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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

Under the scenario of generalized measurements, it can be questioned how much of quantum uncertainty can be attributed to measuring device, independent of the uncertainty in the measured system. On the course to answer the question, we…

Quantum Physics · Physics 2016-08-01 Kyunghyun Baek , Wonmin Son

It is well known that to estimate the Shannon entropy for symbolic sequences accurately requires a large number of samples. When some aspects of the data are known it is plausible to attempt to use this to more efficiently compute entropy.…

Data Analysis, Statistics and Probability · Physics 2018-05-18 Andrew D. Back , Daniel Angus , Janet Wiles

In this paper we remark that Shannon entropy can be expressed as a function of the self-information (i.e. the logarithm) and the inverse of the Lambert $W$ function. It means that we consider that Shannon entropy has the trace form: $-k…

Statistical Mechanics · Physics 2019-07-05 Laurent Truffet

It is pointed out that the case for Shannon entropy and von Neumann entropy, as measures of uncertainty in quantum mechanics, is not as bleak as suggested in quant-ph/0006087. The main argument of the latter is based on one particular…

Quantum Physics · Physics 2007-05-23 Michael J. W. Hall

Subword tokenization is a key part of many NLP pipelines. However, little is known about why some tokenizer and hyperparameter combinations lead to better downstream model performance than others. We propose that good tokenizers lead to…

Computation and Language · Computer Science 2023-06-30 Vilém Zouhar , Clara Meister , Juan Luis Gastaldi , Li Du , Mrinmaya Sachan , Ryan Cotterell

Calculating the Shannon entropy for symbolic sequences has been widely considered in many fields. For descriptive statistical problems such as estimating the N-gram entropy of English language text, a common approach is to use as much data…

Information Theory · Computer Science 2018-05-24 Andrew D. Back , Daniel Angus , Janet Wiles

For a certain moment, the information volume represented in a probability space can be accurately measured by Shannon entropy. But in real life, the results of things usually change over time, and the prediction of the information volume…

Information Theory · Computer Science 2020-12-15 Qianli Zhou , Yong Deng

We show that a proper expression of the uncertainty relation for a pair of canonically-conjugate continuous variables relies on entropy power, a standard notion in Shannon information theory for real-valued signals. The resulting…

Quantum Physics · Physics 2018-01-16 Anaelle Hertz , Michael G. Jabbour , Nicolas J. Cerf

Building on Shannon's lead, let's consider a more malleable expression for tracking uncertainty, and states of "knowledge available" vs. "knowledge missing," to better practice innovation, improve risk management, and successfully measure…

Information Theory · Computer Science 2010-06-08 Gideon Samid

A tight information-theoretic measurement uncertainty relation is experimentally tested with neutron spin-1/2 qubits. The noise associated to the measurement of an observable is defined via conditional Shannon entropies and a tradeoff…

Quantum Physics · Physics 2019-02-12 Bülent Demirel , Stephan Sponar , Alastair A. Abbott , Cyril Branciard , Yuji Hasegawa

We propose a compression-based version of the empirical entropy of a finite string over a finite alphabet. Whereas previously one considers the naked entropy of (possibly higher order) Markov processes, we consider the sum of the…

Information Theory · Computer Science 2011-04-05 Paul M. B. Vitányi

In this paper we discuss about the validity of the Shannon entropy functional in connection with the correct Gibbs-Hertz probability distribution function. We show that there is no contradiction in using the Shannon-Gibbs functional and…

Classical Physics · Physics 2015-03-11 Alessio Gagliardi , Alessandro Pecchia

We share a small connection between information theory, algebra, and topology - namely, a correspondence between Shannon entropy and derivations of the operad of topological simplices. We begin with a brief review of operads and their…

Algebraic Topology · Mathematics 2021-09-13 Tai-Danae Bradley

This paper derives bounds for two omnipresent information theoretic measures, the Shannon entropy and its complementary dual, the extropy. Based on a large size data set from a logconcave model, the said bounds are obtained for the entropy…

Statistics Theory · Mathematics 2025-07-21 Konstantinos Zografos

Information based thermodynamic logic is revisited. It consists of two parts: Part A applies the modern theory of probability in which an arbitrary convex function \phi is employed as an analytic "device" to express information as…

Statistical Mechanics · Physics 2023-12-07 Bing Miao , Hong Qian , Yong-Shi Wu

Park et al. [Phys. Rev. A 106, L031504 (2022)] showed that the Shannon entropy of the probability distribution of a single random variable for far-field profiles (FFPs) in deformed microcavity lasers can efficiently measure the…

Optics · Physics 2022-12-14 Kyu-Won Park , Kwon-Wook Son , Chang-Hyun Ju , Kabgyun Jeong

We study an information-theoretic measure of uncertainty for quantum systems. It is the Shannon information $I$ of the phase space probability distribution $\la z | \rho | z \ra $, where $|z \ra $ are coherent states, and $\rho$ is the…

General Relativity and Quantum Cosmology · Physics 2009-10-22 Arlen Anderson , Jonathan J. Halliwell

We review a new form of entropy suggested by us, with origin in mixing of states of systems due to interactions and deformations of phase cells. It is demonstrated that this nonextensive form also leads to asymmetric maximal entropy…

Statistical Mechanics · Physics 2009-06-16 Fariel Shafee

To overcome the drawbacks of Shannon's entropy, the concept of cumulative residual and past entropy has been proposed in the information theoretic literature. Furthermore, the Shannon entropy has been generalized in a number of different…

Information Theory · Computer Science 2021-03-23 Chanchal Kundu , Antonio Di Crescenzo , Maria Longobardi