Truncated Variational Hamiltonian Ansatz: efficient quantum circuit design for quantum chemistry and material science

TL;DR

The paper introduces the truncated Variational Hamiltonian Ansatz (tVHA), a new quantum circuit design that reduces complexity and improves convergence for quantum chemistry calculations on noisy intermediate-scale quantum devices.

Contribution

The novel tVHA circuit significantly lowers parameter count and circuit size, enabling more efficient variational quantum eigensolver applications compared to existing ansätze.

Findings

tVHA reduces circuit size and parameters

tVHA improves convergence in quantum chemistry calculations

tVHA is suitable for both weakly and strongly correlated systems

Abstract

Quantum computing has the potential to revolutionize quantum chemistry and material science by offering solutions to complex problems unattainable with classical computers. However, the development of efficient quantum algorithms that are efficient under noisy conditions remains a major challenge. This paper introduces the truncated Variational Hamiltonian Ansatz (tVHA), a novel circuit design for conducting quantum calculations on Noisy Intermediate-Scale Quantum (NISQ) devices. tVHA provides a promising approach for a broad range of applications by utilizing principles from the adiabatic theorem in solid state physics. Our proposed ansatz significantly reduces the parameter count and can decrease circuit size substantially, with a trade-off in accuracy. Thus, tVHA facilitates easier convergence within the variational quantum eigensolver framework compared to state-of-the-art ans\"atze such as Unitary Coupled Cluster (UCC) and Hardware-Efficient Ansatz (HEA). While this paper concentrates on the practical applications of tVHA in quantum chemistry, demonstrating its suitability for both weakly and strongly correlated systems and its compatibility with active space calculations, its underlying principles suggest a wider applicability extending to the broader field of material science computations on quantum computing platforms.