Multiscale quantum algorithms for quantum chemistry

• Published in: Chemical science (Cambridge) Vol. 14; no. 12; pp. 319 - 325
• Main Authors: Ma, Huan, Liu, Jie, Shang, Honghui, Fan, Yi, Li, Zhenyu, Yang, Jinlong
• Format: Journal Article
• Language: English
• Published: England Royal Society of Chemistry 22.03.2023; The Royal Society of Chemistry
• Subjects: Algorithms; Chemistry; Complex systems; Perturbation theory; Quantum chemistry; Quantum computers; Quantum computing; Simulation
• ISSN: 2041-6520; 2041-6539
• DOI: 10.1039/d2sc06875c

Exploring the potential applications of quantum computers in material design and drug discovery is attracting more and more attention after quantum advantage has been demonstrated using Gaussian boson sampling. However, quantum resource requirements in material and (bio)molecular simulations are far beyond the capacity of near-term quantum devices. In this work, multiscale quantum computing is proposed for quantum simulations of complex systems by integrating multiple computational methods at different scales of resolution. In this framework, most computational methods can be implemented in an efficient way on classical computers, leaving the critical portion of the computation to quantum computers. The simulation scale of quantum computing strongly depends on available quantum resources. As a near-term scheme, we integrate adaptive variational quantum eigensolver algorithms, second-order Møller-Plesset perturbation theory and Hartree-Fock theory within the framework of the many-body expansion fragmentation approach. This new algorithm is applied to model systems consisting of hundreds of orbitals with decent accuracy on the classical simulator. This work should encourage further studies on quantum computing for solving practical material and biochemistry problems. We propose a multiscale quantum computing framework suitable for efficient simulations of complex chemical systems on near-term quantum devices.