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可靠地评估细胞色素 P450 的电子结构,无论是在当今的经典计算机上,还是在未来的量子计算机上。

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

机构信息

Google Quantum AI, Google Research, Venice, CA 90291.

Quantum Simulation Technologies, Inc., Boston, MA 02135.

出版信息

Proc Natl Acad Sci U S A. 2022 Sep 20;119(38):e2203533119. doi: 10.1073/pnas.2203533119. Epub 2022 Sep 12.

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 -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.

摘要

准确评估量子计算机在化学模拟中的应用,特别是它们潜在的计算优势,为如何部署这些未来的设备提供了重要的背景信息。为了可靠地进行这种评估,必须将量子资源估计与试图回答相关化学问题并定义经典算法模拟前沿的经典计算相结合。在此,我们探讨了评估细胞色素 P450 酶 (CYPs) 电子结构所需的量子计算和经典计算资源,从而定义了经典-量子优势边界。这是通过分析密度矩阵重整化群加 -电子价态微扰理论 (DMRG+NEVPT2) 和耦合簇单双加非迭代三 [CCSD(T)] 计算在表明多参考特征的 CYP 催化循环模型中的自旋间隙的收敛来实现的。为相同的系统计算了使用量子比特化量子行走进行相位估计所需的量子资源。编译到表面码中提供了运行时估计值,可直接与 DMRG 运行时间进行比较,并评估潜在的量子优势。经典和量子资源估计都表明,在足以平衡动态和多组态电子相关的规模上模拟 CYP 模型有可能成为量子优势问题,并强调了经典计算和量子算法开发在化学模拟中的重要相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c7d8/9499570/a693b5fba62e/pnas.2203533119fig01.jpg

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