Date of Original Version
In the present paper we describe a stochastic quadrature method that is designed for the evaluation of generalized, complex averages. Motivated by recent advances in sparse sampling techniques, this method is based on a combination of parallel tempering and stationary phase filtering methods. Numerical applications of the resulting ‘‘stationary tempering’’ approach are presented. We also examine inherent structure decomposition from a probabilistic clustering perspective.
D. Sabo, J.D. Doll and D.L. Freeman, “Stationary tempering and the complex quadrature problem,” Journal of Chemical Physics, 116(9), 3509 (2002).