Friday, October 27, 2017 - 4:00pm
Andrew Sand — Gagliardi Group
Smith 117/119
Gradients in MC-PDFT: It’s all downhill (or uphill) from here
Abstract: 
In order to optimize a molecular geometry, one needs to calculate and minimize the molecular gradient. Ideally, one would want to use an analytical approach (fast) as opposed to a numerical approach (slow). Analytic gradients can often be extremely difficult to compute, however, especially for non-variational methods. In this work, I will discuss the recent implementation of analytic gradient routines for multiconfiguration pair-density functional theory (MC-PDFT). In particular, I will show how the low time and memory costs of MC-PDFT, in addition to analytic gradient support, results in a methodology that is both fast and accurate for the determinations of equilibria and transition states, especially for multiconfigurational systems.