Q# and NWChem: Tools for Scalable Quantum Chemistry on Quantum Computers

TL;DR

This paper introduces an open-source quantum chemistry library in Q# that interfaces with NWChem, enabling scalable quantum simulations of electronic structures for complex molecules, bridging classical and quantum computational tools.

Contribution

The paper presents a standardized interface schema, Broombridge, and demonstrates practical quantum chemistry calculations on molecules, facilitating scalable quantum simulations on hardware.

Findings

Successfully performed ground- and excited-state calculations for complex molecules.

Provided resource estimates for classically intractable quantum simulations.

Integrated NWChem with Q# for accessible quantum chemistry computations.

Abstract

Fault-tolerant quantum computation promises to solve outstanding problems in quantum chemistry within the next decade. Realizing this promise requires scalable tools that allow users to translate descriptions of electronic structure problems to optimized quantum gate sequences executed on physical hardware, without requiring specialized quantum computing knowledge. To this end, we present a quantum chemistry library, under the open-source MIT license, that implements and enables straightforward use of state-of-art quantum simulation algorithms. The library is implemented in Q#, a language designed to express quantum algorithms at scale, and interfaces with NWChem, a leading electronic structure package. We define a standardized schema for this interface, Broombridge, that describes second-quantized Hamiltonians, along with metadata required for effective quantum simulation, such as trial wavefunction ansatzes. This schema is generated for arbitrary molecules by NWChem, conveniently accessible, for instance, through Docker containers and a recently developed web interface EMSL Arrows. We illustrate use of the library with various examples, including ground- and excited-state calculations for LiH, H$_{10}$, and C$_{20}$ with an active-space simplification, and automatically obtain resource estimates for classically intractable examples.