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

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.

Ab Initio Methods in First‐Row Transition Metal Chemistry

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Accurate non-covalent interaction energies on noisy intermediate-scale quantum computers via second-order symmetry-adapted perturbation theory

“…Many application studies in chemistry use either reduced model systems or molecules with a simple electronic structure [30][31][32][33]. There are several promising application areas for quantum chemistry in computer aided drug design [34] namely, exploring potential energy surfaces [35], simulating metalloenzymes [36] and computing protein-ligand interaction energies [37], the last of which we consider in this work.…”

Simulating key properties of lithium-ion batteries with a fault-tolerant quantum computer

“…This is a major experimental and theoretical effort requiring innovations on several fronts. While the computational resource requirements of quantum algorithms have steadily decreased over time [45], there is still significant room to improve and identify problems of practical importance where a convincing argument can be made for the benefits of a quantum approach [38,[46][47][48].…”