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Predicting how systems respond to external perturbations far from equilibrium remains a fundamental challenge across physics, chemistry, and biology. We present a unified response framework for stochastic Markov dynamics that integrates…

Statistical Mechanics · Physics 2026-05-13 Jiming Zheng , Zhiyue Lu

The minimum achievable statistical uncertainty in the estimation of physical parameters is determined by the quantum Fisher information. Its computation for noisy systems is still a challenging problem. Using a variational approach, we…

Quantum Physics · Physics 2012-11-21 B. M. Escher , L. Davidovich , N. Zagury , R. L. de Matos Filho

Non-equilibrium stationary fluctuations may exhibit a special symmetry called fluctuation relations (FR). Here, we show that this property is always satisfied by the subtraction of two random and independent variables related by a…

Statistical Mechanics · Physics 2011-12-13 Adrian A. Budini

In this paper we reconsider the single parameter quantum Fisher information (QFI) and compare it with the two-parameter one. We find simple relations connecting the single parameter QFI (both in the asymmetric and symmetric phase shift…

Quantum Physics · Physics 2020-07-08 Stefan Ataman

Quantum sensors driven into the quantum chaotic regime can have dramatically enhanced sensitivity, which, however, depends intricately on the details of the underlying classical phase space. Here, we develop an accurate semiclassical…

Quantum Physics · Physics 2026-01-26 Mahdi RouhbakhshNabati , Daniel Braun , Henning Schomerus

Information geometry provides a tool to systematically investigate parameter sensitivity of the state of a system. If a physical system is described by a linear combination of eigenstates of a complex (that is, non-Hermitian) Hamiltonian,…

Quantum Physics · Physics 2013-08-26 Dorje C. Brody , Eva-Maria Graefe

We provide a new perspective on Stein's so-called density approach by introducing a new operator and characterizing class which are valid for a much wider family of probability distributions on the real line. We prove an elementary…

Probability · Mathematics 2013-04-05 Christophe Ley , Yvik Swan

The Fisher information matrix (FIM) is a fundamental quantity to represent the characteristics of a stochastic model, including deep neural networks (DNNs). The present study reveals novel statistics of FIM that are universal among a wide…

Machine Learning · Statistics 2019-10-10 Ryo Karakida , Shotaro Akaho , Shun-ichi Amari

The subjects of the paper are the likelihood method (LM) and the expected Fisher information (FI) considered from the point od view of the construction of the physical models which originate in the statistical description of phenomena. The…

Data Analysis, Statistics and Probability · Physics 2013-10-08 E. W. Piotrowski , J. Sladkowski , J. Syska , S. Zajac

Fisher information, lies at the heart of parameter estimation theory, was recently found to have a close relation with multipartite entanglement (Pezz\'{e} and Smerzi, Phys. Rev. Lett. 102, 100401). We use Fisher information to distinguish…

Quantum Physics · Physics 2009-05-05 Jian Ma , Xiaoguang Wang

Based on the normal distribution and its properties, i.e., average and variance, Fisher works have provided a conceptual framework to identify genotype-phenotype associations. While Fisher intuition has proved fruitful over the past…

Populations and Evolution · Quantitative Biology 2023-07-06 Cyril Rauch , Panagiota Kyratzi , Andras Paldi

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

In this paper, our prime objective is to apply the techniques of parameter estimation theory and the concept of Quantum Metrology in the form of Fisher Information to investigate the role of certain physical quantities in the open quantum…

High Energy Physics - Theory · Physics 2021-03-30 Sayantan Choudhury , Satyaki Chowdhury , Nitin Gupta , Abinash Swain

In this paper, a new three-parameter lifetime distribution is introduced and many of its standard properties are discussed. These include shape of the probability density function, hazard rate function and its shape, quantile function,…

Methodology · Statistics 2013-08-21 Min Wang

Quantifying measurement precision in quantum systems is vital for advancing quantum technologies such as sensing, communication, and computation. The quantum Fisher information (QFI) sets the ultimate precision bound in Hermitian systems;…

Quantum Physics · Physics 2026-03-12 Javid Naikoo , Ravindra W. Chhajlany , Jan Kołodyński , Adam Miranowicz

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

This paper deals with the problem of estimating the coupling constant $\theta$ of a mixing quantum Markov chain. For a repeated measurement on the chain's output we show that the outcomes' time average has an asymptotically normal…

Quantum Physics · Physics 2011-06-23 Madalin Guta

Quantum Fisher information (QFI) plays a vital role in quantum precision measurement, quantum information, many-body physics, and other domains. Obtaining the QFI from experiment for a quantum state reveals insights such as the limits of…

Quantum Physics · Physics 2024-08-26 Qi Liu

Noise affects the performance of quantum technologies, hence the importance of elaborating operative figures of merit that can capture its impact in exact terms. In quantum metrology, the introduction of the Fisher information measurement…

Quantum Physics · Physics 2024-09-30 Francesco Albarelli , Ilaria Gianani , Marco G. Genoni , Marco Barbieri

Fisher information and Shannon entropy are fundamental tools for understanding and analyzing dynamical systems from complementary perspectives. They can characterize unknown parameters by quantifying the information contained in variables,…

Information Theory · Computer Science 2025-12-19 Yuxuan Bao , J. Nathan Kutz