Collaborative Research: EAGER: QIA: Large Scale QAOA Quantum Simulator
Collaborative Research: EAGER: QIA: Large Scale QAOA Quantum Simulator
批准号:
2122793
负责人:
Ilya Safro
金额:
$10.0万
依托单位:
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
项目状态:
已结题
起止时间:
2020-10-01 至 2023-09-30
中文摘要
点击翻译按钮获取中文摘要
英文摘要
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.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1109/hpec55821.2022.9926353
发表时间:
2022-09
期刊:
2022 IEEE High Performance Extreme Computing Conference (HPEC)
影响因子:
--
作者:
[Cameron Ibrahim;Danylo Lykov;Zichang He;Y. Alexeev;Ilya Safro]
通讯作者:
Cameron Ibrahim;Danylo Lykov;Zichang He;Y. Alexeev;Ilya Safro
RAPID: Automated discovery of COVID-19 related hypotheses using publicly available scientific literature
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批准号:2027864
-
项目类别:Standard Grant
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资助金额:$10.45万
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财政年份:2020
-
负责人:Ilya Safro
-
依托单位:
Collaborative Research: EAGER: QIA: Large Scale QAOA Quantum Simulator
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批准号:2035606
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项目类别:Standard Grant
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资助金额:$10.0万
-
财政年份:2020
-
负责人:Ilya Safro
-
依托单位:
RAPID: Automated discovery of COVID-19 related hypotheses using publicly available scientific literature
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批准号:2127776
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项目类别:Standard Grant
-
资助金额:$10.45万
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财政年份:2020
-
负责人:Ilya Safro
-
依托单位:
EAGER: SSDIM: Multiscale Methods for Generating Infrastructure Networks
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批准号:1745300
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项目类别:Standard Grant
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资助金额:$20.0万
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财政年份:2017
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负责人:Ilya Safro
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依托单位:
EAGER: Feedback-based Network Optimization for Smart Cities
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批准号:1647361
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项目类别:Standard Grant
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资助金额:$15.11万
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财政年份:2016
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负责人:Ilya Safro
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依托单位:
Fast and Scalable Multigrid Methods for Hypergraph Partitioning Problems
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批准号:1522751
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项目类别:Standard Grant
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资助金额:$18.0万
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财政年份:2015
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负责人:Ilya Safro
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依托单位:
国内基金
海外基金
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