title: Large-Scale Cubic-Scaling Random Phase Approximation Correlation Energy Calculations Using a Gaussian Basis.
abstract: We present an algorithm for computing the correlation energy in the random phase approximation (RPA) in a Gaussian basis requiring [Formula: see text] operations and [Formula: see text] memory. The method is based on the resolution of the identity (RI) with the overlap metric, a reformulation of RI-RPA in the Gaussian basis, imaginary time, and imaginary frequency integration techniques, and the use of sparse linear algebra. Additional memory reduction without extra computations can be achieved by an iterative scheme that overcomes the memory bottleneck of canonical RPA implementations. We report a massively parallel implementation that is the key for the application to large systems. Finally, cubic-scaling RPA is applied to a thousand water molecules using a correlation-consistent triple-ζ quality basis.
authors: Department of Chemistry and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), University of Zurich , 8057 Zurich, Switzerland.
authors: Jan
authors: J
authors: Wilhelm
authors: Department of Chemistry and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), University of Zurich , 8057 Zurich, Switzerland.
authors: Patrick
authors: P
authors: Seewald
authors: Computational Research Division, Lawrence Berkeley National Laboratory , Berkeley, California 94720, United States.
authors: Mauro
authors: M
authors: Del Ben
authors: Department of Chemistry and National Centre for Computational Design and Discovery of Novel Materials (MARVEL), University of Zurich , 8057 Zurich, Switzerland.
authors: Jürg
authors: J
authors: Hutter