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Related papers: Introduction to quantum Fisher information

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In this paper we prove a nontrivial lower bound for the determinant of the covariance matrix of quantum mechanical observables, which was conjectured by Gibilisco, Isola and Imparato. The lower bound is given in terms of the commutator of…

Mathematical Physics · Physics 2009-11-13 Attila Andai

The problem of determining the intrinsic quality of a signal processing system with respect to the inference of an unknown deterministic parameter $\theta$ is considered. While the Fisher information measure $F(\theta)$ forms a classical…

Information Theory · Computer Science 2018-05-30 Manuel Stein , Josef A. Nossek

Many quantum statistical models are most conveniently formulated in terms of non-orthonormal bases. This is the case, for example, when mixtures and superpositions of coherent states are involved. In these instances, we show that the…

Quantum Physics · Physics 2019-10-02 Marco G. Genoni , Tommaso Tufarelli

We consider the problem of determining the weights of a quantum ensemble. That is to say, given a quantum system that is in a set of possible known states according to an unknown probability law, we give strategies to estimate the…

Quantum Physics · Physics 2010-02-01 J. I. de Vicente , J. Calsamiglia , R. Munoz-Tapia , E. Bagan

Fisher Information (FI) is a quantity ubiquitously measured in such varied areas like metrology, machine learning, and biological complexity. Mathematically, it represents a lower bound in the variance of unknown parameters that are related…

Statistical Mechanics · Physics 2026-01-21 Pedro B. Melo , Sílvio M. Duarte Queirós , Diogo O. Soares-Pinto , Welles A. M. Morgado

We consider kinetic models for Fermi-Dirac-like particles obeying the exclusion principle. A generalized notion of Fisher information, tailored to kinetic equations of Fermi-Dirac-Fokker-Planck type, is introduced via the associated entropy…

Analysis of PDEs · Mathematics 2025-08-22 Yuzhe Zhu

Quantum metrology enhances the sensitivity of parameter estimation using the distinctive resources of quantum mechanics such as entanglement. It has been shown that the precision of estimating an overall multiplicative factor of a…

Quantum Physics · Physics 2016-05-31 Shengshi Pang , Todd A. Brun

A framework for a quantum information theory is introduced that is based on the measure of quantum information associated with probability distribution predicted by quantum measuring of state. The entanglement between states of measured…

Quantum Physics · Physics 2007-05-23 Yi-Xin Chen

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

In this paper, we investigate steered quantum coherence, i.e., the $l_1$ norm of steered coherence and the relative entropy of steered coherence, and the quantum Fisher information in the Gibbs state of two-qubit $XXZ$ systems. Their…

Quantum Physics · Physics 2023-12-18 Biao-Liang Ye , Yao-Kun Wang , Shao-Ming Fei

This paper provides a mathematical framework for Fisher information analysis for inverse problems based on Gaussian noise on infinite-dimensional Hilbert space. The covariance operator for the Gaussian noise is assumed to be trace class,…

Mathematical Physics · Physics 2015-06-04 Sven Nordebo , Mats Gustafsson , Andrei Khrennikov , Bö rje Nilsson , Joachim Toft

In order to provide a guaranteed precision and a more accurate judgement about the true value of the Cram\'{e}r-Rao bound and its scaling behavior, an upper bound (equivalently a lower bound on the quantum Fisher information) for precision…

Quantum Physics · Physics 2017-05-04 R. Yousefjani , S. Salimi , A. S. Khorashad

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

In this chapter, a statistical measure of complexity and the Fisher-Shannon information product are introduced and their properties are discussed. These measures are based on the interplay between the Shannon information, or a function of…

Chaotic Dynamics · Physics 2012-01-13 Ricardo Lopez-Ruiz , Jaime Sanudo , Elvira Romera , Xavier Calbet

Quantum Fisher information (QFI) is a central concept in quantum sciences used to quantify the ultimate precision limit of parameter estimation, detect quantum phase transitions, witness genuine multipartite entanglement, or probe…

Quantum Physics · Physics 2026-02-09 Carlos L. Benavides-Riveros , Tomasz Wasak , Alessio Recati

This paper explores as didactically as possible the fundamental principles of both classical and quantum metrology, focusing on the Cram\'er-Rao Bound and how it defines the maximum precision in parameter estimation, taking into account…

Quantum Physics · Physics 2024-12-13 Leonardo A. M. Souza

We show that the quantum Fisher information about any phase parameter encoded in a family of pure quantum states can be faithfully compressed into a single qubit, accompanied by a logarithmic amount of classical bits. When the phase is…

Studies about Quantum Information Theory continue actively in many research institutions. Very recently, pratical setups of large scale quantum computers are widely studied e.g. quantum repeaters, memories and processors. Entanglement…

Quantum Physics · Physics 2017-05-16 Volkan Erol

Quantum systems used for metrology can offer enhanced precision over their classical counterparts. The design of quantum sensors can be optimized by maximizing the quantum Fisher information (QFI), which characterizes the precision of…

Quantum Physics · Physics 2025-08-26 George Mihailescu , Anthony Kiely , Andrew K. Mitchell

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
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