English
Related papers

Related papers: Invariant density statistical quantifiers and a te…

200 papers

Atmospheric flows exhibit long-range spatiotemporal correlations manifested as the fractal geometry to the global cloud cover pattern concomitant with inverse power law form for power spectra of temporal fluctuations on all space-time…

chao-dyn · Physics 2009-10-31 A. M. Selvam , S. Fadnavis

The Fisher information matrix (FIM) is a key quantity in statistics as it is required for example for evaluating asymptotic precisions of parameter estimates, for computing test statistics or asymptotic distributions in statistical testing,…

Methodology · Statistics 2023-02-07 Maud Delattre , Estelle Kuhn

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

The concept of temperature is one of the key ideas in describing the thermodynamical properties of a physical system. In classical statistical mechanics of ideal gases, the notion of temperature can be described in two different ways, the…

Statistical Mechanics · Physics 2007-11-12 Krishna R. Narayanan , Arun R. Srinivasa

Information processing abilities of active matter are studied in the reservoir computing (RC) paradigm to infer the future state of a chaotic signal. We uncover an exceptional regime of agent dynamics that has been overlooked previously. It…

Adaptation and Self-Organizing Systems · Physics 2026-01-26 Mario U. Gaimann , Miriam Klopotek

The lattice dynamics of coesite has been studied by a combination of diffuse x-ray scattering, inelastic x-ray scattering and an ab initio lattice dynamics calculation. The combined technique gives access to the full lattice dynamics in…

We consider the impact that temporal correlations in the measurement statistics can have on the achievable precision in a sequential metrological protocol. In this setting, and for a single quantum probe, we establish that it is the…

Quantum Physics · Physics 2024-04-02 Eoin O'Connor , Steve Campbell , Gabriel T. Landi

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 apply estimation theory to a system formed by two interacting trapped ions. By using the Fisher matrix formalism, we introduce a simple scheme for estimation of the temperature of the longitudinal vibrational modes of the ions. We use…

Quantum Physics · Physics 2022-05-26 O. P. de Sá Neto , H. A. S. Costa , G. A. Prataviera , M. C. de Oliveira

Classical Fisher-information asymptotics describe the covariance of regular efficient estimators through the local quadratic approximation of the log-likelihood, and thus capture first-order geometry only. In curved models, including…

Statistics Theory · Mathematics 2026-04-15 Malik Amir , Sourangshu Ghosh

We study the probability densities of finite-time or \local Lyapunov exponents (LLEs) in low-dimensional chaotic systems. While the multifractal formalism describes how these densities behave in the asymptotic or long-time limit, there are…

chao-dyn · Physics 2009-10-31 Awadhesh Prasad , Ramakrishna Ramaswamy

The dynamics of two variants of quantum Fisher information under decoherence are investigated from a geometrical point of view. We first derive the explicit formulas of these two quantities for a single qubit in terms of the Bloch vector.…

Quantum Physics · Physics 2013-02-27 Wei Zhong , Zhe Sun , Jian Ma , Xiaoguang Wang , Franco Nori

We analyze a specific role of probability density gradients in the theory of irreversible transport processes. The classic Fisher information and information entropy production concepts are found to be intrinsically entangled with the very…

Statistical Mechanics · Physics 2007-05-23 Piotr Garbaczewski

A central problem in data analysis is the low dimensional representation of high dimensional data, and the concise description of its underlying geometry and density. In the analysis of large scale simulations of complex dynamical systems,…

Numerical Analysis · Mathematics 2007-05-23 Boaz Nadler , Stephane Lafon , Ronald R. Coifman , Ioannis G. Kevrekidis

We present a new method for proving sharp local propagation of chaos in Fisher Information for particles with smooth interaction and drift. We rely on a new Lemma computing the Fisher Information of two diffusion processes with smooth…

Probability · Mathematics 2025-11-26 Jules Grass , Christophe Poquet , Arnaud Guillin

We analyse the impact of temperature on the diffusion coefficient of an inertial Brownian particle moving in a symmetric periodic potential and driven by a symmetric time-periodic force. Recent studies have revealed the low friction regime…

Statistical Mechanics · Physics 2023-06-28 I. G. Marchenko , V. Aksenova , I. I. Marchenko , J. Łuczka , J. Spiechowicz

Using the tools of random matrix theory we develop a statistical analysis of the transport properties of thermoelectric low-dimensional systems made of two electron reservoirs set at different temperatures and chemical potentials, and…

Mesoscale and Nanoscale Physics · Physics 2016-08-23 Adel Abbout , Henni Ouerdane , Christophe Goupil

Informational dependence between statistical or quantum subsystems can be described with Fisher matrix or Fubini-Study metric obtained from variations of the sample/configuration space coordinates. Using these non-covariant objects as…

High Energy Physics - Theory · Physics 2019-01-30 Vitaly Vanchurin

A relevant problem in dynamics is to characterize how deterministic systems may exhibit features typically associated to stochastic processes. A widely studied example is the study of (normal or anomalous) transport properties for…

Chaotic Dynamics · Physics 2023-02-15 Roberto Artuso , Tulio M. de Oliveira , Cesar Manchein

Learning dynamics from dissipative chaotic systems is notoriously difficult due to their inherent instability, as formalized by their positive Lyapunov exponents, which exponentially amplify errors in the learned dynamics. However, many of…

Machine Learning · Computer Science 2024-06-07 Yair Schiff , Zhong Yi Wan , Jeffrey B. Parker , Stephan Hoyer , Volodymyr Kuleshov , Fei Sha , Leonardo Zepeda-Núñez