Monte Carlo Simulation in Statistical Physics

Kurt Binder received his Ph.D. at the Technical University of Vienna in1969 with a thesis on Monte Carlo simulations of Ising and Heisenberg magnets, and since then he has pioneered the development of Monte Carlo simulation methods in statistical physics. From 1969 to 1974, Kurt Binder worked at the Technical University in Munich, interrupted by a period as IBM postdoctoral fellow in Zurich in 1972-73. After a stay at Bell Laboratories, Murray Hill, NJ (1974), and a first appointment as Professor of Theoretical Physics at the University of Saarbrücken back in Germany (1974-1977), he held a joint appointment as Full Professor at the University of Cologne and as one of the Directors of the Institute of Solid State Research at Jülich (1977-1983). He has held his present position as Professor of Theoretical Physics at the University of Mainz, Germany, since 1983, and since 1989 he has also been an external member of the Max Planck Institute for Polymer Research in Mainz. Kurt Binder has written more than 1100 research publications and edited 5 books on computer simulations. He received the German Physical Society's Max Planck Medal in 1993. He is an Editorial Board member of several journals and has served as Chairman of the IUPAP Commission on Statistical Physics. In 2001 he was awarded the Berni Alder CECAM prize by the European Physical Society. In 2007 he received the Boltzmann Medal from the International Union of Pure and Applied Physics and an honorary Ph.D. degree in Chemistry from the Marie-Curie-Sklodowska University (Lublin, Poland), and was named one of the first Gutenberg Fellows at the University of Mainz. In 2009 he was the winner of the Lennard-Jones Prize awarded by the Statistical Mechanics and Thermodynamics Group of the Royal Society of Chemistry in recognition of his outstanding contribution to the field of thermodynamics. He retired from office in 2012, but is still active in research. From 2011 to 2017 he has been the Chairman of the Scientific Council of the John von Neumann Institute for Computing at the Supercomputer Centre Jülich. Dieter Heermann studied Computer Science, Mathematics and Physics. He received his Ph.D. at Boston University (USA) with the work "Metastability in Ising Models". From 1983 to 1987 he worked as a postdoctoral fellow and as an external member at the Institute of Solid State Physics at the Forschungszentrum Jülich. From 1984 to 1987 he was Assistant Professor at the University of Mainz, and in 1988 he was appointed as Professor at the University of Wuppertal. In 1989 he moved to the Institute for Theoretical Physics at Heidelberg University. There he joined the efforts to establish the newly formed interdisciplinary research center for scientific computing (IWR) and participated in many initiatives of the center, among them being the Vice-Chairman for the Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences. From 2008 to 2014 he also served as an Adjunct Professor at The Jackson Laboratory, Maine (USA) and as Visiting professor at the Chinese Academy of Sciences in 2011. Since 2013 he serves as Vice-President of Heidelberg University. He currently is Specialty Chief Editor Biophysics for the open access journal Frontiers.

Introduction: Purpose and Scope of this Volume, and Some General Comments.- Theoretical Foundations of the Monte Carlo Method and Its Applications in Statistical Physics.- Guide to Practical Work with the Monte Carlo Method.- Some Important Developments of the Monte Carlo Methodology.- Quantum Monte Carlo Simulation: An Introduction.- Monte Carlo Methods for the Sampling of Free Energy Landscapes.- Special Monte Carlo Algorithms.- Finite Size Scaling Tools for the Study of Interfacial Phenomena and Wetting.

"This will be an appropriate text for advanced graduate students, scientist and researchers who are interested in Monte Carlo methods in statistical mechanics." (Maria Christina Mariani, zbMATH 1428.82003, 2020)

“This will be an appropriate text for advanced graduate students, scientist and researchers who are interested in Monte Carlo methods in statistical mechanics.” (Maria Christina Mariani, zbMATH 1428.82003, 2020)