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In the realm of deep learning, the Fisher information matrix (FIM) gives novel insights and useful tools to characterize the loss landscape, perform second-order optimization, and build geometric learning theories. The exact FIM is either…

Machine Learning · Computer Science 2021-10-29 Alexander Soen , Ke Sun

We consider the problem of estimating an arbitrary dynamical parameter of an quantum open system in the input-output formalism. For irreducible Markov processes, we show that in the limit of large times the system-output state can be…

Quantum Physics · Physics 2015-09-02 Catalin Catana , Luc Bouten , Madalin Guta

System identification is an integrant part of control theory and plays an increasing role in quantum engineering. In the quantum set-up, system identification is usually equated to process tomography, i.e. estimating a channel by probing it…

Quantum Physics · Physics 2012-11-27 Catalin Catana , Merlijn van Horssen , Madalin Guta

The quantum Fisher information, the quantum analogue of the classical Fisher information, is a central quantity in quantum metrology and quantum sensing due to its connection to parameter estimation and fidelity susceptibility. Using…

The importance of the quantum Fisher information metric is testified by the number of applications that this has in very different fields, ranging from hypothesis testing to metrology, passing through thermodynamics. Still, from the rich…

Quantum Physics · Physics 2024-04-30 Matteo Scandi , Paolo Abiuso , Jacopo Surace , Dario De Santis

For linear mixed models with co-variance matrices which are not linearly dependent on variance component parameters, we prove that the average of the observed information and the Fisher information can be split into two parts. The essential…

Methodology · Statistics 2020-05-11 Shengxin Zhu , Tongxiang Gu , Xingping Liu

This study presents the Fisher information for the position-dependent mass Schr\"odinger equation with hyperbolical potential {$V(x)=-V_0{\rm csch}^2(ax)$}. The analysis of the quantum-mechanical probability for the ground and exited states…

Quantum Physics · Physics 2015-09-30 B. J. Falaye , F. A. Serrano , Shi-Hai Dong

We study the optimality conditions of information transfer in systems with memory in the low signal-to-noise ratio regime of vanishing input amplitude. We find that the optimal mutual information is represented by a maximum-variance of the…

Neurons and Cognition · Quantitative Biology 2010-08-13 Lubomir Kostal , Petr Lansky

The Fisher information matrix summarizes the amount of information in a set of data relative to the quantities of interest. There are many applications of the information matrix in statistical modeling, system identification and parameter…

Computation · Statistics 2014-05-08 Xumeng Cao

For a known weak signal in additive white noise, the asymptotic performance of a locally optimum processor (LOP) is shown to be given by the Fisher information (FI) of a standardized even probability density function (PDF) of noise in three…

Data Analysis, Statistics and Probability · Physics 2011-11-28 Fabing Duan , Francois Chapeau-Blondeau , Derek Abbott

We find the information geometry of tempered stable processes. Beginning with the derivation of $\alpha$-divergence between two tempered stable processes, we obtain the corresponding Fisher information matrices and the $\alpha$-connections…

Differential Geometry · Mathematics 2025-12-30 Jaehyung Choi

This paper studies semiparametric Fisher information in models parametrized by general normed spaces. The main contribution is to establish that positive semiparametric Fisher information is equivalent to the gradient of the parameter of…

Statistics Theory · Mathematics 2026-04-02 Telmo Pérez-Izquierdo

The Fisher information matrix is a quantity of fundamental importance for information geometry and asymptotic statistics. In practice, it is widely used to quickly estimate the expected information available in a data set and guide…

Methodology · Statistics 2023-06-06 William R. Coulton , Benjamin D. Wandelt

Current experimental design techniques for dynamical systems often only incorporate measurement noise, while dynamical systems also involve process noise. To construct experimental designs we need to quantify their information content. The…

Methodology · Statistics 2026-03-24 Arno Strouwen , Bart M. Nicolaï , Peter Goos

We introduce the Fisher information in the basis of decay modes of Markovian dynamics, arguing that it encodes important information about the behavior of nonequilibrium systems. In particular we generalize an orthonormality relation…

Statistical Mechanics · Physics 2014-09-16 Matteo Polettini

Quantum Fisher information is a key concept in the field of quantum metrology, which aims to enhance the parameter accuracy by using quantum resources. In this paper, utilizing a representation of quantum Fisher information for a general…

Quantum Physics · Physics 2015-07-14 Xiao-Xing Jing , Jing Liu , Heng-Na Xiong , Xiaoguang Wang

We define a mixed topology on the fiber space $\cup_\mu \oplus^n L^n(\mu)$ over the space $\mathcal{M}(\Omega)$ of all finite non-negative measures $\mu$ on a separable metric space $\Omega$ provided with Borel $\sigma$-algebra. We define a…

Statistics Theory · Mathematics 2016-01-26 Hông Vân Lê

In this manuscript, we investigate the effect of the white and color noise on a accelerated two-qubit system, where different initial state setting are considered. The behavior of the survival amount of entanglement is quantified for this…

Quantum Physics · Physics 2019-07-02 F. Ebrahim , N. Metwally

In this paper, we consider a parametric hidden Markov model where the hidden state space is non necessarily finite. We provide a necessary and sufficient condition for the invertibility of the limiting Fisher information matrix.

Statistics Theory · Mathematics 2007-06-13 Randal Douc

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