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Studying the typical entanglement entropy of a bipartite system when averaging over different ensembles of pure quantum states has been instrumental in different areas of physics, ranging from many-body quantum chaos to black hole…

Quantum Physics · Physics 2025-07-08 Lucas Hackl , Mario Kieburg , Joel Maldonado

We study a dynamical system with time dependent Hamiltonian by numerical experiments so as to find a relation between thermodynamics and chaotic nature of the system. Excess information loss, defined newly based on Lyapunov analysis, is…

chao-dyn · Physics 2009-10-31 S. Sasa , T. S. Komatsu

In a recent Letter [1] a framework for estimating entropy was introduced and applied to one-dimensional and two-dimensional systems. In this Comment we show that the method is not well suited for estimating entropy in bidimensional systems…

Statistical Mechanics · Physics 2022-07-15 E. Brigatti , F. N. M. de Sousa Filho

Quantum information quantities, such as mutual information and entropies, are essential for characterizing quantum systems and protocols in quantum information science. In this contribution, we identify types of information measures based…

Quantum Physics · Physics 2025-10-21 Christopher Popp , Tobias C. Sutter , Beatrix C. Hiesmayr

Deep learning systems have been reported to achieve state-of-the-art performances in many applications, and a key is the existence of well trained classifiers on benchmark datasets. As a main-stream loss function, the cross entropy can…

Machine Learning · Computer Science 2022-09-22 Jirong Yi , Qiaosheng Zhang , Zhen Chen , Qiao Liu , Wei Shao

Collaborative information serves as the cornerstone of recommender systems which typically focus on capturing it from user-item interactions to deliver personalized services. However, current understanding of this crucial resource remains…

Information Retrieval · Computer Science 2025-11-27 Xiaokun Zhang , Zhaochun Ren , Bowei He , Ziqiang Cui , Chen Ma

Entropy is a fundamental concept in quantum information theory that allows to quantify entanglement and investigate its properties, for example its monogamy over multipartite systems. Here, we derive variational formulas for relative…

Quantum Physics · Physics 2024-05-21 Mario Berta , Marco Tomamichel

Copula Entropy (CE) is a recently introduced concept for measuring correlation/dependence in information theory. In this paper, the theory of CE is introduced and the thermodynamic interpretation of CE is presented with N-particle…

Information Theory · Computer Science 2021-12-03 Jian Ma

Maximum entropy estimation is of broad interest for inferring properties of systems across many different disciplines. In this work, we significantly extend a technique we previously introduced for estimating the maximum entropy of a set of…

Data Analysis, Statistics and Probability · Physics 2016-01-05 Elliot A. Martin , Jaroslav Hlinka , Alexander Meinke , Filip Děchtěrenko , Jörn Davidsen

We numerically calculate entanglement entropy and mutual information for a massive free scalar field on commutative (ordinary) and noncommutative (fuzzy) spheres. We regularize the theory on the commutative geometry by discretizing the…

High Energy Physics - Theory · Physics 2015-06-23 Philippe Sabella-Garnier

Motivated by applications to group synchronization and quadratic assignment on random data, we study a general problem of Bayesian inference of an unknown ``signal'' belonging to a high-dimensional compact group, given noisy pairwise…

Statistics Theory · Mathematics 2025-12-23 Kaylee Y. Yang , Timothy L. H. Wee , Zhou Fan

Mutual information is widely applied to learn latent representations of observations, whilst its implication in classification neural networks remain to be better explained. We show that optimising the parameters of classification neural…

Machine Learning · Computer Science 2020-09-18 Zhenyue Qin , Dongwoo Kim , Tom Gedeon

For sensory networks, we determine the rate with which they acquire information about the changing external conditions. Comparing this rate with the thermodynamic entropy production that quantifies the cost of maintaining the network, we…

Statistical Mechanics · Physics 2013-04-08 A. C. Barato , D Hartich , U. Seifert

We discuss the information entropy for a general open pointer-based simultaneous measurement and show how it is bound from below. This entropic uncertainty bound is a direct consequence of the structure of the entropy and can be obtained…

Quantum Physics · Physics 2015-03-24 Raoul Heese , Matthias Freyberger

In this Thesis, several results in quantum information theory are collected, most of which use entropy as the main mathematical tool. *While a direct generalization of the Shannon entropy to density matrices, the von Neumann entropy behaves…

Quantum Physics · Physics 2018-10-25 Christian Majenz

Bayesian neural networks have successfully designed and optimized a robust neural network model in many application problems, including uncertainty quantification. However, with its recent success, information-theoretic understanding about…

Information Theory · Computer Science 2022-06-22 Jae Oh Woo

The minimum rate needed to accurately approximate a product distribution based on an unnormalized informational divergence is shown to be a mutual information. This result subsumes results of Wyner on common information and Han-Verd\'{u} on…

Information Theory · Computer Science 2013-05-14 Jie Hou , Gerhard Kramer

Let $X$ be a non-negative random variable and let the conditional distribution of a random variable $Y$, given $X$, be ${Poisson}(\gamma \cdot X)$, for a parameter $\gamma \geq 0$. We identify a natural loss function such that: 1) The…

Information Theory · Computer Science 2015-03-17 Rami Atar , Tsachy Weissman

General quantum measurements are represented by instruments. In this paper the mathematical formalization is given of the idea that an instrument is a channel which accepts a quantum state as input and produces a probability and an a…

Quantum Physics · Physics 2007-05-23 Alberto Barchielli , Giancarlo Lupieri

We propose a new information-theoretic bound on generalization error based on a combination of the error decomposition technique of Bu et al. and the conditional mutual information (CMI) construction of Steinke and Zakynthinou. In a…

Information Theory · Computer Science 2021-01-01 Ruida Zhou , Chao Tian , Tie Liu
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