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Related papers: Deformed logarithms and entropies

200 papers

Multiparameter persistent homology has emerged as a powerful generalization of topological data analysis, capable of encoding multivariate filtrations. However, the algebraic complexity of multiparameter persistence modules, marked by wild…

Algebraic Topology · Mathematics 2026-04-14 Mauricio Angel

The Heisenberg algebra is first deformed with the set of parameters ${q, l, \lambda}$ to generate a new family of generalized coherent states. In this framework, the matrix elements of relevant operators are exactly computed. A proof on…

Mathematical Physics · Physics 2013-01-03 J. D. Bukweli-Kyemba , M. N. Hounkonnou

In a recent paper, the authors proposed a general methodology for probabilistic learning on manifolds. The method was used to generate numerical samples that are statistically consistent with an existing dataset construed as a realization…

Probability · Mathematics 2018-03-30 C. Soizea , R. Ghanem , C. Safta , X. Huan , Z. P. Vane , J. Oefelein , G. Lacaz , H. N. Najm , Q. Tang , X. Chen

In this paper, we develop the notion of entropy for uniform hypergraphs via tensor theory. We employ the probability distribution of the generalized singular values, calculated from the higher-order singular value decomposition of the…

Machine Learning · Computer Science 2020-06-22 Can Chen , Indika Rajapakse

A deformed differential calculus is developed based on an associative star-product. In two dimensions the Hamiltonian vector fields model the algebra of pseudo-differential operator, as used in the theory of integrable systems. Thus one…

High Energy Physics - Theory · Physics 2020-12-16 I. A. B. Strachan

The paper contributes to strengthening the relation between machine learning and the theory of differential equations. In this context, the inverse problem of fitting the parameters, and the initial condition of a differential equation to…

Machine Learning · Computer Science 2022-06-22 Imre Fekete , András Molnár , Péter L. Simon

We consider the most general set of integrable deformations extending the $T\bar{T}$ deformation of two-dimensional relativistic QFTs. They are CDD deformations of the theory's factorised S-matrix related to the higher-spin conserved…

High Energy Physics - Theory · Physics 2020-05-27 Guzmán Hernández-Chifflet , Stefano Negro , Alessandro Sfondrini

We study the entanglement entropy of theories that are derived from relevant perturbation of given CFTs for regions with a singular boundary by using the AdS/CFT correspondence. In the smooth case, it is well known that a relevant…

High Energy Physics - Theory · Physics 2019-02-26 Mostafa Ghasemi , Shahrokh Parvizi

It has recently been a common practice to maximize the deformed entropies through the escort averaging scheme. However, whatever averaging procedure is employed, one should recover the ordinary Shannon maximization results in the…

Statistical Mechanics · Physics 2018-03-23 Thomas Oikonomou , G. Baris Bagci

We develop a general method for computing logarithmic and log-gamma expectations of distributions. As a result, we derive series expansions and integral representations of the entropy for several fundamental distributions, including the…

Information Theory · Computer Science 2018-07-24 Mahdi Cheraghchi

The deformation principle admits one to obtain a very broad class of nonuniform geometries as a result of deformation of the proper Euclidean geometry. The Riemannian geometry is also obtained by means of a deformation of the Euclidean…

General Mathematics · Mathematics 2007-05-23 Yuri A. Rylov

Using the AdS/CFT correspondence, we examine entanglement entropy for a boundary theory deformed by a relevant operator and establish two results. The first is that if there is a contribution which is logarithmic in the UV cut-off, then the…

High Energy Physics - Theory · Physics 2012-11-07 Ling-Yan Hung , Robert C. Myers , Michael Smolkin

We calculate explicit formulae for the Shannon entropies of several families of tailored random graph ensembles for which no such formulae were as yet available, in leading orders in the system size. These include bipartite graph ensembles…

Disordered Systems and Neural Networks · Physics 2014-04-24 Ekaterina Roberts , Ton Coolen

We present a path toward determining the statistical origin of the thermodynamic limit for systems with long-range interactions. We assume throughout that the systems under consideration have thermodynamic properties given by the Tsallis…

Statistical Mechanics · Physics 2015-06-18 Nikos Kalogeropoulos

In this paper we generalize the technique of deflation to define two new methods to systematically find many local minima of a nonlinear least squares problem. The methods are based on the Gauss-Newton algorithm, and as such do not require…

Numerical Analysis · Mathematics 2025-06-13 Alban Bloor Riley , Marcus Webb , Michael L Baker

Shannon entropy, a cornerstone of information theory, statistical physics and inference methods, is uniquely identified by the Shannon-Khinchin or Shore-Johnson axioms. Generalizations of Shannon entropy, motivated by the study of…

Data Analysis, Statistics and Probability · Physics 2026-04-20 Andrea Somazzi , Diego Garlaschelli

For the first time, a general two-parameter family of entropy conservative numerical fluxes for the shallow water equations is developed and investigated. These are adapted to a varying bottom topography in a well-balanced way, i.e.…

Numerical Analysis · Mathematics 2017-03-24 Hendrik Ranocha

We construct two-parameter families of integrable $\lambda$-deformations of two-dimensional field theories. These interpolate between a CFT (a WZW/gauged WZW model) and the non-Abelian T-dual of a principal chiral model on a group/symmetric…

High Energy Physics - Theory · Physics 2015-09-01 Konstantinos Sfetsos , Konstantinos Siampos , Daniel C. Thompson

It is not obvious how to extend Shannon's original information entropy to higher dimensions, and many different approaches have been tried. We replace the English text symbol sequence originally used to illustrate the theory by a discrete,…

Information Theory · Computer Science 2016-09-06 Kieran G. Larkin

Based on Jaynes' maximum entropy principle, exponential random graphs provide a family of principled models that allow the prediction of network properties as constrained by empirical data (observables). However, their use is often hindered…

Statistical Mechanics · Physics 2020-12-03 Szabolcs Horvát , Éva Czabarka , Zoltán Toroczkai