Jitendra Balakrishnan

Monte Carlo method for computing density of states and quench probability of potential energy and enthalpy landscapes

The thermodynamics and kinetics of a many-body system can be described in terms of a potential energy landscape in multidimensional configuration space. The partition function of such a landscape can be written in terms of a density of states, which can be computed using a variety of Monte Carlo techniques. In this paper, a new self-consistent Monte Carlo method for computing density of states is described that uses importance sampling and a multiplicative update factor to achieve rapid convergence. The technique is then applied to compute the equilibrium quench probability of the various inherent structures (minima) in the landscape. The quench probability depends on both the potential energy of the inherent structure and the volume of its corresponding basin in configuration space. Finally, the methodology is extended to the isothermal-isobaric ensemble in order to compute inherent structure quench probabilities in an enthalpy landscape.

Potential energy landscapes of elemental and heterogeneous chalcogen clusters

We describe the potential energy landscapes of elemental S{sub 8}, Se{sub 8}, and Te{sub 8} clusters using disconnectivity graphs. Inherent structures include both ring and chain configurations, with rings especially dominant in Se{sub 8}. We also map the potential energy landscapes of heterogeneous Se{sub n}(S,Te){sub 8-n} clusters, which offer insights into the structure of heterogeneous chalcogen glasses.