Kirjojen hintavertailu – 12 903 735 kirjaa ja 27 kauppaa

Kirjailija

Jian-sheng Wang

Kirjat ja teokset yhdessä paikassa: 2 kirjaa, julkaisuja vuosilta 2005–2021, suosituimpiin kuuluu Markov Chain Monte Carlo: Innovations And Applications. Vertaile teosten hintoja ja tarkista saatavuus suomalaisista kirjakaupoista.

2 kirjaa

Kirjojen julkaisuvuodet: 2005–2021.

Advanced Statistical Mechanics

Advanced Statistical Mechanics

Jian-sheng Wang

World Scientific Publishing Co Pte Ltd
2021
sidottu
This short textbook covers roughly 13 weeks of lectures on advanced statistical mechanics at the graduate level. It starts with an elementary introduction to the theory of ensembles from classical mechanics, and then goes on to quantum statistical mechanics with density matrix. These topics are covered concisely and briefly. The advanced topics cover the mean-field theory for phase transitions, the Ising models and their exact solutions, and critical phenomena and their scaling theory. The mean-field theories are discussed thoroughly with several different perspectives — focusing on a single degree, or using Feynman-Jensen-Bogoliubov inequality, cavity method, or Landau theory. The renormalization group theory is mentioned only briefly. As examples of computational and numerical approach, there is a chapter on Monte Carlo method including the cluster algorithms. The second half of the book studies nonequilibrium statistical mechanics, which includes the Brownian motion, the Langevin and Fokker-Planck equations, Boltzmann equation, linear response theory, and the Jarzynski equality. The book ends with a brief discussion of irreversibility. The topics are supplemented by problem sets (with partial answers) and supplementary readings up to the current research, such as heat transport with a Fokker-Planck approach.
Markov Chain Monte Carlo: Innovations And Applications

Markov Chain Monte Carlo: Innovations And Applications

Wilfrid S Kendall; Faming Liang; Jian-sheng Wang

World Scientific Publishing Co Pte Ltd
2005
sidottu
Markov Chain Monte Carlo (MCMC) originated in statistical physics, but has spilled over into various application areas, leading to a corresponding variety of techniques and methods. That variety stimulates new ideas and developments from many different places, and there is much to be gained from cross-fertilization. This book presents five expository essays by leaders in the field, drawing from perspectives in physics, statistics and genetics, and showing how different aspects of MCMC come to the fore in different contexts. The essays derive from tutorial lectures at an interdisciplinary program at the Institute for Mathematical Sciences, Singapore, which exploited the exciting ways in which MCMC spreads across different disciplines.