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Motivation: Entropy measurements on hierarchical structures have been used in methods for information retrieval and natural language modeling. Here we explore its application to semantic similarity. By finding shared ontology terms,…

Computation and Language · Computer Science 2017-06-20 Andrew Warren , Joao Setubal

We consider the entanglement entropy for the 2D Ising model at the conformal fixed point in the presence of interfaces. More precisely, we investigate the situation where the two subsystems are separated by a defect line that preserves…

High Energy Physics - Theory · Physics 2015-05-25 Enrico M. Brehm , Ilka Brunner

In the context of averaging an inhomogeneous cosmological model, we propose a natural measure identical to the Kullback-Leibler relative information entropy, which expresses the distinguishability of the local inhomogeneous density field…

General Relativity and Quantum Cosmology · Physics 2011-07-28 Masaaki Morita , Thomas Buchert , Akio Hosoya , Nan Li

Changing climate signals and the continuous world population growth requires proper hydrologic risk analysis to build and operate water resource infrastructures in a sustainable way. Although modernized computational facilities are becoming…

Pattern Formation and Solitons · Physics 2022-08-30 Victor Peñaranda , David Serrano , Mahesh Maskey

Complex structures often emerge from initially homogeneous or weakly correlated states. We address the apparent tension between this ordering and entropy growth through a unified framework combining semi-microscopic phase-space dynamics,…

Cosmology and Nongalactic Astrophysics · Physics 2026-05-27 Francisco-Shu Kitaura

The deep connection between entropy and information is discussed in terms of both classical and quantum physics. The mechanism of information transfer between systems via entanglement is explored in the context of decoherence theory. The…

Quantum Physics · Physics 2021-01-05 Martin Paul Vaughan

Reconstructing the structural connectivity between interacting units from observed activity is a challenge across many different disciplines. The fundamental first step is to establish whether or to what extent the interactions between the…

Neurons and Cognition · Quantitative Biology 2016-11-02 Elliot A. Martin , Jaroslav Hlinka , Jörn Davidsen

Predictive inference requires balancing statistical accuracy against informational complexity, yet the choice of complexity measure is usually imposed rather than derived. We treat econometric objects as predictive rules, mappings from…

Statistics Theory · Mathematics 2026-02-16 Nicholas G. Polson , Daniel Zantedeschi

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

Transfer entropy provides a general tool for analyzing the magnitudes and directions---but not the \emph{kinds}---of information transfer in a system. We extend transfer entropy in two complementary ways. First, we distinguish…

Data Analysis, Statistics and Probability · Physics 2011-02-09 Paul L. Williams , Randall D. Beer

Fractal dimension is defined on the base of entropy, including macro state entropy and information entropy. The generalized correlation dimension of multifractals is based on Renyi entropy. However, the mathematical transform from entropy…

Physics and Society · Physics 2020-11-17 Yanguang Chen

Entanglement -- the coherent correlations between parties in a joint quantum system -- is well-understood and quantifiable in the two-dimensional, two-party case. Higher (>2)-dimensional entangled systems hold promise in extending the…

Quantum Physics · Physics 2022-10-20 Alexandria J. Moore , Andrew M. Weiner

We study the directional entropy of the dynamical system associated to a $\Z^2$ configuration in a finite alphabet. We show that under local assumptions on the complexity, either every direction has zero topological entropy or some…

Dynamical Systems · Mathematics 2014-09-18 Ryan Broderick , Van Cyr , Bryna Kra

Human dynamical social networks encode information and are highly adaptive. To characterize the information encoded in the fast dynamics of social interactions, here we introduce the entropy of dynamical social networks. By analysing a…

Physics and Society · Physics 2012-01-17 Kun Zhao , Márton Karsai , Ginestra Bianconi

We study the scaling behavior of the entanglement entropy of two dimensional conformal quantum critical systems, i.e. systems with scale invariant wave functions. They include two-dimensional generalized quantum dimer models on bipartite…

Statistical Mechanics · Physics 2009-03-28 Benjamin Hsu , Michael Mulligan , Eduardo Fradkin , Eun-Ah Kim

The information entropy of a nuclear density distribution is calculated for a number of nuclei. Various phenomenological models for the density distribution using different geometry are employed. Nuclear densities calculated within various…

Nuclear Theory · Physics 2015-06-26 G. A. Lalazissis , S. E. Massen , C. P. Panos , S. S. Dimitrova

Recent developments enable the quantification of causal control given a structural causal model (SCM). This has been accomplished by introducing quantities which encode changes in the entropy of one variable when intervening on another.…

Machine Learning · Computer Science 2024-02-20 Francisco N. F. Q. Simoes , Mehdi Dastani , Thijs van Ommen

We study the approach to equilibrium of systems of gas particles in terms of relative entropy. The systems are modeled by the Kac master equation in arbitrary dimensions. First, we study the Kac system coupled to a thermostat, and secondly…

Mathematical Physics · Physics 2023-01-24 Lukas Hauger

We present a new paradigm for capturing the complementarity of two observables. It is based on the entanglement created by the interaction between the system observed and the two measurement devices used to measure the observables…

Quantum Physics · Physics 2014-01-29 Patrick J. Coles , Marco Piani

Despite the remarkable success of large large-scale neural networks, we still lack unified notation for thinking about and describing their representational spaces. We lack methods to reliably describe how their representations are…

Machine Learning · Computer Science 2025-06-02 Henry Conklin
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