Mathematical Foundations of Classical Statistical Mechanics

Considers the problem of investigation of systems of infinite number of particles. The text discusses the equilibrium and non-equilibrium states of infinite classical statistical systems defined in terms of stationary and nonstationary solutions to the Bogolyubov equations for the sequences of correlation functions in the thermodynamic limit.

List of contents

Problem for the BBGKY Hierarchy. Equilibrium States. Canonical Ensemble. Equilibrium States. Grand Canonical Ensemble. Thermodynamic Limit for Non-equilibrium Systems. Appendix 1: Stationary Solutions of the BBGKY Hierarchy of Equations. Appendix 2: Existence of the Hamiltonian Dynamics of Infinitely Many Particles. References. Index.

Summary

Considers the problem of investigation of systems of infinite number of particles. The text discusses the equilibrium and non-equilibrium states of infinite classical statistical systems defined in terms of stationary and nonstationary solutions to the Bogolyubov equations for the sequences of correlation functions in the thermodynamic limit.

Additional text

"[A] good reference in which many classical and profound results of both equilibrium and nonequilibrium statistical mechanics are collected and presented in a unified way." - SIAM Review, Vol. 46, No. 1

Product details

• Authors: V. I. Gerasimenko, V.I. Gerasimenko, V.I. (Kiev Institute of Mathematics Gerasimenko, P V Malyshev, P. V. Malyshev, D. Ya Petrina, D.Ya. Petrina, D.Ya. (National Academy of Sciences of Ukraine) Petrina
• Publisher: Taylor and Francis
• Languages: English
• Product format: Hardback
• Released: 31.12.2022
• EAN: 9780415273541
• ISBN: 978-0-415-27354-1
• No. of pages: 352
• Weight: 657 g
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Basic principles; Wahrscheinlichkeitsrechnung und Statistik, MATHEMATICS / Probability & Statistics / General, Klassische Mechanik, MATHEMATICS / History & Philosophy, SCIENCE / Mechanics / General, Classical mechanics, Probability & statistics, Mathematical foundations, Probability and statistics