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The von Neumann entropy and the subentropy of a mixed quantum state are upper and lower bounds, respectively, on the accessible information of any ensemble consistent with the given mixed state. Here we define and investigate a set of…

Quantum Physics · Physics 2007-05-23 Sarah R. Nichols , William K. Wootters

Shannon's entropy is one of the building blocks of information theory and an essential aspect of Machine Learning methods (e.g., Random Forests). Yet, it is only finitely defined for distributions with fast decaying tails on a countable…

Statistics Theory · Mathematics 2022-05-25 Jialin Zhang , Jingyi Shi

We present a detailed derivation of some estimators of Shannon entropy for discrete distributions. They hold for finite samples of N points distributed into M "boxes", with N and M -> oo, but N/M < oo. In the high sampling regime (<< 1…

Data Analysis, Statistics and Probability · Physics 2011-11-09 P. Grassberger

This article serves as a brief introduction to the Shannon information theory. Concepts of information, Shannon entropy and channel capacity are mainly covered. All these concepts are developed in a totally combinatorial flavor. Some issues…

Information Theory · Computer Science 2021-04-26 Ricky X. F. Chen

Shannon's entropy and other entropy-based concepts are derived from the new, more general concept of relative divergence of one "grading' function on a linearly ordered set from another such function. The definition of relative divergence…

Probability · Mathematics 2019-03-14 Alexander Dukhovny

Shannon's information entropies in position- and momentum- space and their sum $S$ are calculated for various $s$-$p$ and $s$-$d$ shell nuclei using a correlated one-body density matrix depending on the harmonic oscillator size $b_0$ and…

Quantum Physics · Physics 2009-11-07 S. E. Massen

A method of representing probabilistic aspects of quantum systems is introduced by means of a density function on the space of pure quantum states. In particular, a maximum entropy argument allows us to obtain a natural density function…

Quantum Physics · Physics 2015-06-26 D. C. Brody , L. P. Hughston

The fidelity-based smooth min-relative entropy is a distinguishability measure that has appeared in a variety of contexts in prior work on quantum information, including resource theories like thermodynamics and coherence. Here we provide a…

Quantum Physics · Physics 2024-05-29 Theshani Nuradha , Mark M. Wilde

Shannon's fundamental bound for perfect secrecy says that the entropy of the secret message cannot be larger than the entropy of the secret key initially shared by the sender and the legitimate receiver. Massey gave an information theoretic…

Information Theory · Computer Science 2016-11-17 Siu-Wai Ho , Terence H. Chan , Alex Grant , Chinthani Uduwerelle

Since its origin in the thermodynamics of the 19th century, the concept of entropy has also permeated other fields of physics and mathematics, such as Classical and Quantum Statistical Mechanics, Information Theory, Probability Theory,…

Machine Learning · Statistics 2025-03-06 Salomé A. Sepúveda Fontaine , José M. Amigó

The concept of Relative Divergence of one Grading Function from another is extended from totally ordered chains to power sets of finite event spaces. Shannon Entropy concept is extended to normalized grading functions on such power sets.…

Probability · Mathematics 2022-07-15 Alexander Dukhovny

The Shannon-Khinchin axioms are generalized to nonextensive systems and the uniqueness theorem for the nonextensive entropy is proved rigorously. In the present axioms, Shannon additivity is used as additivity in contrast to…

Mathematical Physics · Physics 2007-05-23 Hiroki Suyari

The form invariance of pseudoadditivity is shown to determine the structure of nonextensive entropies. Nonextensive entropy is defined as the appropriate expectation value of nonextensive information content, similar to the definition of…

Statistical Mechanics · Physics 2009-11-07 Hiroki Suyari

Understanding the way in which random entities interact is of key interest in numerous scientific fields. This can range from a full characterization of the joint distribution to single scalar summary statistics. In this work we identify a…

Statistics Theory · Mathematics 2016-11-22 Yaniv Tenzer , Gal Elidan

We show for a general pure entangled state of two two-level atoms, the von Neumann entropy of the partial traces can be directly measured from the magnitude of the mean spin vector of a single atom of the pair. We emphasize the fact that…

Quantum Physics · Physics 2020-06-02 Ram Narayan Deb

The leakage chain rule for quantum min-entropy quantifies the change of min-entropy when one party gets additional leakage about the information source. Herein we provide an interactive version that quantifies the change of min-entropy…

Quantum Physics · Physics 2018-10-26 Ching-Yi Lai , Kai-Min Chung

Information has an entropic character which can be analyzed within the Statistical Theory in molecular systems. R. Landauer and C.H. Bennett showed that a logical copy can be carried out in the limit of no dissipation if the computation is…

Biological Physics · Physics 2012-08-15 J. Ricardo Arias-Gonzalez

Relations among von Neumann entropies of different parts of an $N$-partite quantum system have direct impact on our understanding of diverse situations ranging from spin systems to quantum coding theory and black holes. Best formulated in…

Quantum Physics · Physics 2024-01-03 Matthias Christandl , Bergfinnur Durhuus , Lasse Harboe Wolff

When the von Neumann entropy (VNE) of a system increases due to measurements, certain information is lost, some of which may be recoverable. We define information retrievability (IR) and information loss (IL) as functions of the density…

Quantum Physics · Physics 2025-03-27 Xing M. Wang

We conclude a sequence of work by giving near-optimal sketching and streaming algorithms for estimating Shannon entropy in the most general streaming model, with arbitrary insertions and deletions. This improves on prior results that obtain…

Data Structures and Algorithms · Computer Science 2008-12-18 Nicholas J. A. Harvey , Jelani Nelson , Krzysztof Onak