papers AI Learner
The Github is limit! Click to go to the new site.

An efficient deterministic perturbation theory for selected configuration interaction methods

2018-08-06
Norm M. Tubman, Daniel S. Levine, Diptarka Hait, Martin Head-Gordon, K. Birgitta Whaley

Abstract

The interplay between advances in stochastic and deterministic algorithms has recently led to development of interesting new selected configuration interaction (SCI) methods for solving the many body Schrödinger equation. The performance of these SCI methods can be greatly improved with a second order perturbation theory (PT2) correction, which is often evaluated in a stochastic or hybrid-stochastic manner. In this work, we present a highly efficient, fully deterministic PT2 algorithm for SCI methods and demonstrate that our approach is orders of magnitude faster than recent proposals for stochastic SCI+PT2. We also show that it is important to have a compact reference SCI wave function, in order to obtain optimal SCI+PT2 energies. This indicates that it advantageous to use accurate search algorithms such as ‘ASCI search’ rather than more approximate approaches. Our deterministic PT2 algorithm is based on sorting techniques that have been developed for modern computing architectures and is inherently straightforward to use on parallel computing architectures. Related architectures such as GPU implementations can be also used to further increase the efficiency. Overall, we demonstrate that the algorithms presented in this work allow for efficient evaluation of trillions of PT2 contributions with modest computing resources.

Abstract (translated by Google)
URL

https://arxiv.org/abs/1808.02049

PDF

https://arxiv.org/pdf/1808.02049


Similar Posts

Comments