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Generalised Thermostatistics / by Jan Naudts
Edition | 1st ed. 2011. |
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Publisher | London : Springer London : Imprint: Springer |
Year | 2011 |
Language | English |
Size | XI, 201 p : online resource |
Authors | *Naudts, Jan author SpringerLink (Online service) |
Subjects | LCSH:Mathematics LCSH:System theory LCSH:Mathematical physics LCSH:Thermodynamics FREE:Mathematics FREE:Complex Systems FREE:Mathematical Methods in Physics FREE:Thermodynamics FREE:Theoretical, Mathematical and Computational Physics |
Notes | 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 HTTP:URL=https://doi.org/10.1007/978-0-85729-355-8 |
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E-Book | Location | Media type | Volume | Call No. | Status | Reserve | Comments | ISBN | Printed | Restriction | Designated Book | Barcode No. |
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E-Book | オンライン | 電子ブック |
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Springer eBooks | 9780857293558 |
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EB00231245 |
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