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Related papers: A Pessimistic Approximation for the Fisher Informa…

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The Fisher information approximation (FIA) is an implementation of the minimum description length principle for model selection. Unlike information criteria such as AIC or BIC, it has the advantage of taking the functional form of a model…

Methodology · Statistics 2018-08-02 Daniel W. Heck , Morten Moshagen , Edgar Erdfelder

A new information-theoretic approach to the central limit theorem for stable laws is presented. The main novelty is the concept of relative fractional Fisher information, which shares most of the properties of the classical one, included…

Information Theory · Computer Science 2015-04-28 Giuseppe Toscani

A relationship between the Fisher information and the characteristic function is established with the help of two inequalities. A necessary and sufficient condition for equality is found. These results are used to determine the asymptotic…

Information Theory · Computer Science 2010-07-12 Cihan Tepedelenlioglu , Mahesh K. Banavar , Andreas Spanias

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

We review the introduction of likelihood functions and Fisher information in classical estimation theory, and we show how they can be defined in a very similar manner within quantum measurement theory. We show that the stochastic master…

Quantum Physics · Physics 2013-04-03 Søren Gammelmark , Klaus Mølmer

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

Informationally complete measurements form the foundation of universal quantum state reconstruction, while quantum parameter estimation is based on the local structure of the manifold of quantum states. Here we establish a general link…

Quantum Physics · Physics 2025-12-18 Rakesh Saini , Jukka Kiukas , Daniel Burgarth , Alexei Gilchrist

We present a method to generate probability distributions that correspond to metrics obeying partial differential equations generated by extremizing a functional $J[g^{\mu\nu}(\theta^i)]$, where $g^{\mu\nu}(\theta^i)$ is the Fisher metric.…

Statistical Mechanics · Physics 2009-11-10 Xavier Calmet , Jacques Calmet

We present a method to estimate the quantum Fisher information (QFI) of many-body quantum states in the presence of decoherence, where its direct evaluation requires the full spectral resolution of the density matrix. We show that, for…

Quantum Physics · Physics 2026-05-25 Francesco Musso , Vittorio Vitale , Sara Murciano

Quantum learning (in metrology and machine learning) involves estimating unknown parameters from measurements of quantum states. The quantum Fisher information matrix can bound the average amount of information learnt about the unknown…

Quantum Physics · Physics 2021-04-21 Joe H. Jenne , David R. M. Arvidsson-Shukur

Despite the widespread use and success of machine-learning techniques for detecting phase transitions from data, their working principle and fundamental limits remain elusive. Here, we explain the inner workings and identify potential…

Disordered Systems and Neural Networks · Physics 2023-11-20 Julian Arnold , Niels Lörch , Flemming Holtorf , Frank Schäfer

We present a novel synthesis of Fisher information and asset pricing theory that yields a practical method for reconstructing the probability density implicit in security prices. The Fisher information approach to these inverse problems…

Statistical Mechanics · Physics 2008-12-10 Raymond J. Hawkins , B. Roy Frieden

We consider estimating the magnitude of a monochromatic AC signal that couples to a two-level sensor. For any detection protocol, the precision achieved depends on the signal's frequency and can be quantified by the quantum Fisher…

We consider the estimation of parameters encoded in the measurement record of a continuously monitored quantum system in the jump unraveling, corresponding to a single-shot scenario, where information is continuously gathered. Here, it is…

Quantum Physics · Physics 2026-02-04 Marco Radaelli , Joseph A. Smiga , Gabriel T. Landi , Felix C. Binder

Entanglement is the key quantum resource for improving measurement sensitivity beyond classical limits. However, the production of entanglement in mesoscopic atomic systems has been limited to squeezed states, described by Gaussian…

A family of skew information quantities is obtained, in which the well-known Wigner-Yanase skew information and quantum Fisher information stand as special cases. A transparent proof of convexity of the generalized skew information is…

Quantum Physics · Physics 2023-06-14 Ma-Cheng Yang , Cong-Feng Qiao

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

The Quantum Fisher Information (QFI) plays a crucial role in quantum information theory and in many practical applications such as quantum metrology. However, computing the QFI is generally a computationally demanding task. In this work we…

Quantum Physics · Physics 2021-06-25 M. Cerezo , Akira Sone , Jacob L. Beckey , Patrick J. Coles

Fisher information, Shannon information entropy and Statistical Complexity are calculated for the interface of a normal metal and a superconductor, as a function of the temperature for several materials. The order parameter $\Psi({\bf r})$…

Quantum Physics · Physics 2018-06-05 Ch. C. Moustakidis , C. P. Panos

In this paper, we first establish general bounds on the Fisher information distance to the class of normal distributions of Malliavin differentiable random variables. We then study the rate of Fisher information convergence in the central…

Probability · Mathematics 2024-08-20 Nguyen Tien Dung , Nguyen Thu Hang
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