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Gravitation and Astrophysics
The ICGA series of conferences is specially aimed to serve the needs of the workers in this research area in the Asia-Pacific region. The previous conferences of this series have attracted a growing number of local, regional and international participants. 2005 was an auspicious year. Not only was it the International Year of Physics, commemorating Einstein''s great achievements of 1905, it also was the anniversary of Einstein''s development of General Relativity: he submitted the final form of his field equations on 25 November, 1915. Nine decades years later, around 40 Taiwan-based participants were joined by over 40 distinguished visitors from Canada, China, France, Japan, Korea, Russia, ...
Differential Geometry and Mathematical Physics
This volume contains the text of the lectures which were given at the Differential Geometry Meeting held at Liege in 1980 and at the Differential Geometry Meeting held at Leuven in 1981. The first of these meetings was more orientated toward mathematical physics; the second has a stronger flavour of analysis. The Editors are pleased to thank the lectures who contributed scientifically to these two meetings. They are also grateful to Professor M. F1ato who has encouraged publication of these contributions in the Mathematical Physics Studies Series. We also thank the F.N.R.S. who supported financially the Contact group in differential geometry. The Universite de Liege and the Katholieke Univer...
Tenth Marcel Grossmann Meeting, The: On Recent Developments In Theoretical & Experimental General Relativity, Gravitation, & Relativistic Field Theories (In 3 Vols) - Procs Of The Mgio Meeting Held At Brazilian Ctr For Res In Phys (Cbpf)
The Marcel Grossmann meetings were conceived to promote theoretical understanding in the fields of physics, mathematics, astronomy and astrophysics and to direct future technological, observational, and experimental efforts. They review recent developments in gravitation and general relativity, with major emphasis on mathematical foundations and physical predictions. Their main objective is to bring together scientists from diverse backgrounds and their range of topics is broad, from more abstract classical theory and quantum gravity and strings to more concrete relativistic astrophysics observations and modeling.This Tenth Marcel Grossmann Meeting was organized by an international committee...
Global Aspects of Classical Integrable Systems
This book gives a complete global geometric description of the motion of the two di mensional hannonic oscillator, the Kepler problem, the Euler top, the spherical pendulum and the Lagrange top. These classical integrable Hamiltonian systems one sees treated in almost every physics book on classical mechanics. So why is this book necessary? The answer is that the standard treatments are not complete. For instance in physics books one cannot see the monodromy in the spherical pendulum from its explicit solution in terms of elliptic functions nor can one read off from the explicit solution the fact that a tennis racket makes a near half twist when it is tossed so as to spin nearly about its in...
Nonlinear Gravitodynamics
This book gives a detailed, up-to-date account of theLenseOCoThirring effect and its implications for physics andastrophysics. Starting from a profound intuition of Lense and Thirringin 1918, based on a simple solution to the linearized Einstein fieldequations, this has emerged in the past four decades as a phenomenonof extraordinary importance in cosmology, radio jets in quasars, andthe physics of neutron stars and black holes, besides leading to someof the most sophisticated experiments ever performed in the spacesurrounding our planet."
Differential Geometrical Theory of Statistics
This book is a printed edition of the Special Issue "Differential Geometrical Theory of Statistics" that was published in Entropy
Geometry and Nature
This volume is the outgrowth of a conference devoted to William K. Clifford entitled, "New Trends in Geometrical and Topological Methods", which was held at the University of Madeira in July and August 1995. The aim of the conference was to bring together active workers in fields linked to Clifford's work and to foster the exchange of ideas between mathematicians and theoretical physicists. Divided into 6 one-day sessions, each session was devoted to a specific aspect of Clifford's work. This volume is an attempt to bring the Clifford legacy in a new perspective to a larger community of mathematicians and physicists. New concepts, ideas, and results stemming from Clifford's work are discussed. Containing papers presented or submitted to the conference, each article is self-contained.
Geometric Science of Information
This book constitutes the proceedings of the 6th International Conference on Geometric Science of Information, GSI 2023, held in St. Malo, France, during August 30-September 1, 2023. The 125 full papers presented in this volume were carefully reviewed and selected from 161 submissions. They cover all the main topics and highlights in the domain of geometric science of information, including information geometry manifolds of structured data/information and their advanced applications. The papers are organized in the following topics: geometry and machine learning; divergences and computational information geometry; statistics, topology and shape spaces; geometry and mechanics; geometry, learning dynamics and thermodynamics; quantum information geometry; geometry and biological structures; geometry and applications.
Geometric Structures of Statistical Physics, Information Geometry, and Learning
Machine learning and artificial intelligence increasingly use methodological tools rooted in statistical physics. Conversely, limitations and pitfalls encountered in AI question the very foundations of statistical physics. This interplay between AI and statistical physics has been attested since the birth of AI, and principles underpinning statistical physics can shed new light on the conceptual basis of AI. During the last fifty years, statistical physics has been investigated through new geometric structures allowing covariant formalization of the thermodynamics. Inference methods in machine learning have begun to adapt these new geometric structures to process data in more abstract repres...
