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

TL;DR

This paper evaluates the classical and quantum computational resources needed to simulate the electronic structure of cytochrome P450 enzymes, highlighting potential quantum advantages in complex chemical simulations.

Contribution

It provides a detailed analysis of classical and quantum resource requirements for simulating CYP enzymes, establishing a classical-quantum advantage boundary.

Findings

Classical methods like DMRG+NEVPT2 and CCSD(T) are analyzed for convergence.

Quantum phase estimation resources are estimated for CYP models.

Simulation of large CYP models may demonstrate quantum advantage.

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. In order to perform this assessment reliably, quantum resource estimates must be coupled with classical simulations attempting to answer relevant chemical questions and to define the classical simulation frontier. Herein, we explore the quantum and classical 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 DMRG+NEVPT2 and coupled cluster singles doubles with non-iterative 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 simulations and quantum algorithms development for chemical simulation.