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Information geometry is used to quantify the amount of information integration within multiple terminals of a causal dynamical system. Integrated information quantifies how much information is lost when a system is split into parts and…

Information Theory · Computer Science 2017-09-08 Shun-ichi Amari , Naotsugu Tsuchiya , Masafumi Oizumi

We review basic notions in the field of information geometry such as Fisher metric on statistical manifold, $\alpha$-connection and corresponding curvature following Amari's work . We show application of information geometry to asymptotic…

Statistics Theory · Mathematics 2014-10-14 Mashbat Suzuki

Given a pure state vector |x> and a density matrix rho, the function p(x|rho)=<x|rho|x> defines a probability density on the space of pure states parameterised by density matrices. The associated Fisher-Rao information measure is used to…

Quantum Physics · Physics 2011-06-03 Dorje C. Brody

Our goal is to extend information geometry to situations where statistical modeling is not obvious. The setting is that of modeling experimental data. Quite often the data are not of a statistical nature. Sometimes also the model is not a…

Quantum Physics · Physics 2015-06-15 Jan Naudts , Ben Anthonis

We use so-called geometrical approach in description of transition from regular motion to chaotic in Hamiltonian systems with potential energy surface that has several local minima. Distinctive feature of such systems is coexistence of…

Chaotic Dynamics · Physics 2007-05-23 V. P. Berezovoj , Yu. L. Bolotin , G. I. Ivashkevych

Precision control of a quantum system requires accurate determination of the effective system Hamiltonian. We develop a method for estimating the Hamiltonian parameters for some unknown two-state system and providing uncertainty bounds on…

We introduce the information geometry module of the Python package Geomstats. The module first implements Fisher-Rao Riemannian manifolds of widely used parametric families of probability distributions, such as normal, gamma, beta,…

Machine Learning · Computer Science 2022-11-22 Alice Le Brigant , Jules Deschamps , Antoine Collas , Nina Miolane

Critical quantum metrology relies on the extreme sensitivity of a system's eigenstates near the critical point of a quantum phase transition to Hamiltonian perturbations. This means that these eigenstates are extremely sensitive to all the…

Quantum Physics · Physics 2025-06-12 George Mihailescu , Steve Campbell , Karol Gietka

We consider torsion in parameter manifolds that arises via conformal transformations of the Fisher information metric, and define it for information geometry of a wide class of physical systems. The torsion can be used to differentiate…

Classical Physics · Physics 2023-08-09 Kunal Pal , Kuntal Pal , Tapobrata Sarkar

The manifold of empirical mean values of statistical data ad infinitum has a geometric shape that depends on the probability measure that governs the generating model. Large deviation theory produces entropy functions that depend on both…

Information Theory · Computer Science 2026-05-07 Viswa Virinchi Muppirala , Hong Qian

Optimization in large language models (LLMs) unfolds over high-dimensional parameter spaces with non-Euclidean structure. Information geometry frames this landscape using the Fisher information metric, enabling more principled learning via…

Computation and Language · Computer Science 2025-12-09 Riccardo Di Sipio

We use the method of maximum entropy to model physical space as a curved statistical manifold. It is then natural to use information geometry to explain the geometry of space. We find that the resultant information metric does not describe…

General Relativity and Quantum Cosmology · Physics 2015-12-31 Ariel Caticha

Dynamical phase transitions are defined as non-analytic points of the large deviation function of current fluctuations. We show that for boundary driven systems, many dynamical phase transitions can be identified using the geometrical…

Statistical Mechanics · Physics 2017-12-13 Ohad Shpielberg

In contrast to Hermitian systems, eigenstates of non-Hermitian ones are in general nonorthogonal. This feature is most pronounced at exceptional points where several eigenstates are linearly dependent. In this work we show that near this…

Quantum Physics · Physics 2016-12-23 Alexander A. Zyablovsky , Evgeny S. Andrianov , Alexander A. Pukhov

We theoretically investigate parameter quantum estimation in quantum chaotic systems. Our analysis is based on an effective description of non-integrable quantum systems in terms of a random matrix Hamiltonian. Based on this approach we…

Recently, there has been considerable interest in the application of information geometry to quantum many body physics. This interest has been driven by three separate lines of research, which can all be understood as different facets of…

Quantum Physics · Physics 2023-09-13 J. Lambert , E. S. Sørensen

In the present work, we discuss how the functional form of thermodynamic observables can be deduced from the geometric properties of subsets of phase space. The geometric quantities taken into account are mainly extrinsic curvatures of the…

Statistical Mechanics · Physics 2020-05-01 Ghofrane Bel-Hadj-Aissa , Matteo Gori , Vittorio Penna , Giulio Pettini , Roberto Franzosi

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

Information geometry provides differential geometric concepts like a Riemannian metric, connections and covariant derivatives on spaces of probability distributions. We discuss here how these concepts apply to quantum field theories in the…

High Energy Physics - Theory · Physics 2023-04-11 Stefan Floerchinger

Physical systems behave according to their underlying dynamical equations which, in turn, can be identified from experimental data. Explaining data requires selecting mathematical models that best capture the data regularities. Identifying…

Data Analysis, Statistics and Probability · Physics 2014-03-18 Carlo Cafaro