Coupled Cluster Theory (CCT)

Single-reference coupled cluster (SRCC) methods have revolutionized our ability to accurately predict molecular energies and properties. As new developments in theory and computer science extend the application of SRCC methods to larger and larger systems, advancements in coupled cluster methods for studying multi-reference systems have lagged far behind. DECISIVE ANALYTICS Corporation has teamed with Professor Edward Valeev from Virginia Tech to propose a robust, efficient, easy-to-use coupled cluster method applicable to ground-state and excited-state molecular properties. The parallel explicitly-correlated importance-sampling coupled cluster method (ISCC-F12) will extend the ability to accurately predict molecular energies and properties to large multi-reference applications through a unique combination of an arbitrary-order, general active-space sampling algorithm, a universal perturbative explicitly-correlated basis set incompleteness correction, and an efficient parallel block-sparse multi-dimensional tensor contraction library. BENEFIT: The parallel ISCC-F12 method being developed under this effort has the potential to provide unparalleled accuracy to larger multi-reference applications than ever before. Our method can provide the AFOSR with a predictive tool to study the energy and properties of ground-state and excited-state potential energy surfaces, polyradical species, and low-spin transition metal compounds that are often encountered in the discovery of new energetic materials for propellants and explosives, insensitive munitions, fuels, and gas generators. The parallel ISCC-F12 method will, for the first time, enable scientists to study multi-reference applications without choosing an active-space or hand-selecting reference configurations. DECISIVE ANALYTICS Corporation and Professor Edward Valeev from Virginia Tech have developed related technologies for multi-reference applications and our team is well-positioned to take advantage of the technology developed under this STTR.