Work

Reducing unitary coupled cluster circuit depth by classical stochastic amplitude prescreening

Year: 2022

Type: article

Abstract: Unitary coupled cluster (UCC) approaches are an appealing route to utilizing quantum hardware to perform quantum chemistry calculations, as quantum computers can in principle perform UCC calculations in a polynomially scaling fashion, as compared with the exponential scaling required on classical computers. Current noisy intermediate scale quantum computers are limited by both hardware capacity in number of logical qubits and the noise introduced by the deep circuits required for UCC calculations using the variational quantum eigensolver (VQE) approach. We present a combined classical-quantum approach where a stochastic classical UCC preprocessing step is used to determine the important excitations in the UCC Ansatz. The reduced number of selected excitations are then used in a UCC-based VQE calculation. This approach gives a systematically improvable approximation, and we show that significant reductions in quantum resources can be achieved, with simulations on the ${\mathrm{CH}}_{2}, {\mathrm{N}}_{2}$, and ${\mathrm{N}}_{2}{\mathrm{H}}_{2}$ molecules giving submillihartree errors.

Source: Physical Review Research

DOI: 10.1103/physrevresearch.4.023243

Authors: Maria-Andreea Filip, Nathan Fitzpatrick, David Muñoz Ramo, Alex J. W. Thom

Institutions: University of Cambridge, Cambridge Quantum Computing (United Kingdom)

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,625

Funders: Royal Society, Cambridge Trust, Corpus Christi College, University of Cambridge