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Related papers: Fisher Information and Atomic Structure

200 papers

We analyze the scaling of quantum Fisher information with the number of system particles in the limit of large number of particles, as a function of the number of parties interacting with each other, for encoding Hamiltonians having…

Quantum Physics · Physics 2026-02-05 Aparajita Bhattacharyya , Debarupa Saha , Ujjwal Sen

Relativistic effects on the precision of quantum metrology for particle detectors, such as two-level atoms are studied. The quantum Fisher information is used to estimate the phase sensitivity of atoms in non-inertial motions or in…

Quantum Physics · Physics 2016-06-22 Xiang Hao , Yinzhong Wu

Given a set of measurements, observability characterizes the distinguishability of a system's initial state, whereas constructability focuses on the final state in a trajectory. In the presence of process and/or measurement noise, the…

Systems and Control · Electrical Eng. & Systems 2025-03-03 Burak Boyacıoğlu , Floris van Breugel

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

It is shown that calculation of the momentum Fisher information of the quasione- dimensional hydrogen atom recently presented by Saha et al (2017 Eur. J. Phys. {\bf 38} 025103) is wrong. A correct derivation is provided and its didactical…

Quantum Physics · Physics 2017-03-13 O. Olendski

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

Random fields are useful mathematical objects in the characterization of non-deterministic complex systems. A fundamental issue in the evolution of dynamical systems is how intrinsic properties of such structures change in time. In this…

Information Theory · Computer Science 2017-03-14 Alexandre L. M. Levada

We study the problem of parameter estimation in time series stemming from general stochastic processes, where the outcomes may exhibit arbitrary temporal correlations. In particular, we address the question of how much Fisher information is…

Statistical Mechanics · Physics 2023-09-06 Joseph A. Smiga , Marco Radaelli , Felix C. Binder , Gabriel T. Landi

Bohr's dictum "Physical phenomena are observed relative to different experimental setups" is applied to a set of binary elements that represent the smallest units of information. A description relative to "macroscopic" setups of such…

General Physics · Physics 2007-05-23 Walter Smilga

The statistical properties of ions in two-dimensional fully developed turbulence have been compared between two different numerical algorithms. In particular, we compare Hybrid Particle In Cell (hybrid PIC with fluid electrons) and full PIC…

Space Physics · Physics 2019-09-25 Francesco Pecora , Francesco Pucci , Giovanni Lapenta , David Burgess , Sergio Servidio

We report on a recently proposed approach, inspired by quantum informationtheory, for calculating low-energy nuclear structure in the framework of the configuration-interaction shell-model. Empirical evidence has demonstrated that the…

Nuclear Theory · Physics 2025-04-02 Calvin W. Johnson , Oliver C. Gorton

The analysis and modelling of a range of plasmas (for example: astrophysical, laser-produced and fusion), require atomic data for a number of parameters, such as energy levels, radiative rates and electron impact excitation rates, or…

Atomic Physics · Physics 2017-10-09 K. M. Aggarwal

Consider two forms of sampling from a population: (i) drawing $s$ samples of $n$ elements with replacement and (ii) drawing a single sample of $ns$ elements. In this paper, under the setting where the descending order population frequency…

Statistics Theory · Mathematics 2018-02-05 Koji Tsukuda , Shuhei Mano

We study the onset of particle statistics effects as the temperature is lowered in strongly correlated two-dimensional Hubbard models. We utilize numerical linked-cluster expansions and focus on the properties of interacting lattice…

Strongly Correlated Electrons · Physics 2012-08-31 Ehsan Khatami , Marcos Rigol

Fisher information measures a disorder system, which is specified by a corresponding probability, the likelihood. In this article, we provide a bridge to connect classical and quantum mechanics by using Fisher information. Following the…

Quantum Physics · Physics 2014-12-30 Tzu-Chao Hung

Relative Fisher information (IR), which is a measure of correlative fluctuation between two probability densities, has been pursued for a number of quantum systems, such as, 1D quantum harmonic oscillator (QHO) and a few central potentials…

Quantum Physics · Physics 2019-04-05 Neetik Mukherjee , Amlan K. Roy

Starting from a set of different two- and three-nucleon interactions from chiral effective field theory, we use the importance-truncated no-core shell model for ab initio calculations of excitation energies as well as electric quadrupole…

Nuclear Theory · Physics 2016-08-08 Angelo Calci , Robert Roth

A quantum measurement is Fisher symmetric if it provides uniform and maximal information on all parameters that characterize the quantum state of interest. Using (complex projective) 2-designs, we construct measurements on a pair of…

Quantum Physics · Physics 2018-01-25 Huangjun Zhu , Masahito Hayashi

We show that both the classical as well as the quantum definitions of the Fisher information faithfully identify resourceful quantum states in general quantum resource theories, in the sense that they can always distinguish between states…

Quantum Physics · Physics 2021-11-25 Kok Chuan Tan , Varun Narasimhachar , Bartosz Regula

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