Simulation methods for advanced scientific computing [electronic resource]
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The objective of the project was to create effective new algorithms for solving N-body problems by computer simulation. The authors concentrated on deve...
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Online Access |
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Format: | Government Document Electronic eBook |
Language: | English |
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Los Alamos, N.M. : Oak Ridge, Tenn. :
Los Alamos National Laboratory ; distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy,
1998.
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245 | 0 | 0 | |a Simulation methods for advanced scientific computing |h [electronic resource] |
260 | |a Los Alamos, N.M. : |b Los Alamos National Laboratory ; |a Oak Ridge, Tenn. : |b distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, |c 1998. | ||
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500 | |a 11/01/1998. | ||
500 | |a "LA-UR--98-2094" | ||
500 | |a "DE99000816" | ||
500 | |a Carlson, J.A.; Forster, R.A.; Booth, T.E. | ||
500 | |a USDOE Assistant Secretary for Management and Administration, Washington, DC (US) | ||
520 | 3 | |a This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The objective of the project was to create effective new algorithms for solving N-body problems by computer simulation. The authors concentrated on developing advanced classical and quantum Monte Carlo techniques. For simulations of phase transitions in classical systems, they produced a framework generalizing the famous Swendsen-Wang cluster algorithms for Ising and Potts models. For spin-glass-like problems, they demonstrated the effectiveness of an extension of the multicanonical method for the two-dimensional, random bond Ising model. For quantum mechanical systems, they generated a new method to compute the ground-state energy of systems of interacting electrons. They also improved methods to compute excited states when the diffusion quantum Monte Carlo method is used and to compute longer time dynamics when the stationary phase quantum Monte Carlo method is used. | |
536 | |b W-7405-ENG-36. | ||
650 | 7 | |a Algorithms. |2 local. | |
650 | 7 | |a Computerized Simulation. |2 local. | |
650 | 7 | |a Diffusion. |2 local. | |
650 | 7 | |a Electrons. |2 local. | |
650 | 7 | |a Excited States. |2 local. | |
650 | 7 | |a Ising Model. |2 local. | |
650 | 7 | |a Lanl. |2 local. | |
650 | 7 | |a Monte Carlo Method. |2 local. | |
650 | 7 | |a Simulation. |2 local. | |
650 | 7 | |a Materials Science. |2 edbsc. | |
650 | 7 | |a General And Miscellaneous//mathematics, Computing, And Information Science. |2 edbsc. | |
710 | 2 | |a Los Alamos National Laboratory. |4 res. | |
710 | 2 | |a United States. |b Department of Energy. |b Office of Scientific and Technical Information. |4 dst. | |
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