The influence of basis sets and ansatze building to quantum computing in chemistry

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Molecular Modeling Pub Date : 2024-07-19 DOI:10.1007/s00894-024-06072-2
Caio M. Porto, Rene Alfonso Nome, Nelson H. Morgon
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Abstract

Context

Quantum computing is an exciting area, which has grown at an astonishing rate in the last decade. It is especially promising for the computational and theoretical chemistry area. One algorithm has received a lot of attention lately, the variational quantum eigensolver (VQE). It is used to solve electronic structure problems and it is suitable to the noisy intermediate-scale quantum (NISQ) hardware. VQE calculations require ansatze and one of the most known is the unitary coupled cluster (UCC). It uses the chosen basis set to generate a quantum computing circuit which will be iteratively minimized. The present work investigates the circuit depth and the number of gates as a function of basis sets and molecular size. It has been shown that for the current quantum devices, only the smallest molecules and basis sets are tractable. The H\(_{\textbf{2}}\) molecule with the cc-pVTZ and aug-cc-pVTZ basis sets have circuit depths in the order of 10\(^6\) to 10\(^{\textbf{7}}\) gates and the C\(_{\textbf{2}}\)H\(_{\textbf{6}}\) molecule with 3–21G basis set has a circuit depth of \(\mathbf {2.2}\times \textbf{10}^{\textbf{8}}\) gates. At the same time the analysis demonstrates that the H\(_{\textbf{2}}\) molecule with STO-3G basis set, requires at least 500 shots to reduce the error and that, although error mitigation schemes can diminish the error, they were not able to completely negate it.

Methods

The quantum computing and electronic structure calculations were performed using the Qiskit package from IBM and the PySCF package, respectively. The ansatze were generated using the UCCSD method as implemented in Qiskit, using the basis sets STO-3G, 3–21G, 6–311G(d,p), def2-TZVP, cc-pVDZ, aug-cc-pVDZ, cc-pVTZ, and aug-cc-pVTZ. The operators and the Hamiltonian were mapped using the Jordan-Wigner scheme. The classical optimizer chosen was the simultaneous perturbation stochastic approximation (SPSA). The quantum computers used were the Nairobi and Osaka, with 7 and 127 qubits respectively.

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基集和安萨特泽构建对化学量子计算的影响。
背景:量子计算是一个令人兴奋的领域,在过去十年中以惊人的速度发展。对于计算和理论化学领域来说,它尤其大有可为。最近,有一种算法备受关注,它就是变分量子优解器(VQE)。它用于解决电子结构问题,适用于噪声中量子(NISQ)硬件。VQE 计算需要ansatze,其中最著名的是单元耦合簇(UCC)。它使用所选的基集生成量子计算电路,该电路将被迭代最小化。目前的工作研究了电路深度和门的数量与基集和分子大小的函数关系。研究表明,对于目前的量子设备,只有最小的分子和基集是可行的。使用 cc-pVTZ 和 aug-cc-pVTZ 基集的 H 2 分子的电路深度在 10 6 到 10 7 门之间,而使用 3-21G 基集的 C 2 H 6 分子的电路深度为 2.2 × 10 8 门。同时分析表明,使用 STO-3G 基集的 H 2 分子至少需要 500 次射击才能减少误差,虽然误差缓解方案可以减少误差,但无法完全消除误差:量子计算和电子结构计算分别使用 IBM 的 Qiskit 软件包和 PySCF 软件包进行。计算结果使用 Qiskit 中实现的 UCCSD 方法生成,并使用了 STO-3G、3-21G、6-311G(d,p)、def2-TZVP、cc-pVDZ、aug-cc-pVDZ、cc-pVTZ 和 aug-cc-pVTZ 基集。算子和哈密顿都是用乔丹-维格纳方案映射的。选择的经典优化器是同步扰动随机近似(SPSA)。使用的量子计算机是内罗毕和大阪量子计算机,分别有 7 和 127 个量子比特。
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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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