Strongly Correlated Systems
Subtitle: Numerical Methods
By: edited by Adolfo Avella, Ferdinando Mancini
Contributors: Mancini, Ferdinando; SpringerLink (Online service)
Series: Springer Series in Solid-State Sciences -- 176
Publisher: Springer Berlin Heidelberg; Imprint: Springer
Published: 2013
Place of publication: Berlin, Heidelberg
Language: eng
Format: [electronic resource] :
Number of pages: 325
ISBN-13: 9783642351068
Subjects: Spectroscopy and Microscopy; Solid state physics; Mathematical physics; Physics; Mathematical Methods in Physics
Description: This volume presents, for the very first time, an exhaustive collection of those modern numerical methods specifically tailored for the analysis of Strongly Correlated Systems. Many novel materials, with functional properties emerging from macroscopic quantum behaviors at the frontier of modern research in physics, chemistry and material science, belong to this class of systems. Any technique is presented in great detail by its own inventor or by one of the world-wide recognized main contributors. The exposition has a clear pedagogical cut and fully reports on the most relevant case study where the specific technique showed to be very successful in describing and enlightening the puzzling physics of a particular strongly correlated system. The book is intended for advanced graduate students and post-docs in the field as textbook and/or main reference, but also for other researchers in the field who appreciate consulting a single, but comprehensive, source or wishes to get acquainted, in a as painless as possible way, with the working details of a specific technique.
Table of contents: title: Lanczos and Finite Temperature Lanczos; title: Density Matrix Renormalization Group; title: Variational Monte Carlo (VMC); title: Gaussian Quantum Monte Carlo; title: Auxiliary Field Monte Carlo; title: Stochastic Series Expansion (SSE); title: Worm Algorithm; title: Loop Algorithm; title: Continuous Time Quantum Monte Carlo (CTQMC); title: Hirsch - Fye Quantum Monte Carlo (HFQMC).