CAREER: Efficient and Effective Quantum Program Optimization in the High-Dimensional Space
职业:高维空间中高效且有效的量子程序优化
基本信息
- 批准号:2338773
- 负责人:
- 金额:$ 75.63万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2024
- 资助国家:美国
- 起止时间:2024-10-01 至 2029-09-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Quantum computing holds immense potential for revolutionizing technology in many domains, such as physics, chemistry, material science, optimization, etc. Currently, quantum hardware advancements outpace the corresponding software capabilities, and this project aims to bridge the gap between quantum hardware capabilities and software compiler optimizations. Existing quantum compiler optimizations mostly only perform local small-scale transformations and a large optimization space remains untouched. This project aims to reshape the quantum compiler infrastructure with novel programming languages and optimization methods, which will systematically enable more effective and efficient large-scale program optimizations across high-dimensional quantum spaces and compiler support for more diverse quantum hardware platforms beyond traditional quantum bits. The project's interdisciplinary nature stimulates collaboration across various domains and its technical advancements lay the foundation for unlocking the full potential of quantum computing. This project also supports education initiatives and training opportunities for both academic and industrial participants, nurturing a skilled quantum computing workforce for societal advancement.This project will significantly enhance the performance of quantum computing software by greatly improving the capability, applicability, and reliability of quantum compiler optimizations. Specifically, this project takes a three-pronged approach. First, this project will pioneer quantum algorithmic optimizations with high-level intermediate representations and corresponding compilation algorithms, enabling comprehensive quantum program optimizations across extensive qubit and operation ranges, thus drastically improving compiler efficiency and program performance. Second, this project seeks to expand compiler support beyond qubit-based systems to encompass diverse quantum hardware paradigms like continuous-variable quantum computing and analog quantum simulators. These efforts will broaden the quantum compiler infrastructure's adaptability, unlocking the potential of diverse quantum hardware landscapes. Third, this project will develop innovative testing and verification tools that can ensure the accuracy and scalability of high-dimensional quantum program optimizations, fostering the creation of dependable quantum software. The success of this research agenda will greatly enhance quantum compiler infrastructure and contribute to the realization of more powerful quantum computing technologies and applications.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.
量子计算在物理、化学、材料科学、优化等许多领域具有巨大的技术革命潜力。目前,量子硬件的进步超过了相应的软件能力,该项目旨在弥合量子硬件能力和软件编译器优化之间的差距。现有的量子编译器优化大多只执行局部小规模的转换,大的优化空间仍未触及。该项目旨在通过新颖的编程语言和优化方法重塑量子编译器基础设施,这将系统地实现跨高维量子空间的更有效和高效的大规模程序优化,并为传统量子比特之外的更多样化的量子硬件平台提供编译器支持。该项目的跨学科性质刺激了各个领域的合作,其技术进步为释放量子计算的全部潜力奠定了基础。该项目还为学术和工业参与者提供教育计划和培训机会,为社会进步培养熟练的量子计算人才。该项目将通过大大提高量子编译器优化的能力,适用性和可靠性,显着提高量子计算软件的性能。具体而言,该项目采取三管齐下的办法。首先,该项目将通过高级中间表示和相应的编译算法开创量子算法优化,从而在广泛的量子位和操作范围内实现全面的量子程序优化,从而大大提高编译效率和程序性能。其次,该项目旨在将编译器支持扩展到基于量子位的系统之外,以涵盖各种量子硬件范例,如连续变量量子计算和模拟量子模拟器。这些努力将扩大量子编译器基础设施的适应性,释放各种量子硬件环境的潜力。第三,该项目将开发创新的测试和验证工具,以确保高维量子程序优化的准确性和可扩展性,促进创建可靠的量子软件。这一研究议程的成功将极大地增强量子编译器基础设施,并有助于实现更强大的量子计算技术和应用。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(0)
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Gushu Li其他文献
QECV: Quantum Error Correction Verification
QECV:量子纠错验证
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Anbang Wu;Gushu Li;Hezi Zhang;G. Guerreschi;Yuan Xie;Yufei Ding - 通讯作者:
Yufei Ding
QASMTrans: A QASM Quantum Transpiler Framework for NISQ Devices
QASMTrans:适用于 NISQ 设备的 QASM 量子转译器框架
- DOI:
- 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Fei Hua;Meng Wang;Gushu Li;B. Peng;Chenxu Liu;Muqing Zheng;S. Stein;Yufei Ding;Eddy Z. Zhang;Travis Humble;Ang Li - 通讯作者:
Ang Li
Towards Efficient Ansatz Architecture for Variational Quantum Algorithms
面向变分量子算法的高效 Ansatz 架构
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Anbang Wu;Gushu Li;Yuke Wang;Boyuan Feng;Yufei Ding;Yuan Xie - 通讯作者:
Yuan Xie
Fermihedral: On the Optimal Compilation for Fermion-to-Qubit Encoding
费米面体:费米子到量子位编码的最佳编译
- DOI:
10.1145/3620666.3651371 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Yuhao Liu;Shize Che;Junyu Zhou;Yunong Shi;Gushu Li - 通讯作者:
Gushu Li
Gushu Li的其他文献
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