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This manuscript contains preprint of a chapter under consideration for inclusion in the forthcoming third edition of {\em Cover and Thomas's Elements of Information Theory}, posted with permission from Wiley. The table of contents EIT-3 ToC…

Information Theory · Computer Science 2026-05-06 Abbas El Gamal

We develop an algebraic and information-theoretic framework to characterize symmetry breaking of generalized, non-invertible symmetries in two spatial dimensions. The reduction of symmetry is modeled within subfactor theory, where…

Quantum Physics · Physics 2025-10-13 Javier Molina-Vilaplana , Germán Sierra , H. C. Zhang

In this paper have written the results of the information analysis of structures. The obtained information estimation (IE) are based on an entropy measure of C. Shannon. Obtained IE is univalent both for the non-isomorphic and for the…

Information Theory · Computer Science 2007-07-16 Alexander Shaydurov

Motivated by recent work of Florian Pop, we study the connections between three notions of equivalence of function fields: isomorphism, elementary equivalence, and the condition that each of a pair of fields can be embedded in the other,…

Logic · Mathematics 2007-05-23 Pete L. Clark

We develop a geometric foundation of microcanonical thermodynamics in which entropy and its derivatives are determined from the geometry of phase space, rather than being introduced through an a priori ensemble postulate. Once the minimal…

Statistical Mechanics · Physics 2025-12-30 Loris Di Cairano

The statistical mechanics of Gibbs is a juxtaposition of subjective, probabilistic ideas on the one hand and objective, mechanical ideas on the other. In this paper, we follow the path set out by Jaynes, including elements added…

Statistical Mechanics · Physics 2015-11-24 David M. Rogers , Thomas L. Beck , Susan B. Rempe

Smooth entropies are a tool for quantifying resource trade-offs in (quantum) information theory and cryptography. In typical bi- and multi-partite problems, however, some of the sub-systems are often left unchanged and this is not reflected…

Quantum Physics · Physics 2020-07-20 Anurag Anshu , Mario Berta , Rahul Jain , Marco Tomamichel

In financial markets valuable information is rarely circulated homogeneously, because of time required for information to spread. However, advances in communication technology means that the 'lifetime' of important information is typically…

Pricing of Securities · Quantitative Finance 2011-08-05 Dorje C. Brody , Yan Tai Law

Conditional mutual information is important in the selection and interpretation of graphical models. Its empirical version is well known as a generalised likelihood ratio test and that it may be represented as a difference in entropy. We…

Methodology · Statistics 2015-01-20 Joe Whittaker , Florian Martin , Yang Xiang

Bifurcation phenomena are common in multi-dimensional multi-parameter dynamical systems. Normal form theory suggests that the bifurcations themselves are driven by relatively few parameters; however, these are often nonlinear combinations…

Dynamical Systems · Mathematics 2023-11-29 Christian N. K. Anderson , Mark K. Transtrum

This paper lays the foundations for a unified framework for numerically and computationally applying methods drawn from a range of currently distinct geometrical approaches to statistical modelling. In so doing, it extends information…

Statistics Theory · Mathematics 2012-09-11 Karim Anaya-Izquierdo , Frank Critchley , Paul Marriott , Paul W. Vos

Despite the wide usage of information as a concept in science, we have yet to develop a clear & concise scientific definition. This paper is aimed at laying the foundations for a new theory concerning the mechanics of information alongside…

General Physics · Physics 2017-07-13 Kiyam Lin , SongLing Lin

Economic interactions often occur in networks where heterogeneous agents (such as workers or firms) sort and produce. However, most existing estimation approaches either require the network to be dense, which is at odds with many empirical…

Econometrics · Economics 2023-07-24 Stéphane Bonhomme , Kevin Dano

In neuroscience, methods from information geometry (IG) have been successfully applied in the modelling of binary vectors from spike train data, using the orthogonal decomposition of the Kullback-Leibler divergence and mutual information to…

Neurons and Cognition · Quantitative Biology 2025-10-17 Eric Albers , Paul Marriott , Masami Tatsuno

This arXiv report provides a short introduction to the information-theoretic measure proposed by Chen and Golan in 2016 for analyzing machine- and human-centric processes in data intelligence workflows. This introduction was compiled based…

Information Theory · Computer Science 2021-03-30 Min Chen

We introduce an information-theoretic framework for smooth structures on topological manifolds, replacing coordinate charts with small-scale entropy data of local probability probes. A concise set of axioms identifies admissible coordinate…

Differential Geometry · Mathematics 2026-01-21 Amandip Sangha

Although some information-theoretic measures of uncertainty or granularity have been proposed in rough set theory, these measures are only dependent on the underlying partition and the cardinality of the universe, independent of the lower…

Artificial Intelligence · Computer Science 2011-02-02 Ping Zhu , Qiaoyan Wen

This paper analytically demonstrates that, in a Two-Agent New Keynesian model with Rotemberg-type price and wage rigidities, monetary transmission can be amplified when two mechanisms are sufficiently strong: the heterogeneity-induced…

Theoretical Economics · Economics 2026-05-05 Kenji Miyazaki

Standard methods for estimating production functions in the Olley and Pakes (1996) tradition require assumptions on input choices. We introduce a new method that exploits (increasingly available) data on a firm's expectations of its future…

Econometrics · Economics 2024-07-12 Agnes Norris Keiller , Aureo de Paula , John Van Reenen

We introduce Feature-Product networks (FP-nets) as a novel deep-network architecture based on a new building block inspired by principles of biological vision. For each input feature map, a so-called FP-block learns two different filters,…

Computer Vision and Pattern Recognition · Computer Science 2020-08-19 Philipp Grüning , Thomas Martinetz , Erhardt Barth