scholarly journals A new approach to Monte Carlo simulations in statistical physics

2004 ◽  
Vol 34 (2a) ◽  
Author(s):  
D. P. Landau ◽  
F. Wang
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Statistical Physics ◽  
New Approach

A new approach to Monte Carlo simulations in statistical physics: Wang-Landau sampling

2004 ◽  
Vol 72 (10) ◽  
pp. 1294-1302 ◽  
Author(s):  
D. P. Landau ◽  
Shan-Ho Tsai ◽  
M. Exler
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Statistical Physics ◽  
New Approach

Improved estimation is a prerequisite for successful terminal guidance

2005 ◽  
Vol 219 (2) ◽  
pp. 145-156 ◽  
Author(s):  
J Shinar ◽  
V Turetsky
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Estimation Errors ◽  
New Approach ◽  
Target Acceleration ◽  
The Future ◽  
New Ideas ◽  
Estimation System ◽  
Terminal Guidance

Successful interception of manoeuvring anti-surface missiles that are expected in the future can be achieved only if the estimation errors against manoeuvring targets can be minimized. The paper raises new ideas for an improved estimation concept by separating the tasks of the estimation system and by explicit use of the time-to-go in the process. The outcome of the new approach is illustrated by results of Monte Carlo simulations in generic interception scenarios. The results indicate that if an eventual ‘jump’ in the commanded target acceleration is detected sufficiently rapidly, small estimation errors and consequently precise guidance can be obtained.

Acceleration Algorithms in Monte Carlo Simulations in Statistical Physics

1991 ◽  
Vol 02 (01) ◽  
pp. 201-208
Author(s):  
ROBERT H. SWENDSEN
Keyword(s):  
Monte Carlo ◽  
Phase Transitions ◽  
Monte Carlo Simulations ◽  
Statistical Physics ◽  
Relaxation Times ◽  
Critical Slowing Down ◽  
Cluster Approach ◽  
New Developments ◽  
Slowing Down ◽  
Thermodynamic Phase

Monte Carlo simulations of thermodynamic phase transitions are usually hampered by long relaxation times due to the phenomenon of “critical slowing down.” Using a mapping due to Fortuin and Kasteleyn, a cluster approach to Monte Carlo simulations has been developed, which greatly reduces relaxation times, improving efficiency by up to two or three orders of magnitude. New developments and extensions of this approach are also discussed.

HOW MONTE CARLO SIMULATIONS CAN CLARIFY COMPLEX PROBLEMS IN STATISTICAL PHYSICS

2001 ◽  
Vol 15 (09) ◽  
pp. 1193-1211 ◽  
Author(s):  
KURT BINDER
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Statistical Physics ◽  
Condensed Matter ◽  
Finite Size ◽  
Two Dimensional ◽  
Finite Size Scaling ◽  
Complex Phase ◽  
Finite Systems ◽  
Scaling Methods

Statistical mechanics of condensed matter systems in physics (fluids and solids) derives macroscopic equilibrium properties of these systems as averages computed from a Hamiltonian that describes the atomistic interactions in the system. While analytic methods for most problems involve uncontrolled approximations, Monte Carlo simulations allow numerically exact treatments, apart from statistical errors and from the systematic problem that finite systems are treated rather than the thermodynamic limit. However, this problem can be overcome by finite size scaling methods, and thus Monte Carlo methods have become a very powerful tool to study even complex phase transitions. Examples given will include unmixing of polymer blends, two-dimensional melting, etc.

A parallel multiprocessor system for Monte Carlo simulations in statistical physics

1989 ◽  
Vol 60 (9) ◽  
pp. 2981-2991 ◽  
Author(s):  
Jukka Saarinen ◽  
Kimmo Kaski ◽  
Jouko Viitanen
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Statistical Physics ◽  
Multiprocessor System
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