By Shigenori Tanaka, Stuart M. Rothstein, and William A. Lester, Jr. (Eds.)
content material: PREFACE ; I. ACCURACY AND PRECISION OF QUANTUM MONTE CARLO CALCULATIONS ; 1. CORRELATED SAMPLING FOR power modifications IN DIFFUSION QUANTUM MONTE CARLO ; JAMES B. ANDERSON ; 2. inhabitants keep watch over BIAS WITH functions TO PARALLEL DIFFUSION MONTE CARLO ; JARON T. KROGEL AND DAVID M. CEPERLEY ; three. ENHANCEMENT OF SAMPLING potency IN AB INITIO MONTE CARLO SIMULATIONS utilizing AN AUXILIARY power power floor ; AKIRA NAKAYAMA AND TETSUYA TAKETSUGU ; four. fresh leads to the precise therapy OF FERMIONS AT 0 AND FINITE TEMPERATURE ; NORM M. TUBMAN, JONATHAN L. DUBOIS, AND BERNI J. ALDER ; II. alternate NODES AND SIMULATED ELECTRON DISTRIBUTION ; five. QUANTUM MONTE CARLO dealing with THE HARTREE-FOCK SYMMETRY predicament: THE CASE OF HYDROGEN jewelry ; PETER REINHARDT, JULIEN TOULOUSE, ROLAND ASSARAF, C. J. UMRIGAR, AND PHILIP E. HOGGAN ; 6. unmarried ELECTRON DENSITIES FROM QUANTUM MONTE CARLO SIMULATIONS ; ARNE LUCHOW AND RENE PETZ ; 7. MANY-BODY NODAL HYPERSURFACE AND area AVERAGES FOR CORRELATED WAVE features ; SHUMING HU, KEVIN RASCH, AND LUBOS MITAS ; III. huge AND EXPERIMENTALLY tough structures ; eight. A QUANTUM MONTE CARLO learn OF the floor country CHROMIUM DIMER ; KENTA HONGO AND RYO MAEZONO ; nine. A BENCHMARK QUANTUM MONTE CARLO research OF MOLECULAR CRYSTAL POLYMORPHISM: A difficult CASE FOR DENSITY-FUNCTIONAL thought ; MARK A. WATSON, KENTA HONGO, TOSHIAKI IITAKA, AND ALAN ASPURU-GUZIK ; 10. QUANTUM MONTE CARLO IN PRESENCE OF SPIN-ORBIT interplay ; A. AMBROSETTI, F. PEDERIVA, E. LIPPARINI, AND L. MITAS ; eleven. HIGH-ENERGY ELECTRON SCATTERING FROM chosen DIATOMICS utilizing MONTE CARLO equipment ; S. A. ALEXANDER, SUMITA DATTA, AND R. L. COLDWELL ; 12. learning homes OF FLOPPY MOLECULES utilizing DIFFUSION MONTE CARLO ; ANNE B. MCCOY, CHARLOTTE E. HINKLE, AND ANDREW S. PETIT ; thirteen. QUANTUM MONTE CARLO examine OF THE BINDING OF A POSITRON TO POLAR MOLECULES ; YUKIUMI KITA AND MASANORI TACHIKAWA ; IV. HYBRID MOLECULAR MECHANICS/DYNAMICS AND MONTE CARLO ALGORITHMS ; 14. MOLECULAR DYNAMICS AND HYBRID MONTE CARLO ALGORITHMS FOR THE VARIATIONAL direction imperative WITH A FOURTH-ORDER PROPAGATOR ; SHINICHI MIURA ; 15. AB INITIO direction quintessential MOLECULAR DYNAMICS AND MONTE CARLO SIMULATIONS FOR WATER TRIMER AND OLIGOPEPTIDE ; TAKATOSHI FUJITA, MASA-AKI KUSA, TAKAYUKI FUJIWARA, YUJI MOCHIZUKI, AND ; SHIGENORI TANAKA ; sixteen. past A unmarried SOLVATED ELECTRON: HYBRID QUANTUM MONTE CARLO AND MOLECULAR MECHANICS method ; D. YU. ZUBAREV AND W. A. LESTER, JR. ; V. earlier AND way forward for QUANTUM MONTE CARLO ; 17. QUANTUM MONTE CARLO AND ZDENEK HERMAN'S ENCHANTED PSILAND ; JAMES B. ANDERSON ; EDITORS' BIOGRAPHIES ; INDEXES ; writer INDEX ; topic INDEX
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Additional info for Advances in Quantum Monte Carlo
Ch003 diagonal matrix whose elements are the basis functions at Z(i) and given by The interpolated potential for a given configuration Z is obtained by solving the normal equation Eq. (6), which is implemented by using the singular value decomposition (SVD). In this work, we use polynomials up to the second order of each component of Z as the basis functions. The weight function of the form is employed throughout this study. Path Integral Monte Carlo Method The imaginary time path integral formulation of quantum statistics provides a conceptual and computationally practical route for studying the quantum nature of systems at thermal equilibrium (15).
B 2004, 69, 085116. ; ACS Symposium Series; American Chemical Society: Washington, DC, 2012. jp An approach is developed to enhance sampling for ab initio Monte Carlo and ab initio path integral Monte Carlo calculations of molecular clusters by utilizing an approximate potential as a guide to move in the configuration space more efficiently. Two methods are introduced in this chapter, where the first one utilizes the interpolated potential energy surface obtained by the moving least-squares method, and the second one employs the molecular dynamics scheme to update the system configuration in the context of hybrid Monte Carlo method in which potential energy gradients are evaluated by computationally less expensive ab initio electronic structure methods.
In some cases this could lead to less efficient sampling than the conventional MC method. We briefly describe the AP method for a canonical ensemble of classical system, whose probability density is given as where is the reciprocal temperature in units of the Boltzmann constant. Here R is the configuration of the system and Z is the partition function. The extension to quantum systems using imaginary time path integral formulation, which will be described below, is straightforward. The procedure for the AP method is as follows.
Advances in Quantum Monte Carlo by Shigenori Tanaka, Stuart M. Rothstein, and William A. Lester, Jr. (Eds.)