Abstract
The Hessian of the ring polymer spring potential in the standard Trotter path integral is a P × P symmetric circulant matrix with a centroid eigenvalue of zero. All such matrices commute and are diagonalized by the same bead-to-normal mode transformation matrix, and their eigenvalues contain ⌈P/2⌉ − 1 degenerate pairs by symmetry. However, this still leaves some freedom to improve on the Trotter approximation: one can optimize the remaining ⌊P/2⌋ independent non-zero normal mode frequencies to fit the exact quantum mechanical radii of gyration of harmonic ring polymers with frequencies in the range 0 ≤ ω ≤ ωmax, where ωmax is the maximum physical frequency in the problem of interest. The optimization involves solving a simple least squares problem for the optimum (economized or “Eco”) internal mode frequencies. The remainder of the calculation then proceeds in the same way as a Trotter path integral calculation. An example application to hexagonal ice shows that the convergence of the Eco path integral is comparable to that of the fourth order Suzuki–Chin path integral, but with purely second order Trotter effort. There is no need to calculate the projected Hessians that arise in the Suzuki–Chin method by finite differences; there is no need to develop any new estimators for observables, and once the Eco frequencies have been calculated, the implementation of the Eco path integral involves changing just a few lines of a Trotter path integral code. To provide a more impressive example, we have implemented the Eco method in GPUMD and used it to converge the (negative) thermal expansion coefficient and the constant pressure heat capacity of MOF-5 with a machine-learned neuroevolution potential.