James B. Anderson

Quantum Monte Carlo
Origins, Development, Applications

Monte Carlo methods are a class of computational algorithms for simulating the behavior of a wide range of various physical and mathematical systems (with many variables). Their utility has increased with general availability of fast computers, and new applications are continually forthcoming. The basic concepts of Monte Carlo are both simple and straightforward and rooted in statistics and probability theory, their defining characteristic being that the methodology relies on random or pseudo-random sequences of numbers. It is a technique of numerical analysis based on the approximate solution of a problem using repeated sampling experiments and observing the proportion of times a given property is satisfied.
The term Monte Carlo was first used to describe calculational methods based on chance in the 1940s, but the methods themselves preceded the term by as much as a century. Quantum Monte Carlo (QMC) first appeared in 1982 and similarly was preceded by development of the related calculational methodology. The success of QMC methods over the past few decades has been remarkable, and this book will clearly demonstrate that success in its discussion of applications. For isolated molecules, the basic material of chemistry, QMC methods have produced exact solutions of the Schroedinger equation for very small systems and the most accurate solutions available for very large systems. The range of applications is impressive: folding of protein molecules, interactions in liquids, structure modeling in crystals and enzymes, quantum dots, designing heat shields and aerodynamic forms, architecture, design, business and economics, and even cinema and video games (3D modeling).

This book takes a similar approach to Henry Schaefers classic book Quantum Chemistry (OUP, 1984 now a Dover edition), collecting summaries of some of the most important papers in the quantum Monte Carlo literature, tying everything together with analysis and discussion of applications. Quantum Monte Carlo is a reference book for quantum Monte Carlo applications, belonging near the desk of every quantum chemist, physicist, and a wide range of scientists and engineers across many disciplines, destined to become a classic.

176 pages; 5-1/2 x 8-1/4;
ISBN13: 978-0-19-531010-8
ISBN10: 0-19-531010-1


Dominic D. Joyce

Riemannian holonomy groups and calibrated geometry

(Hardback)
ISBN-10: 0-19-921560-X
ISBN-13: 978-0-19-921560-7
Estimated publication date: April 2007
320 pages, 234x156 mm
Series: Oxford Graduate Texts in Mathematics number 12

Description

Accessible to graduate students in both Mathematics and Physics
Surveys current research and states open problems, particularly in calibrated geometry
Thorough coverage, major proofs such as the Calabi conjecture are provided in full
Extensive, up-to-date bibliography

This graduate level text covers an exciting and active area of research at the crossroads of several different fields in Mathematics and Physics. In Mathematics it involves Differential Geometry, Complex Algebraic Geometry, Symplectic Geometry, and in Physics String Theory and Mirror Symmetry. Drawing extensively on the author's previous work, the text explains the advanced mathematics involved simply and clearly to both mathematicians and physicists. Starting with the basic geometry of connections, curvature, complex and K?hler structures suitable for beginning graduate students, the text covers seminal results such as Yau's proof of the Calabi Conjecture, and takes the reader all the way to the frontiers of current research in calibrated geometry, giving many open problems.

Readership: Graduates and researchers in Mathematics and Physics

Contents

Preface
1. Background material
2. Introduction to connections, curvature and holonomy groups
3. Riemannian holonomy groups
4. Calibrated geometry
5. K?hler manifolds
6. The Calabi Conjecture
7. Calabi-Yau manifolds
8. Special Lagrangian geometry
9. Mirror Symmetry and the SYZ Conjecture
10. Hyperk?hler and quaternionic K?hler manifolds
11. The exceptional holonomy groups
12. Associative, coassociative and Cayley submanifolds
References
Index


Edited by Jean Bourgain, Carlos E. Kenig & S. Klainerman

Mathematical Aspects of Nonlinear Dispersive Equations

Paper | May 2007 |ISBN13: 978-0-691-12955-6
Cloth | April 2007 | ISBN13: 978-0-691-12860-3
296 pp. | 6 x 9

This collection of new and original papers on mathematical aspects of nonlinear dispersive equations includes both expository and technical papers that reflect a number of recent advances in the field. The expository papers describe the state of the art and research directions. The technical papers concentrate on a specific problem and the related analysis and are addressed to active researchers.

The book deals with many topics that have been the focus of intensive research and, in several cases, significant progress in recent years, including hyperbolic conservation laws, Schrodinger operators, nonlinear Schrodinger and wave equations, and the Euler and Navier-Stokes equations.

Jean Bourgain is Professor of Mathematics at the Institute for Advanced Study in Princeton. In 1994, he won the Fields Medal. He is the author of Green's Function Estimates for Lattice Schrodinger Operators and Applications (Princeton). Carlos E. Kenig is Professor of Mathematics at the University of Chicago. He is a fellow of the American Academy of Arts and Sciences and the author of Harmonic Analysis Techniques for Second Order Elliptic Boundary Value Problems. S. Klainerman is Professor of Mathematics at Princeton University. He is a MacArthur Fellow and Bocher Prize recipient. He is the coauthor of The Global Nonlinear Stability of the Minkowski Space (Princeton).

Another Princeton book by Jean Bourgain:

Green's Function Estimates for Lattice Schrodinger Operators and Applications. (AM-158).
Series:

Qi Li & Jeffrey Scott Racine

Nonparametric Econometrics:
Theory and Practice

Cloth | 2007 | ISBN13: 978-0-691-12161-1
768 pp. | 7 x 10 | 23 line illus. 17 tables.

Until now, students and researchers in nonparametric and semiparametric statistics and econometrics have had to turn to the latest journal articles to keep pace with these emerging methods of economic analysis. Nonparametric Econometrics fills a major gap by gathering together the most up-to-date theory and techniques and presenting them in a remarkably straightforward and accessible format. The empirical tests, data, and exercises included in this textbook help make it the ideal introduction for graduate students and an indispensable resource for researchers.

Nonparametric and semiparametric methods have attracted a great deal of attention from statisticians in recent decades. While the majority of existing books on the subject operate from the presumption that the underlying data is strictly continuous in nature, more often than not social scientists deal with categorical data--nominal and ordinal--in applied settings. The conventional nonparametric approach to dealing with the presence of discrete variables is acknowledged to be unsatisfactory.

This book is tailored to the needs of applied econometricians and social scientists. Qi Li and Jeffrey Racine emphasize nonparametric techniques suited to the rich array of data types--continuous, nominal, and ordinal--within one coherent framework. They also emphasize the properties of nonparametric estimators in the presence of potentially irrelevant variables.

Nonparametric Econometrics covers all the material necessary to understand and apply nonparametric methods for real-world problems.

Qi Li is Professor of Economics and Hugh Roy Cullen Professor in Liberal Arts at Texas A&M University. Jeffrey Scott Racine is Professor of Economics, Professor in the Graduate Program in Statistics, and Senator William McMaster Chair in Econometrics at McMaster University.

Endorsements:

"Nonparametric Econometrics by Li and Racine is a must for any serious econometrician or statistician who is working on cutting-edge problems. The theoretical treatment of nonparametric methods is remarkably complete in its coverage of mainstream and relatively arcane topics. I particularly like Li and Racine's general treatment of continuous and discrete regressors and of specification testing, topics that I have not seen handled in such a comprehensive fashion. I will certainly use this in my graduate econometrics courses and in conducting my own research."--Robin Sickles, Rice University

"Very few studies have tried to apply the nonparametric techniques to analyze real data. The lack of applications of those techniques is perhaps attributable to the lack of a good textbook that explains intuitively how and why those techniques work. This book by Li and Racine serves both applied researchers and graduate students. It is written in plain language so that it can be understood by anyone with basic econometrics but zero knowledge of nonparametric methods. And it contains enough specifics that clearly spell out steps to implement those methods."--Chunrong Ai, University of Florida

"This book represents a very significant contribution to the field of econometrics. It provides an extremely thorough coverage of our knowledge in the area of nonparametric and semiparametric methods as they apply to economic models and economic data. And it makes accessible, for the first time, a body of relatively new material relating to discrete and 'mixed' data. There is a good balance of theoretical material and applications. Apart from serving as a superb teaching text in graduate-level courses where the students have a strong econometrics/statistics preparation, I believe this book will become a must-have reference resource for many researchers."--David E. Giles, University of Victoria

contents


Elias Kiritsis

String Theory in a Nutshell

Cloth | May 2007 | ISBN13: 978-0-691-12230-4
640 pp. | 7 x 10 | 18 halftones. 44 line illus. 7 tables.

This book is the essential new introduction to modern string theory, by one of the world's authorities on the subject. Concise, clearly presented, and up-to-date, String Theory in a Nutshell brings together the best understood and most important aspects of a theory that has been evolving since the early 1980s. A core model of physics that substitutes one-dimensional extended "strings" for zero-dimensional point-like particles (as in quantum field theory), string theory has been the leading candidate for a theory that would successfully unify all fundamental forces of nature, including gravity.

Starting with the basic definitions of the theory, Elias Kiritsis guides readers through classic and modern topics. In particular, he treats perturbative string theory and its Conformal Field Theory (CFT) tools in detail while also developing nonperturbative aspects and exploring the unity of string interactions. He presents recent topics including black holes, their microscopic entropy, and the AdS/CFT correspondence. He also describes matrix model tools for string theory. In all, the book contains nearly five hundred exercises for the graduate-level student, and works as a self-contained and detailed guide to the literature.

String Theory in a Nutshell is the staple one-volume reference on the subject not only for students and researchers of theoretical high-energy physics, but also for mathematicians and physicists specializing in theoretical cosmology and QCD.

Elias Kiritsis is Directeur de Recherche at the CNRS, affiliated with the Ecole Polytechnique in Paris, and Professor of Physics at the University of Crete.

Endorsements:

"An excellent reference for any graduate student interested in string theory. Kiritsis succinctly describes many of the recent developments that are necessary background to current research. Topics covered include black holes in string theory, holography, various dualities among string theories, and dualities connecting string theory to gauge theories. The basic frameworks for connecting string theory to four-dimensional physics are also explained."--Juan Maldacena, Institute for Advanced Study

"This very well-written book, which builds on the fundamentals and provides an excellent introduction to the state of the art in string theory, will be quite useful to students and to researchers acquainting themselves with this exciting field. It concisely lays out the successes of string theory to date and the challenges that await. I have no doubt that the topics described herein will remain at the heart of the theory even when our understanding of its dynamics and its role in describing nature improve."--David Kutasov, University of Chicago

"There is a definite need for a short speedy introduction to modern string theory. Kiritsis beautifully fill this gap--including all essential areas, but remaining relatively concise, so that a beginning student can work through the entire text."--Andrew Strominger, Harvard University

"String theory textbooks are found on the bookshelves of not only those theoretical physicists who call themselves string theorists, but also others, and this book will appeal especially to this broader category of readers. More universal in its coverage than are comparable texts, it seeks to explain virtually all the issues whose knowledge becomes more or less necessary for every researcher in the field. Indeed, it squeezes all its material into less than 600 pages of well-defined, short sentences with a clear technical content--a nearly complete discussion of the subject that will be really useful to many experts and future experts."--Lubos Motl, Harvard University

K. K. Tung

Topics in Mathematical Modeling

Cloth | May 2007 | ISBN13: 978-0-691-11642-6
336 pp. | 7 x 10 | 31 halftones. 52 line illus. 5 tables.

Topics in Mathematical Modeling is an introductory textbook on mathematical modeling. The book teaches how simple mathematics can help formulate and solve real problems of current research interest in a wide range of fields, including biology, ecology, computer science, geophysics, engineering, and the social sciences. Yet the prerequisites are minimal: calculus and elementary differential equations. Among the many topics addressed are HIV; plant phyllotaxis; global warming; the World Wide Web; plant and animal vascular networks; social networks; chaos and fractals; marriage and divorce; and El Nino. Traditional modeling topics such as predator-prey interaction, harvesting, and wars of attrition are also included. Most chapters begin with the history of a problem, follow with a demonstration of how it can be modeled using various mathematical tools, and close with a discussion of its remaining unsolved aspects.

Designed for a one-semester course, the book progresses from problems that can be solved with relatively simple mathematics to ones that require more sophisticated methods. The math techniques are taught as needed to solve the problem being addressed, and each chapter is designed to be largely independent to give teachers flexibility.

The book, which can be used as an overview and introduction to applied mathematics, is particularly suitable for sophomore, junior, and senior students in math, science, and engineering.

K. K. Tung is Professor and Chairman of the Department of Applied Mathematics at the University of Washington. He is the author or coauthor of more than eighty research papers in atmospheric sciences and applied mathematics, and editor or chief editor of two journals in these fields.

Endorsements:

"This book has a refreshing style that should appeal to undergraduates. Indeed, the author has produced a textbook that might well achieve his goal of teaching applied mathematics without those being taught noticing!"--Andrew Wathen, University of Oxford

"With courses in mathematical modeling getting ever more popular, this book will make a valuable addition to the subject. It deals with topics that should be appealing even to students not majoring in math or science, and the level of mathematical sophistication is carefully increased throughout the book."--Henrik Kalisch, University of Bergen, Norway