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Computational statistical physics / Lucas Bo?ttcher, Hans J. Herrmann.

By: Contributor(s): Material type: TextTextLanguage: English Cambridge : Cambridge University Press, 2021Description: 1 online resource (xiii, 257 pages) : digital, PDF file(s)Content type:
  • text
Media type:
Carrier type:
  • online resource
ISBN:
  • 9781108882316 (ebook)
Subject(s): Additional physical formats: No titleDDC classification:
  • 530.13
LOC classification:
  • QC174.8 .B68 2021
Online resources: Summary: Providing a detailed and pedagogical account of the rapidly-growing field of computational statistical physics, this book covers both the theoretical foundations of equilibrium and non-equilibrium statistical physics, and also modern, computational applications such as percolation, random walks, magnetic systems, machine learning dynamics, and spreading processes on complex networks. A detailed discussion of molecular dynamics simulations is also included, a topic of great importance in biophysics and physical chemistry. The accessible and self-contained approach adopted by the authors makes this book suitable for teaching courses at graduate level, and numerous worked examples and end of chapter problems allow students to test their progress and understanding.
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Title from publisher's bibliographic system (viewed on 24 Aug 2021).

Providing a detailed and pedagogical account of the rapidly-growing field of computational statistical physics, this book covers both the theoretical foundations of equilibrium and non-equilibrium statistical physics, and also modern, computational applications such as percolation, random walks, magnetic systems, machine learning dynamics, and spreading processes on complex networks. A detailed discussion of molecular dynamics simulations is also included, a topic of great importance in biophysics and physical chemistry. The accessible and self-contained approach adopted by the authors makes this book suitable for teaching courses at graduate level, and numerous worked examples and end of chapter problems allow students to test their progress and understanding.

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