Partitioning Quantum Chemistry Simulations with Clifford Circuits

TL;DR

This paper explores a hybrid quantum-classical approach to simulate larger molecules with fewer qubits by partitioning quantum chemistry problems using Clifford and near-Clifford circuits, balancing efficiency and expressibility.

Contribution

It introduces a novel partitioning method employing Clifford and near-Clifford circuits to reduce qubit requirements while maintaining accuracy in quantum chemistry simulations.

Findings

Achieved up to 50% reduction in qubit count.

Maintained similar accuracy to traditional methods.

Validated approach through numerical simulations.

Abstract

Current quantum computing hardware is restricted by the availability of only few, noisy qubits which limits the investigation of larger, more complex molecules in quantum chemistry calculations on quantum computers in the near-term. In this work, we investigate the limits of their classical and near-classical treatment while staying within the framework of quantum circuits and the variational quantum eigensolver. To this end, we consider naive and physically motivated, classically efficient product ansatz for the parametrized wavefunction adapting the separable pair ansatz form. We combine it with post-treatment to account for interactions between subsystems originating from this ansatz. The classical treatment is given by another quantum circuit that has support between the enforced subsystems and is folded into the Hamiltonian. To avoid an exponential increase in the number of Hamiltonian terms, the entangling operations are constructed from purely Clifford or near-Clifford circuits. While Clifford circuits can be simulated efficiently classically, they are not universal. In order to account for missing expressibility, near-Clifford circuits with only few, selected non-Clifford gates are employed. The exact circuit structure to achieve this objective is molecule-dependent and is constructed using simulated annealing and genetic algorithms. We demonstrate our approach on a set of molecules of interest and investigate the extent of our methodology's reach. Empirical validation of our approach using numerical simulations shows a reduction of the qubit count of up to a 50\% at a similar accuracy as compared to the separable-pair ansatz.