Generalised Thermostatistics [recurso electrónico] / by Jan Naudts.

Por: Naudts, Jan [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: Texto

TextoEditor: London : Springer London, 2011Descripción: XI, 201 p. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9780857293558Tema(s): Mathematics | Mathematical physics | Thermodynamics | Mathematics | Mathematics, general | Statistical Physics, Dynamical Systems and Complexity | Mathematical Methods in Physics | ThermodynamicsFormatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD: 510 Clasificación LoC:QA1-939Recursos en línea: Libro electrónico Texto

Contenidos:

Parameter estimation -- Statistical Models -- Thermodynamic Equilibrium -- The Microcanonical Ensemble -- Hyperensembles -- The Mean Field Approximation -- q-Deformed Distributions -- Tsallis’ Thermostatistics -- Changes of Scale -- General deformations -- General Entropies.

En: Springer eBooksResumen: The domain of non-extensive thermostatistics has been subject to intensive research over the past twenty years and has matured significantly. Generalised Thermostatistics cuts through the traditionalism of many statistical physics texts by offering a fresh perspective and seeking to remove elements of doubt and confusion surrounding the area. The book is divided into two parts - the first covering topics from conventional statistical physics, whilst adopting the perspective that statistical physics is statistics applied to physics. The second developing the formalism of non-extensive thermostatistics, of which the central role is played by the notion of a deformed exponential family of probability distributions. Presented in a clear, consistent, and deductive manner, the book focuses on theory, part of which is developed by the author himself, but also provides a number of references towards application-based texts. Written by a leading contributor in the field, this book will provide a useful tool for learning about recent developments in generalized versions of statistical mechanics and thermodynamics, especially with respect to self-study. Written for researchers in theoretical physics, mathematics and statistical mechanics, as well as graduates of physics, mathematics or engineering. A prerequisite knowledge of elementary notions of statistical physics and a substantial mathematical background are required.

Existencias ( 1 )
Notas de título ( 3 )

Existencias
Tipo de ítem	Biblioteca actual	Colección	Signatura	Copia número	Estado	Fecha de vencimiento	Código de barras
Libro Electrónico	Biblioteca Electrónica	Colección de Libros Electrónicos	QA1 -939 (Browse shelf(Abre debajo))	1	No para préstamo		370551-2001

The domain of non-extensive thermostatistics has been subject to intensive research over the past twenty years and has matured significantly. Generalised Thermostatistics cuts through the traditionalism of many statistical physics texts by offering a fresh perspective and seeking to remove elements of doubt and confusion surrounding the area. The book is divided into two parts - the first covering topics from conventional statistical physics, whilst adopting the perspective that statistical physics is statistics applied to physics. The second developing the formalism of non-extensive thermostatistics, of which the central role is played by the notion of a deformed exponential family of probability distributions. Presented in a clear, consistent, and deductive manner, the book focuses on theory, part of which is developed by the author himself, but also provides a number of references towards application-based texts. Written by a leading contributor in the field, this book will provide a useful tool for learning about recent developments in generalized versions of statistical mechanics and thermodynamics, especially with respect to self-study. Written for researchers in theoretical physics, mathematics and statistical mechanics, as well as graduates of physics, mathematics or engineering. A prerequisite knowledge of elementary notions of statistical physics and a substantial mathematical background are required.