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| Funder | National Science Foundation (US) |
|---|---|
| Recipient Organization | University of Pennsylvania |
| Country | United States |
| Start Date | Oct 01, 2024 |
| End Date | Sep 30, 2029 |
| Duration | 1,825 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | National Science Foundation (US) |
| Grant ID | 2338773 |
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.
University of Pennsylvania
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