Finite Temperature Simulation of Non-Markovian Quantum Dynamics in Condensed Phase using Quantum Computers

使用量子计算机对凝聚相非马尔可夫量子动力学进行有限温度模拟

• 批准号: 2320328
• 负责人: Fei Wang
• 金额: $ 50.53万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2320328&HistoricalAwards=false
• 关键词: Finite; Temperature; Simulation; Non; Markovian

With support from the Chemical Theory, Models and Computational Methods program in the Division of Chemistry, Fei Wang of George Mason University will work to develop efficient quantum algorithms to perform condensed phase quantum dynamics simulations on quantum computers. Many important physical and chemical processes occur in the condensed phase, spanning chemical reactions in solutions, charge transfer at semiconductor interfaces, and solar energy conversion in molecular aggregates. The scientific investigation of these processes not only promotes our fundamental understanding but also offers practical solutions to materials design and environmental sustainability. As many of these processes involve charge migration and excitation energy transfer, quantum dynamics involving many degrees of freedom is essential for their description. However, such simulations are resource intensive on classical computers. On the other hand, quantum computers are naturally suited for quantum simulations. With algorithm development, Dr. Wang is aiming to show quantum speedup for quantum dynamics simulations in condensed phases, and demonstrate practical applications of quantum computing in the area of quantum simulation. Graduate students and postdoctoral researchers involved in this project will receive rigorous training in quantum information science and master state-of-the-art quantum simulation tools. Through internship programs offered to undergraduate and high school students, the PI will support underrepresented and economically disadvantaged groups. These efforts will not only encourage broad participation in STEM (science, technology, engineering and mathematics), but also help to educate a future quantum workforce for careers in academia and industry. The focus of this work will be to develop efficient quantum algorithms for finite-temperature non-Markovian time evolution, which offers a general framework for condensed phase quantum dynamics. New advances in this project will cover unitary operator construction, efficient quantum circuit compilation, model and real system simulations, and performance comparison between different types of quantum devices. Three mathematical methods will be explored (unitary dilation, singular value decomposition, and linear combinations of unitary operators) for non-unitary to unitary conversion, and their effectiveness will be assessed based on complexity theory. Two general approaches will be investigated for circuit compilation: one performs the exact mathematical decomposition, and the other uses the variational quantum circuit method. The optimal circuit structure will be identified based on gate counts and circuit depth. The algorithm will be tested on spin-boson models as well as on realistic systems, and the performance of trapped ions and superconducting devices will be compared. The success of the algorithm will offer quantum speedup in simulations of multi-state non-Markovian quantum dynamics at finite temperature. A user-friendly and open-source platform will be put forward such that, with input parameters, dynamical simulations on a quantum computer can be carried out and the results analyzed. This work could potentially inspire future quantum algorithm design for simulating the dynamics of open quantum systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在化学理论，化学分区中的模型和计算方法计划的支持下，乔治·梅森大学（George Mason University）的Fei Wang将致力于开发有效的量子算法，以在量子计算机上执行冷凝的相位量子动力学模拟。许多重要的物理和化学过程发生在凝结阶段，跨越溶液中的化学反应，在半导体界面处的电荷转移以及分子聚集体中的太阳能转化。对这些过程的科学研究不仅促进了我们的基本理解，还为材料设计和环境可持续性提供了实用的解决方案。由于许多这些过程涉及电荷迁移和激发能量转移，因此涉及许多自由度的量子动态对于它们的描述至关重要。但是，此类模拟是古典计算机上的资源密集型。另一方面，量子计算机自然适合量子模拟。随着算法的开发，Wang博士的目标是在凝结相中显示量子动力学模拟的量子加速度，并在量子模拟领域中证明了量子计算的实际应用。参与该项目的研究生和博士后研究人员将接受量子信息科学和最先进的量子模拟工具的严格培训。通过向本科生和高中生提供的实习计划，PI将支持代表性不足且经济弱势群体的团体。这些努力不仅会鼓励广泛参与STEM（科学，技术，工程和数学），而且还可以帮助教育未来的量子劳动力，以了解学术界和行业的职业。这项工作的重点是为有限温度的非马克维亚时间演化开发有效的量子算法，该算法为凝结相位量子动力学提供了一般框架。该项目的新进展将涵盖统一操作员的构建，有效的量子电路汇编，模型和实际系统模拟以及不同类型的量子设备之间的性能比较。将探索三种数学方法（单一扩张，单一值分解和单一操作员的线性组合），以实现单一转换为单位转换，并将根据复杂性理论评估它们的有效性。将研究两种通用方法进行电路汇编：一个执行精确的数学分解，另一种使用变异量子电路方法。最佳电路结构将根据门计数和电路深度确定。该算法将在自旋 - 玻璃模型和逼真的系统上进行测试，并且将比较捕获离子和超导设备的性能。该算法的成功将在有限温度下的多状态非马克维亚量子动力学的模拟中提供量子加速。将提出一个用户友好和开源的平台，以便可以在输入参数上进行量子计算机上的动态模拟并进行分析。这项工作可能会激发未来的量子算法设计，以模拟开放量子系统的动态。该奖项反映了NSF的法定任务，并且使用基金会的智力优点和更广泛的审查标准，被认为值得通过评估来获得支持。

项目成果

Exact Non-Markovian Quantum Dynamics on the NISQ Device Using Kraus Operators

使用 Kraus 算子在 NISQ 设备上实现精确的非马尔可夫量子动力学

• DOI: 10.1021/acsomega.3c09720
• 发表时间: 2024
• 期刊: ACS Omega
• 影响因子: 4.1
• 作者: Seneviratne, Avin;Walters, Peter L.;Wang, Fei
• 通讯作者: Wang, Fei

Path integral quantum algorithm for simulating non-Markovian quantum dynamics in open quantum systems

用于模拟开放量子系统中非马尔可夫量子动力学的路径积分量子算法

• DOI: 10.1103/physrevresearch.6.013135
• 发表时间: 2024
• 期刊: Physical Review Research
• 影响因子: 4.2
• 作者: Walters, Peter L.;Wang, Fei
• 通讯作者: Wang, Fei