Generalised Thermostatistics
Generalised Thermostatistics by Jan Naudts, published by Springer London on February 12, 2011, is a comprehensive exploration of non-extensive thermostatistics, a field that has seen significant research advancements over the past two decades. This edition, comprising 201 pages, presents a fresh perspective on statistical physics, aiming to clarify common uncertainties associated with the subject.
The book is structured in two parts: the first addresses conventional statistical physics while emphasizing the application of statistics to physical concepts, and the second delves into the formalism of non-extensive thermostatistics, highlighting the deformed exponential family of probability distributions. Written in a clear and deductive style, Generalised Thermostatistics focuses on theoretical frameworks, supplemented by references to application-based texts. It serves as a valuable resource for researchers in theoretical physics, mathematics, and statistical mechanics, as well as graduate students in related fields, requiring a foundational understanding of statistical physics and a strong mathematical background.
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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.
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