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.
Sabo, D., Doll, J. D., & Freeman, D. L. (2002). Stationary tempering and the complex quadrature problem. Journal of Chemical Physics, 116(9), 3509-3520. doi: 10.1063/1.1446431
Available at: http://dx.doi.org/10.1063/1.1446431