Variance reduction for forces and pressure in variational Monte Carlo
The work presents simple strategies to reduce variance in Monte Carlo estimators for atomic forces and pressure calculations in variational Monte Carlo methods. By using covariance decomposition, acceptance tricks, and regularization of Pulay terms, the authors show how these modifications can change the variance scaling from problematic power-law divergence to a manageable logarithmic one.