Collaborative Research: EAGER: QIA: Large Scale QAOA Quantum Simulator

合作研究：EAGER：QIA：大规模 QAOA 量子模拟器

基本信息

批准号：
2122793
负责人：
Ilya Safro
金额：
$ 10万
依托单位：
University of Delaware
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-10-01 至 2023-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2122793&HistoricalAwards=false
关键词：
Collaborative Research EAGER QIA Large

项目摘要

The goal of this project is to develop a specialized Quantum Approximate Optimization Algorithm (QAOA) quantum circuit simulator. QAOA is the most studied quantum optimization algorithm and is considered to be the prime candidate for demonstrating quantum advantage. There is a worldwide race underway amongst top quantum information science researchers to find combinatorial optimization problems and their instances that run efficiently and faster on quantum devices rather than on classical computers. One of the critical bottlenecks is to find circuit parameters faster on a classical computer to accelerate variational quantum-classical frameworks. The expected improvements to the developed simulator will dramatically increase the speed of QAOA simulations by at least one order of magnitude and significantly speed up research done on finding optimal QAOA circuit parameters. As a result, it will help the realization of quantum advantage by US scientists in this highly competitive field of science.The technical goal of this project is to carry out computational and algorithmic investigations in various node elimination methods for tensor contraction in the development of a scalable quantum simulator. The plan is to build upon the success of the combinatorial scientific computing community in developing elimination algorithms for such tasks as minimizing the error and complexity in matrix computations and optimizing the time and space complexity in automatic differentiation, and recent developments in treewidth optimization algorithms. Additionally, in this project, emphasis will be placed on scaling up relevant graph algorithms to achieve acceptable time/quality trade-off for large-scale quantum simulators. Algorithmic and software products of this project will include a specialized QAOA quantum circuit open-source simulator equipped with fast optimization algorithms to accelerate tensor contraction methods. A high-quality simulator that scales to sufficiently large circuits is one of the major bottlenecks in discovering applications for demonstrating quantum advantage.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.

该项目的目的是开发专门的量子近似优化算法（QAOA）量子电路模拟器。 QAOA是研究最多的量子优化算法，被认为是证明量子优势的主要候选者。顶级量子信息科学研究人员之间正在进行全球竞赛，以发现组合优化问题及其实例在量子设备上而不是在古典计算机上有效，更快地运行。关键的瓶颈之一是在经典计算机上更快地找到电路参数，以加速变化量子经典框架。对开发的模拟器的预期改进将大大提高QAOA模拟的速度，至少一个数量级，并显着加快了有关找到最佳QAOA电路参数的研究。结果，它将有助于实现美国科学家在这个竞争激烈的科学领域中实现量子优势。该项目的技术目标是在各种节点消除方法中进行计算和算法研究，以在开发可扩展的量子模拟器的开发中进行张量收缩。该计划是基于组合科学计算社区在开发消除算法的成功基础上，诸如将矩阵计算中的误差和复杂性最小化，并优化自动差异化的时间和空间复杂性，以及在树宽优化算法中的最新发展。此外，在此项目中，将重点放在扩展相关的图形算法上，以实现大规模量子模拟器的可接受时间/质量权衡。该项目的算法和软件产品将包括配备快速优化算法的专业QAOA量子电路开源模拟器，以加速张量收缩方法。将扩展到足够大的电路的高质量模拟器是发现证明量子优势的应用的主要瓶颈之一。该奖项反映了NSF的法定任务，并被认为值得通过基金会的知识分子优点和更广泛的影响标准通过评估来进行评估。