Classical Pre-optimization Approach for ADAPT-VQE: Maximizing the Potential of High-Performance Computing Resources to Improve Quantum Simulation of Chemical Applications

TL;DR

This paper enhances ADAPT-VQE by integrating a sparse wavefunction circuit solver and a classical pre-optimization step, significantly reducing quantum resource requirements for accurate molecular energy calculations.

Contribution

It introduces a classical pre-optimization approach for ADAPT-VQE using SWCS, enabling efficient quantum simulations of larger molecular systems with reduced quantum computational cost.

Findings

SWCS improves accuracy and efficiency for molecules with up to 52 spin-orbitals.

Pre-optimization reduces quantum circuit depth and optimization iterations.

Method extends applicability of ADAPT-VQE to larger basis sets.

Abstract

The ADAPT-VQE algorithm is a promising method for generating a compact ansatz based on derivatives of the underlying cost function, and it yields accurate predictions of electronic energies for molecules. In this work we report the implementation and performance of ADAPT-VQE with our recently developed sparse wavefunction circuit solver (SWCS) in terms of accuracy and efficiency for molecular systems with up to 52 spin-orbitals. The SWCS can be tuned to balance computational cost and accuracy, which extends the application of ADAPT-VQE for molecular electronic structure calculations to larger basis sets and larger number of qubits. Using this tunable feature of the SWCS, we propose an alternative optimization procedure for ADAPT-VQE to reduce the computational cost of the optimization. By pre-optimizing a quantum simulation with a parameterized ansatz generated with ADAPT-VQE/SWCS, we aim to utilize the power of classical high-performance computing in order to minimize the work required on noisy intermediate-scale quantum hardware, which offers a promising path toward demonstrating quantum advantage for chemical applications.