AN APPROACH FOR IMPROVED VARIATIONAL QUANTUM MONTE-CARLO

Sampling of core electrons in Monte Carlo approaches to electronic str ucture is a major bottleneck to efficient studies of large molecules. To overcome this problem, we propose an improved Metropolis algorithm for variational Monte Carlo which includes the second derivatives (Hes sian matrix) of the pseudopotential P=-ln\Psi(T)\(2) in its transition probability in addition to the commonly used first derivatives (or qu antum force). To minimize computational effort, we use only the diagon al elements of the Hessian matrix, which are readily obtained from inf ormation already available in the Monte Carlo computation. We analyze the effect of these diagonal terms on the transition probability and c ore-electron sampling. The approach automatically reduces the step siz es of the innermost electrons and does not require further considerati ons such as choice of coordinate system or assignment of electrons to specific shells. In addition, heteronuclear molecules pose no difficul ty for the present algorithm. Application of the method to representat ive systems, Ne, Ar, and KCl, has shown that it increases the acceptan ce ratio of the innermost core electrons by a factor of 5 over previou s algorithms.