Reliably assessing the electronic structure of cytochrome P450 on today’s classical computers and tomorrow’s quantum computers

TLDR

Quantum computers’ potential computational advantages for chemical simulation must be accurately assessed to guide their deployment. The study aims to assess the electronic structure of cytochrome P450 enzymes by coupling quantum resource estimates with classical computations to delineate the classical–quantum advantage boundary. The authors analyze convergence of DMRG+NEVPT2 and CCSD(T) for spin gaps in CYP models, compute quantum resources for phase estimation via qubitized quantum walks, and compile these into surface‑code runtimes to compare with DMRG runtimes. Classical and quantum resource estimates indicate that simulating CYP models at sufficient scale may yield quantum advantage, highlighting the interplay between classical computations and quantum algorithm development.

Abstract

An accurate assessment of how quantum computers can be used for chemical simulation, especially their potential computational advantages, provides important context on how to deploy these future devices. To perform this assessment reliably, quantum resource estimates must be coupled with classical computations attempting to answer relevant chemical questions and to define the classical algorithms simulation frontier. Herein, we explore the quantum computation and classical computation resources required to assess the electronic structure of cytochrome P450 enzymes (CYPs) and thus define a classical–quantum advantage boundary. This is accomplished by analyzing the convergence of density matrix renormalization group plus n -electron valence state perturbation theory (DMRG+NEVPT2) and coupled-cluster singles doubles with noniterative triples [CCSD(T)] calculations for spin gaps in models of the CYP catalytic cycle that indicate multireference character. The quantum resources required to perform phase estimation using qubitized quantum walks are calculated for the same systems. Compilation into the surface code provides runtime estimates to compare directly to DMRG runtimes and to evaluate potential quantum advantage. Both classical and quantum resource estimates suggest that simulation of CYP models at scales large enough to balance dynamic and multiconfigurational electron correlation has the potential to be a quantum advantage problem and emphasizes the important interplay between classical computations and quantum algorithms development for chemical simulation.