Image from Google Jackets

Generalised Thermostatistics [electronic resource] / by Jan Naudts.

Por: Colaborador(es): Tipo de material: TextoTextoEditor: London : Springer London, 2011Descripción: X, 201p. 28 illus. online resourceTipo de contenido:
  • text
Tipo de medio:
  • computer
Tipo de soporte:
  • online resource
ISBN:
  • 9780857293558
  • 99780857293558
Tema(s): Formatos físicos adicionales: Printed edition:: Sin títuloClasificación CDD:
  • 510 23
Recursos en línea:
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.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Collection Call number Status Date due Barcode
Libros electrónicos Libros electrónicos CICY Libro electrónico Libro electrónico 510 (Browse shelf(Opens below)) Available

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.

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.

There are no comments on this title.

to post a comment.