarly, the input entropy of a received word is the entropy of all possible transmitted words. The goal of this work is to study these…

Information Theory · Computer Science 2022-06-16 Shubhransh Singhvi , Omer Sabary , Daniella Bar-Lev , Eitan Yaakobi

Entropy production is often interpreted as a proxy for microscopic disorder or environmental roughness in stochastic systems. We test this interpretation using controlled simulations of overdamped stochastic dynamics on curved surfaces in…

Statistical Mechanics · Physics 2026-02-23 Patrick Romanescu

For an ergodic probability-measure-preserving action $G \curvearrowright (X, \mu)$ of a countable group $G$, we define the Rokhlin entropy $h_G^{\mathrm{Rok}}(X, \mu)$ to be the infimum of the Shannon entropies of countable generating…

Dynamical Systems · Mathematics 2019-04-09 Brandon Seward

Entropy creation rate is introduced for a system interacting with thermostats ({\it i.e.}, in the usual language, for a system subject to internal conservative forces interacting with ``external'' thermostats via conservative forces) and a…

Statistical Mechanics · Physics 2007-05-23 G. Gallavotti

We propose a new method for the calculation of the statistical properties, as e.g. the entropy, of unknown generators of symbolic sequences. The probability distribution p(k) of the elements k of a population can be approximated by the…

Statistical Mechanics · Physics 2015-06-24 Thorsten Poeschel , Werner Ebeling , Helge Rose

In many real-world situations, there are constraints on the ways in which a physical system can be manipulated. We investigate the entropy production (EP) and extractable work involved in bringing a system from some initial distribution $p$…

Statistical Mechanics · Physics 2022-11-22 Artemy Kolchinsky , David H. Wolpert

This paper proposes a novel entropy encoding technique for lossless data compression. Representing a message string by its lexicographic index in the permutations of its symbols results in a compressed version matching Shannon entropy of…

Information Theory · Computer Science 2017-03-24 Abu Bakar Siddique

Tactical selection of experiments to estimate an underlying model is an innate task across various fields. Since each experiment has costs associated with it, selecting statistically significant experiments becomes necessary. Classic linear…

Optimization and Control · Mathematics 2021-03-30 Raj K. Velicheti , Amber Srivastava , Srinivasa M. Salapaka

We consider entanglement in the ground state of the XY spin model on infinite chain. We use von Neumann entropy of a sub-system as a measure of entanglement. The entropy of a large block of neighboring spins approaches a constant as the…

Quantum Physics · Physics 2007-05-23 A. R. Its , B. -Q. Jin , V. E. Korepin

The entropic region is formed by the collection of the Shannon entropies of all subvectors of finitely many jointly distributed discrete random variables. For four or more variables, the structure of the entropic region is mostly unknown.…

Information Theory · Computer Science 2026-03-04 E. P. Csirmaz , L. Csirmaz

Systems driven away from thermal equilibrium constantly deliver entropy to their environment. Determining this entropy production requires detailed information about the system's internal states and dynamics. However, in most practical…

Statistical Mechanics · Physics 2017-10-03 Gili Bisker , Matteo Polettini , Todd R. Gingrich , Jordan M. Horowitz

Let $G$ be a discrete, countably infinite group and $H$ a subgroup of $G$. If $H$ acts continuously on a compact metric space $X$, then we can induce a continuous action of $G$ on $\prod_{H\backslash G}X$ where $H\backslash G$ is the…

Dynamical Systems · Mathematics 2025-10-16 Dakota M. Leonard

This work contains two single-letter upper bounds on the entropy rate of a discrete-valued stationary stochastic process, which only depend on second-order statistics, and are primarily suitable for models which consist of relatively large…

Information Theory · Computer Science 2022-03-11 Ran Tamir

There are three ways to conceptualize entropy: entropy as an extensive thermodynamic quantity of physical systems (Clausius, Boltzmann, Gibbs), entropy as a measure for information production of ergodic sources (Shannon), and entropy as a…

Statistical Mechanics · Physics 2018-11-05 Stefan Thurner , Bernat Corominas-Murtra , Rudolf Hanel

We continue the study of constructing explicit extractors for independent general weak random sources. The ultimate goal is to give a construction that matches what is given by the probabilistic method --- an extractor for two independent…

Computational Complexity · Computer Science 2015-03-10 Xin Li

Given a general scalar balance law, i.e., in several space dimensions and with flux and source both space and time dependent, we focus on the functional properties of the entropy production. We apply this operator to entropy solutions, to…

Analysis of PDEs · Mathematics 2025-04-03 Rinaldo Colombo , Vincent Perrollaz

Motivated by the approach of random linear codes, a new distance in the vector space over a finite field is defined as the logarithm of the "surface area" of a Hamming ball with radius being the corresponding Hamming distance. It is named…

Information Theory · Computer Science 2013-04-30 Shengtian Yang

Many generative models have to combat $\textit{missing modes}$. The conventional wisdom to this end is by reducing through training a statistical distance (such as $f$-divergence) between the generated distribution and provided data…

Machine Learning · Statistics 2019-10-28 Peilin Zhong , Yuchen Mo , Chang Xiao , Pengyu Chen , Changxi Zheng