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Taking into account the density matrices with non-full ranks, we show that the fidelity susceptibility is determined by the support of the density matrix. Combining with the corresponding expression of the quantum Fisher information, we…

Quantum Physics · Physics 2014-05-28 Jing Liu , Heng-Na Xiong , Fei Song , Xiaoguang Wang

The quantum Fisher information represents the continuous family of metrics on the space of quantum states and places the fundamental limit on the accuracy of quantum state estimation. We show that the entire family of the quantum Fisher…

Quantum Physics · Physics 2023-06-07 Tomohiro Shitara , Masahito Ueda

By using the $q$-Gaussian distribution derived by the maximum entropy method for spatially-correlated $N$-unit nonextensive systems, we have calculated the generalized Fisher information matrix of $g_{\theta_n \theta_m}$ for $(\theta_1,…

Statistical Mechanics · Physics 2015-05-13 Hideo Hasegawa

Point estimators may not exist, need not be unique, and their distributions are not parameter invariant. Generalized estimators provide distributions that are parameter invariant, unique, and exist when point estimates do not. Comparing…

Statistics Theory · Mathematics 2022-11-04 Paul W. Vos

Suppose we have a high-frequency sample from the L\'{e}vy process of the form $X_t^\theta=\beta t+\gamma Z_t+U_t$, where $Z$ is a possibly asymmetric locally $\alpha$-stable L\'{e}vy process, and $U$ is a nuisance L\'{e}vy process less…

Probability · Mathematics 2015-08-17 Dmytro Ivanenko , Alexey M. Kulik , Hiroki Masuda

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

The relevance of the concept of Fisher information is increasing in both statistical physics and quantum computing. From a statistical mechanical standpoint, the application of Fisher information in the kinetic theory of gases is…

Quantum Physics · Physics 2018-05-09 Carlo Cafaro , Paul M. Alsing

The Fisher's information metric is introduced in order to find the real meaning of the probability distribution in classical and quantum systems described by Riemaniann non-degenerated superspaces. In particular, the physical r\^{o}le…

High Energy Physics - Theory · Physics 2012-12-04 Diego Julio Cirilo-Lombardo , Victor I. Afonso

We investigate the structural foundations of statistical efficiency under $\alpha$-local differential privacy, with a focus on maximizing Fisher information. Building on the role of continuous staircase mechanisms, we identify a fundamental…

Statistics Theory · Mathematics 2026-03-31 Chiara Amorino , Arnaud Gloter

We study the evolution of the nonlinear version of the Fisher information along the quasilinear heat equation. We also provide a nonlinear version of a recent functional inequality (Cie\'slak--Fuest--Hajduk--Sier\.z\k{e}ga, 2024),…

Analysis of PDEs · Mathematics 2025-09-03 Tomasz Cieślak , Kentaro Fujie , Tatsuya Hosono

Although asymptotic analyses of undirected network models based on degree sequences have started to appear in recent literature, it remains an open problem to study statistical properties of directed network models. In this paper, we…

Statistics Theory · Mathematics 2016-01-13 Ting Yan , Chenlei Leng , Ji Zhu

We develop data processing inequalities that describe how Fisher information from statistical samples can scale with the privacy parameter $\varepsilon$ under local differential privacy constraints. These bounds are valid under general…

Information Theory · Computer Science 2020-05-22 Leighton Pate Barnes , Wei-Ning Chen , Ayfer Ozgur

We study the statistical geometry of random chords on n-dimensional spheres by deriving explicit analytical expressions for the chord length distribution and its associated structural properties. A critical threshold emerges at dimension…

Probability · Mathematics 2025-06-25 Masoud Ataei

Consider the centered Gaussian vector $X$ in $\R^n$ with covariance matrix $ \Sigma.$ Randomize $\Sigma$ such that $ \Sigma^{-1}$ has a Wishart distribution with shape parameter $p>(n-1)/2$ and mean $p\sigma.$ We compute the density…

Statistics Theory · Mathematics 2022-11-28 Gérard G. Letac

The Fisher infinitesimal model is a classical model of phenotypic trait inheritance in quantitative genetics. Here, we prove that it encompasses a remarkable convexity structure which is compatible with a selection function having a convex…

Probability · Mathematics 2025-07-30 Vincent Calvez , David Poyato , Filippo Santambrogio

We study the existence of the maximal quantum Fisher information matrix in multi-parameter quantum estimation, which bounds the ultimate precision limit. We show that when the maximal quantum Fisher information matrix exists, it can be…

Quantum Physics · Physics 2017-08-02 Yu Chen , Haidong Yuan

Optimum designs for parameter estimation in generalized regression models are standardly based on the Fisher information matrix (cf. Atkinson et al (2014) for a recent exposition). The corresponding optimality criteria are related to the…

Statistics Theory · Mathematics 2015-07-28 Katarína Burclová , Andrej Pázman

A Toeplitz matrix is one in which the matrix elements are constant along diagonals. The Fisher-Hartwig matrices are much-studied singular matrices in the Toeplitz family. The matrices are defined for all orders, $N$. They are parametrized…

Mathematical Physics · Physics 2015-05-13 Hui Dai , Zachary Geary , Leo P. Kadanoff

The net Fisher information measure, defined as the product of position and momentum Fisher information measures and derived from the non-relativistic Hartree-Fock wave functions for atoms with Z=1-102, is found to correlate well with the…

Quantum Physics · Physics 2015-06-26 K. D. Sen , C. P. Panos , K. Ch. Chatzisavvas , Ch. C. Moustakidis

Choosing the Fisher information as the metric tensor for a Riemannian manifold provides a powerful yet fundamental way to understand statistical distribution families. Distances along this manifold become a compelling measure of statistical…

Statistics Theory · Mathematics 2023-06-05 Brodie A. J. Lawson , Kevin Burrage , Kerrie Mengersen , Rodrigo Weber dos Santos
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