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We develop a general method to study the Fisher information distance in central limit theorem for nonlinear statistics. We first construct completely new representations for the score function. We then use these representations to derive…

Probability · Mathematics 2024-09-23 Nguyen Tien Dung

This is a short note for some basics of information geometry from thermodynamics and Callen's themostatistics.

Statistical Mechanics · Physics 2022-12-13 Tatsuaki Wada

Diffraction on the slit can be interpreted in accordance with the Heisenberg uncertainty principle. This elementary example hints at the importance of the information theory for the quantum physics. The role played by one particularly…

Quantum Physics · Physics 2007-05-23 Z. Hradil , J. Rehacek

The notions of (metric) hypersurface data were introduced in [Mars,2013] as a tool to analyze, from an abstract viewpoint, hypersurfaces of arbitrary signature in pseudo-riemannian manifolds. In this paper, general geometric properties of…

General Relativity and Quantum Cosmology · Physics 2024-02-13 Marc Mars

In this paper a class of dynamical systems describing expectation variables exactly derived from continuous-time master equations is introduced and studied from the viewpoint of differential geometry, where such master equations consist of…

Mathematical Physics · Physics 2018-11-05 Shin-Itiro Goto , Hideitsu Hino

We show that the mathematical form of the information measure of Fisher's I for a Gibbs' canonical probability distribution (the most important one in statistical mechanics) incorporates important features of the intrinsic structure of…

Statistical Mechanics · Physics 2007-05-23 F. Pennini , A. Plastino

A statistical manifold is a pseudo-Riemannian manifold endowed with a Codazzi structure. This structure plays an important role in Information Geometry and its related fields, e.g., a statistical model admits this structure with the…

Differential Geometry · Mathematics 2024-03-13 Kaito Kayo

Physical systems behave according to their underlying dynamical equations which, in turn, can be identified from experimental data. Explaining data requires selecting mathematical models that best capture the data regularities. Identifying…

Data Analysis, Statistics and Probability · Physics 2014-03-18 Carlo Cafaro

The Fisher information matrix (FIM) plays an important role in the analysis of parameter inference and system design problems. In a number of cases, however, the statistical data distribution and its associated information matrix are either…

Statistics Theory · Mathematics 2016-11-24 Dave Zachariah , Petre Stoica

In this paper, we show how information geometry, the natural geometry of discrete probability distributions, can be used to derive the quantum formalism. The derivation rests upon three elementary features of quantum phenomena, namely…

Quantum Physics · Physics 2010-02-14 Philip Goyal

In quantum resource theory (QRT), asymmetry recognized as a valid resource for the advantage of various quantum information processing. In this paper, we establish the resource theory of asymmetry using quantum Fisher information (QFI). By…

Quantum Physics · Physics 2021-10-07 R. Muthuganesan , V. K. Chandrasekar

In this note we highlight some connections of UMAP to the basic principles of Information Geometry. Originally, UMAP was derived from Category Theory observations. However, we posit that it also has a natural geometric interpretation.

Computational Geometry · Computer Science 2024-12-05 Alexander Kolpakov , Aidan Rocke

The purpose of this paper is to employ the language of Cartan moving frames to study the geometry of the data manifolds and its Riemannian structure, via the data information metric and its curvature at data points. Using this framework and…

Machine Learning · Statistics 2024-11-21 Eliot Tron , Rita Fioresi , Nicolas Couellan , Stéphane Puechmorel

The Fisher information matrix can be used to characterize the local geometry of the parameter space of neural networks. It elucidates insightful theories and useful tools to understand and optimize neural networks. Given its high…

Machine Learning · Computer Science 2024-10-31 Alexander Soen , Ke Sun

We prove the correspondence between the information geometry of a signal filter and a K\"ahler manifold. The information geometry of a minimum-phase linear system with a finite complex cepstrum norm is a K\"ahler manifold. The square of the…

Differential Geometry · Mathematics 2015-03-26 Jaehyung Choi , Andrew P. Mullhaupt

The space of all probability measures having positive density function on a connected compact smooth manifold $M$, denoted by $\mathcal{P}(M)$, carries the Fisher information metric $G$. We define the geometric mean of probability measures…

Differential Geometry · Mathematics 2023-05-19 Mitsuhiro Itoh , Hiroyasu Satoh

The Fisher information matrix (FIM) is a foundational concept in statistical signal processing. The FIM depends on the probability distribution, assumed to belong to a smooth parametric family. Traditional approaches to estimating the FIM…

Computation · Statistics 2015-06-22 Visar Berisha , Alfred O. Hero

The Shahshahani geometry of evolutionary game theory is realized as the information geometry of the simplex, deriving from the Fisher information metric of the manifold of categorical probability distributions. Some essential concepts in…

Information Theory · Computer Science 2009-11-10 Marc Harper

We investigate behavior of the Fisher information matrix of general stable distributions. DuMouchel (1975, 1983) proved that the Fisher information of characteristic exponent \alpha diverges to infinity as \alpha approaches 2. Nagaev and…

Statistics Theory · Mathematics 2007-06-13 Muneya Matsui

Motivated by the corrected form of the entropy-area law, and with the help of von Neumann entropy of quantum matter, we construct an emergent spacetime by the virtue of the geometric language of statistical information manifolds. We discuss…

General Relativity and Quantum Cosmology · Physics 2023-07-24 Hassan Alshal