• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

用于语境子空间变分量子本征求解器和非语境投影假设的稳定器框架。

A Stabilizer Framework for the Contextual Subspace Variational Quantum Eigensolver and the Noncontextual Projection Ansatz.

机构信息

Centre for Computational Science, Department of Chemistry, University College London, LondonWC1H 0AJ, United Kingdom.

Department of Physics and Astronomy, Tufts University, Medford, Massachusetts02155, United States.

出版信息

J Chem Theory Comput. 2023 Feb 14;19(3):808-821. doi: 10.1021/acs.jctc.2c00910. Epub 2023 Jan 23.

DOI:10.1021/acs.jctc.2c00910
PMID:36689668
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9933439/
Abstract

Quantum chemistry is a promising application for noisy intermediate-scale quantum (NISQ) devices. However, quantum computers have thus far not succeeded in providing solutions to problems of real scientific significance, with algorithmic advances being necessary to fully utilize even the modest NISQ machines available today. We discuss a method of ground state energy estimation predicated on a partitioning of the molecular Hamiltonian into two parts: one that is and can be solved classically, supplemented by a component that yields quantum corrections obtained via a Variational Quantum Eigensolver (VQE) routine. This approach has been termed (CS-VQE); however, there are obstacles to overcome before it can be deployed on NISQ devices. The problem we address here is that of the ansatz, a parametrized quantum state over which we optimize during VQE; it is not initially clear how a splitting of the Hamiltonian should be reflected in the CS-VQE ansätze. We propose a "noncontextual projection" approach that is illuminated by a reformulation of CS-VQE in the stabilizer formalism. This defines an ansatz restriction from the full electronic structure problem to the contextual subspace and facilitates an implementation of CS-VQE that may be deployed on NISQ devices. We validate the noncontextual projection ansatz using a quantum simulator and demonstrate chemically precise ground state energy calculations for a suite of small molecules at a significant reduction in the required qubit count and circuit depth.

摘要

量子化学是嘈杂的中等规模量子(NISQ)设备的一个有前途的应用。然而,量子计算机迄今为止未能为真正具有科学意义的问题提供解决方案,需要算法上的进步才能充分利用当今现有的适度 NISQ 机器。我们讨论了一种基于分子哈密顿量的两部分划分的基态能量估计方法:一部分是可以用经典方法求解的 ,通过变分量子本征求解器(VQE)例程获得的量子修正来补充 部分。这种方法被称为 (CS-VQE);然而,在将其部署到 NISQ 设备之前,还有一些障碍需要克服。我们在这里解决的问题是变分量子本征求解(VQE)中优化的变分量子本征态的假设,在 VQE 中,我们对其进行优化;最初不清楚哈密顿量的分裂应该如何反映在 CS-VQE 假设中。我们提出了一种“非上下文投影”方法,该方法通过在稳定子形式主义中重新表述 CS-VQE 得到了阐明。这定义了从全电子结构问题到上下文子空间的假设限制,并促进了 CS-VQE 的实现,该实现可以部署在 NISQ 设备上。我们使用量子模拟器验证了非上下文投影假设,并演示了对一系列小分子的化学精确基态能量计算,所需的量子比特数和电路深度显著减少。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b42/9933439/a21efeec8679/ct2c00910_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b42/9933439/e7e8a2c1a34a/ct2c00910_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b42/9933439/1a7c6a984455/ct2c00910_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b42/9933439/a21efeec8679/ct2c00910_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b42/9933439/e7e8a2c1a34a/ct2c00910_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b42/9933439/1a7c6a984455/ct2c00910_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b42/9933439/a21efeec8679/ct2c00910_0003.jpg

相似文献

1
A Stabilizer Framework for the Contextual Subspace Variational Quantum Eigensolver and the Noncontextual Projection Ansatz.用于语境子空间变分量子本征求解器和非语境投影假设的稳定器框架。
J Chem Theory Comput. 2023 Feb 14;19(3):808-821. doi: 10.1021/acs.jctc.2c00910. Epub 2023 Jan 23.
2
Deep Neural Network Assisted Quantum Chemistry Calculations on Quantum Computers.深度神经网络辅助量子计算机上的量子化学计算。
ACS Omega. 2023 Dec 4;8(50):48211-48220. doi: 10.1021/acsomega.3c07364. eCollection 2023 Dec 19.
3
Wave Function Adapted Hamiltonians for Quantum Computing.用于量子计算的波函数适配哈密顿量。
J Chem Theory Comput. 2022 Feb 8;18(2):899-909. doi: 10.1021/acs.jctc.1c01170. Epub 2022 Jan 18.
4
Variational Quantum-Neural Hybrid Eigensolver.变分量子神经混合本征解算器
Phys Rev Lett. 2022 Mar 25;128(12):120502. doi: 10.1103/PhysRevLett.128.120502.
5
Improved Accuracy on Noisy Devices by Nonunitary Variational Quantum Eigensolver for Chemistry Applications.用于化学应用的非酉变分量子本征求解器在噪声设备上提高了精度。
J Chem Theory Comput. 2021 Jul 13;17(7):3946-3954. doi: 10.1021/acs.jctc.1c00091. Epub 2021 Jun 2.
6
Fragment molecular orbital-based variational quantum eigensolver for quantum chemistry in the age of quantum computing.量子计算时代基于片段分子轨道的变分量子本征求解器用于量子化学。
Sci Rep. 2024 Jan 29;14(1):2422. doi: 10.1038/s41598-024-52926-3.
7
Quantum Algorithm of the Divide-and-Conquer Unitary Coupled Cluster Method with a Variational Quantum Eigensolver.基于变分量子特征求解器的分治幺正耦合簇方法的量子算法
J Chem Theory Comput. 2022 Sep 13;18(9):5360-5373. doi: 10.1021/acs.jctc.2c00602. Epub 2022 Aug 4.
8
The Cost of Improving the Precision of the Variational Quantum Eigensolver for Quantum Chemistry.提高量子化学变分量子本征求解器精度的成本。
Nanomaterials (Basel). 2022 Jan 14;12(2):243. doi: 10.3390/nano12020243.
9
Amplitude Reordering Accelerates the Adaptive Variational Quantum Eigensolver Algorithms.幅度重排序加速自适应变分量子特征求解器算法。
J Chem Theory Comput. 2022 Sep 13;18(9):5267-5275. doi: 10.1021/acs.jctc.2c00403. Epub 2022 Aug 15.
10
Scaling up electronic structure calculations on quantum computers: The frozen natural orbital based method of increments.在量子计算机上扩大电子结构计算规模:基于冻结自然轨道的增量法。
J Chem Phys. 2021 Jul 21;155(3):034110. doi: 10.1063/5.0054647.

引用本文的文献

1
Contextual subspace variational quantum eigensolver calculation of the dissociation curve of molecular nitrogen on a superconducting quantum computer.在超导量子计算机上对分子氮解离曲线进行上下文子空间变分量子本征求解器计算。
npj Quantum Inf. 2025;11(1):25. doi: 10.1038/s41534-024-00952-4. Epub 2025 Feb 12.
2
Synergizing quantum techniques with machine learning for advancing drug discovery challenge.将量子技术与机器学习相结合以应对推进药物发现的挑战。
Sci Rep. 2024 Dec 28;14(1):31216. doi: 10.1038/s41598-024-82576-4.
3
Universal compilation for quantum state tomography.

本文引用的文献

1
Hidden Variable Model for Universal Quantum Computation with Magic States on Qubits.用于量子比特上具有魔法态的通用量子计算的隐变量模型
Phys Rev Lett. 2020 Dec 31;125(26):260404. doi: 10.1103/PhysRevLett.125.260404.
2
Hartree-Fock on a superconducting qubit quantum computer.超导量子比特量子计算机上的 Hartree-Fock 方法。
Science. 2020 Aug 28;369(6507):1084-1089. doi: 10.1126/science.abb9811.
3
Reducing Qubit Requirements for Quantum Simulations Using Molecular Point Group Symmetries.利用分子点群对称性降低量子模拟的量子比特需求。
量子态层析的通用编译。
Sci Rep. 2023 Mar 6;13(1):3750. doi: 10.1038/s41598-023-30983-4.
J Chem Theory Comput. 2020 Oct 13;16(10):6091-6097. doi: 10.1021/acs.jctc.0c00113. Epub 2020 Sep 10.
4
Measurement optimization in the variational quantum eigensolver using a minimum clique cover.使用最小团覆盖的变分量子本征求解器中的测量优化。
J Chem Phys. 2020 Mar 31;152(12):124114. doi: 10.1063/1.5141458.
5
Measuring All Compatible Operators in One Series of Single-Qubit Measurements Using Unitary Transformations.利用酉变换在一系列单量子比特测量中测量所有兼容算符。
J Chem Theory Comput. 2020 Apr 14;16(4):2400-2409. doi: 10.1021/acs.jctc.0c00008. Epub 2020 Mar 18.
6
Iterative Qubit Coupled Cluster Approach with Efficient Screening of Generators.具有高效生成元筛选的迭代量子比特耦合簇方法
J Chem Theory Comput. 2020 Feb 11;16(2):1055-1063. doi: 10.1021/acs.jctc.9b01084. Epub 2020 Jan 24.
7
Contextuality Test of the Nonclassicality of Variational Quantum Eigensolvers.变分量子本征求解非经典性的语境性检验。
Phys Rev Lett. 2019 Nov 15;123(20):200501. doi: 10.1103/PhysRevLett.123.200501.
8
Unitary Partitioning Approach to the Measurement Problem in the Variational Quantum Eigensolver Method.单一划分方法在变分量子本征求解方法中的测量问题。
J Chem Theory Comput. 2020 Jan 14;16(1):190-195. doi: 10.1021/acs.jctc.9b00791. Epub 2019 Dec 5.
9
An adaptive variational algorithm for exact molecular simulations on a quantum computer.一种用于量子计算机上精确分子模拟的自适应变分算法。
Nat Commun. 2019 Jul 8;10(1):3007. doi: 10.1038/s41467-019-10988-2.
10
Downfolding of many-body Hamiltonians using active-space models: Extension of the sub-system embedding sub-algebras approach to unitary coupled cluster formalisms.使用活性空间模型对多体哈密顿量进行降阶折叠:将子系统嵌入子代数方法扩展到酉耦合簇形式体系。
J Chem Phys. 2019 Jul 7;151(1):014107. doi: 10.1063/1.5094643.