Yuko Okamoto (Nagoya University)
Enhanced configurational sampling methods for spin systems and biomolecular systems
Conventional Monte Carlo and molecular dynamics simulations of spin and biological systems are greatly hampered by the multiple-minima problem, where the simulations tend to get trapped in some of a huge number of local-minimum-energy states which are separated by high energy barriers. In order to overcome this difficulty, we have been advocating the uses of generalized-ensemble algorithms which are based on non-Boltzmann weight factors. With these algorithms we can explore a wide range of the configurational space. The advantage of generalized-ensemble algorithms such as multicanonical algorithm, simulated tempering, and replica-exchange method lies in the fact that from only one simulation run, one can obtain various thermodynamic quantities as functions of temperature, pressure, and other parameters of the system. In this talk, I will present the results of our recent applications of generalized-ensemble algorithms to spin and biomolecular systems. Examples of the systems are Ising model, Potts model, protein, protein-ligand complex, etc.