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Information geometry is concerned with the application of differential geometry concepts in the study of the parametric spaces of statistical models. When the random variables are independent and identically distributed, the underlying…

Information Theory · Computer Science 2021-10-05 Alexandre L. M. Levada

The introduction of a metric onto the space of parameters in models in Statistical Mechanics and beyond gives an alternative perspective on their phase structure. In such a geometrization, the scalar curvature, R, plays a central role. A…

Statistical Mechanics · Physics 2009-11-10 W. Janke , D. A. Johnston , R. Kenna

The constraints imposed on hydrodynamics by the structure of gauge and gravitational anomalies are studied in two dimensions. By explicit integration of the consistent gravitational anomaly, we derive the equilibrium partition function at…

High Energy Physics - Theory · Physics 2012-11-06 Manuel Valle

Information geometry provides a tool to systematically investigate parameter sensitivity of the state of a system. If a physical system is described by a linear combination of eigenstates of a complex (that is, non-Hermitian) Hamiltonian,…

Quantum Physics · Physics 2013-08-26 Dorje C. Brody , Eva-Maria Graefe

Information theoretic geometry near critical points in classical and quantum systems is well understood for exactly solvable systems. Here we show that renormalization group flow equations can be used to construct the information metric and…

Statistical Mechanics · Physics 2018-11-21 Reevu Maity , Subhash Mahapatra , Tapobrata Sarkar

Partial differential equations describing compressible fluids are prone to the formation of shock singularities, arising from faster upstream fluid particles catching up to slower, downstream ones. In geometric terms, this causes the…

Analysis of PDEs · Mathematics 2026-01-07 Ruijia Cao , Florian Schäfer

We study geodesics on the parameter manifold, for systems exhibiting second order classical and quantum phase transitions. The coupled non-linear geodesic equations are solved numerically for a variety of models which show such phase…

Statistical Mechanics · Physics 2015-06-11 Prashant Kumar , Subhash Mahapatra , Prabwal Phukon , Tapobrata Sarkar

The manifold of coupling constants parametrizing a quantum Hamiltonian is equipped with a natural Riemannian metric with an operational distinguishability content. We argue that the singularities of this metric are in correspondence with…

Quantum Physics · Physics 2007-05-23 P. Zanardi , P. Giorda , M. Cozzini

In information geometry, one of the basic problem is to study the geomet-ric properties of statistical manifold. In this paper, we study the geometricstructure of the generalized normal distribution manifold and show that it has constant…

Differential Geometry · Mathematics 2019-04-05 Mingao Yuan

A model in statistical mechanics, characterised by the corresponding Gibbs measure, is a subset of the totality of probability distributions on the phase space. The shape of this subset, i.e., the geometry, then plays an important role in…

Condensed Matter · Physics 2007-05-23 D. C. Brody , A. Ritz

We show that gamma distributions provide models for departures from randomness since every neighbourhood of an exponential distribution contains a neighbourhood of gamma distributions, using an information theoretic metric topology. We…

Differential Geometry · Mathematics 2007-05-23 Khadiga Arwini , C. T. J. Dodson

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

Information geometry promotes an investigation of the geometric structure of statistical manifolds, providing a series of elucidations in various areas of scientific knowledge. In the physical sciences, especially in quantum theory, this…

Quantum Physics · Physics 2020-12-08 Gabriel F. Magno , Carlos H. Grossi , Gerardo Adesso , Diogo O. Soares-Pinto

Statistical inference more often than not involves models which are non-linear in the parameters thus leading to non-Gaussian posteriors. Many computational and analytical tools exist that can deal with non-Gaussian distributions, and…

General Relativity and Quantum Cosmology · Physics 2021-01-20 Eileen Giesel , Robert Reischke , Björn Malte Schäfer , Dominic Chia

We derive effective actions for parity-violating fluids in both $(3+1)$ and $(2+1)$ dimensions, including those with anomalies. As a corollary we confirm the most general constitutive relations for such systems derived previously using…

High Energy Physics - Theory · Physics 2019-01-11 Paolo Glorioso , Hong Liu , Srivatsan Rajagopal

In this paper and a companion paper, we show how the framework of information geometry, a geometry of discrete probability distributions, can form the basis of a derivation of the quantum formalism. The derivation rests upon a few…

Quantum Physics · Physics 2010-02-14 Philip Goyal

Although the notion of entropy lies at the core of statistical mechanics, it is not often used in statistical mechanical models to characterize phase transitions, a role more usually played by quantities such as various order parameters,…

Statistical Mechanics · Physics 2016-08-31 D. A. Johnston , W. Janke , R. Kenna

We formulate hydrodynamic equations and spectrally accurate numerical methods for investigating the role of geometry in flows within two-dimensional fluid interfaces. To achieve numerical approximations having high precision and level of…

Soft Condensed Matter · Physics 2023-02-28 Ben J. Gross , Paul J. Atzberger

Despite the simplicity of its molecular unit, water is a challenging system because of its uniquely rich polymorphism and predicted but yet unconfirmed features. Introducing a novel space of generalized coordinates that capture changes in…

We introduce a new information-geometric structure associated with the dynamics on discrete objects such as graphs and hypergraphs. The presented setup consists of two dually flat structures built on the vertex and edge spaces,…

Information Theory · Computer Science 2023-08-08 Tetsuya J. Kobayashi , Dimitri Loutchko , Atsushi Kamimura , Shuhei A. Horiguchi , Yuki Sughiyama
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