Award Abstract # 1818914
PFCQC: STAQ: Software-Tailored Architecture for Quantum co-design

NSF Org: PHY
Division Of Physics
Recipient: DUKE UNIVERSITY
Initial Amendment Date: August 6, 2018
Latest Amendment Date: July 19, 2022
Award Number: 1818914
Award Instrument: Cooperative Agreement
Program Manager: Bogdan Mihaila
bmihaila@nsf.gov
 (703)292-8235
PHY
 Division Of Physics
MPS
 Directorate for Mathematical and Physical Sciences
Start Date: August 1, 2018
End Date: July 31, 2024 (Estimated)
Total Intended Award Amount: $14,999,998.00
Total Awarded Amount to Date: $15,811,123.00
Funds Obligated to Date: FY 2018 = $3,436,105.00
FY 2019 = $2,987,047.00

FY 2020 = $4,348,894.00

FY 2021 = $2,254,293.00

FY 2022 = $2,784,784.00
History of Investigator:
  • Kenneth Brown (Principal Investigator)
    kenneth.r.brown@duke.edu
  • Jungsang Kim (Co-Principal Investigator)
Recipient Sponsored Research Office: Duke University
2200 W MAIN ST
DURHAM
NC  US  27705-4640
(919)684-3030
Sponsor Congressional District: 04
Primary Place of Performance: Duke University
NC  US  27708-0921
Primary Place of Performance
Congressional District:
04
Unique Entity Identifier (UEI): TP7EK8DZV6N5
Parent UEI:
NSF Program(s): FET-Fndtns of Emerging Tech,
FET-Fndtns of Emerging Tech,
NSF Multiplier,
OFFICE OF MULTIDISCIPLINARY AC,
EPMD-ElectrnPhoton&MagnDevices,
COMPUTATIONAL PHYSICS,
PHYSICS AT THE INFO FRONTIER,
Quantum Computing
Primary Program Source: 01002223DB NSF RESEARCH & RELATED ACTIVIT
01001819DB NSF RESEARCH & RELATED ACTIVIT

01001920DB NSF RESEARCH & RELATED ACTIVIT

01002021DB NSF RESEARCH & RELATED ACTIVIT

01002122DB NSF RESEARCH & RELATED ACTIVIT

01002223DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s): 026Z, 057Z, 060Z, 5983, 7203, 7556, 8550
Program Element Code(s): 089y00, 089Y00, 091Y00, 125300, 151700, 724400, 755300, 792800
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.041, 47.049, 47.070

ABSTRACT

Over the past half century, economic growth was heavily driven by increasing computational power, which was crucial in enabling innovation, improving efficiency, and managing complexity in most industries. To continue this growth, it is critical to explore and vet new approaches for increasing computational power. Quantum computers are a promising form of advanced computational power, providing unmatched advantages in code breaking and scientific simulation problems in fields such as molecular chemistry and materials science. Quantum computing has advanced rapidly in recent years, and the hardware development is nearing a level of sophistication where it is possible to construct a quantum computer that may outperform classical computers in solving certain problems. The Software-Tailored Architecture for Quantum co-design (STAQ) project brings together a group of physicists, computer scientists, and engineers to construct a quantum computer capable of showing an advantage over current computer technology. The project also supports the development of educational tools and a quantum information workforce.

A quantum computer can exhibit an advantage over standard computers when the quantum computer is large enough that brute force simulation strategies become infeasible and a quantum algorithm is sufficiently complex that approximate computational methods do not provide accurate results. The STAQ project aims to utilize this quantum advantage by building ion trap quantum computers with 64 or more qubits and developing quantum algorithms suitable for noisy quantum devices. This ambitious task will be enabled by a software stack that optimally maps the quantum algorithms onto the ion trap device and allows for the algorithms and hardware to be designed together. The project requires a wide range of expertise to achieve the scientific goal. The team consists of ion trap experimentalists, quantum information theorists, and computer architects. STAQ will organize a Quantum Ideas School, which will recruit a diverse group of students into quantum information and help retrain current industrial scientists for this emerging field. This project advances the objectives of two of 10 Big Ideas for Future NSF Investments: "The Quantum Leap: Leading the Next Quantum Revolution" and "Growing Convergent Research at NSF". The 10 big ideas will push forward the frontiers of U.S. research, provide innovative approaches to solve some of the most pressing problems the world faces, as well as lead to discoveries not yet known. This project also advances the third objective of the National Strategic Computing Initiative (NSCI), an effort aimed at developing new technological capabilities in the post-Moore's Law era.

This project is supported by the Division of Physics in the Directorate for Mathematical and Physical Sciences, the Division of Computing and Communication Foundations in the Directorate for Computer and Information Science and Engineering, and the Division of Electrical, Communications and Cyber Systems in the Directorate for Engineering.

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.

PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH

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(Showing: 1 - 10 of 134)
Daiwei Zhu, Ze-Pei Cian "Cross-Platform Comparison of Arbitrary Quantum Computations" ArXivorg , 2021 Citation Details
Kushal Seetharam, Debopriyo Biswas "Digital quantum simulation of NMR experiments" ArXivorg , 2021 Citation Details
An, Dong and Liu, Jin-Peng and Lin, Lin "Linear Combination of Hamiltonian Simulation for Nonunitary Dynamics with Optimal State Preparation Cost" Physical Review Letters , v.131 , 2023 https://doi.org/10.1103/PhysRevLett.131.150603 Citation Details
Aniruddha Bapat, Andrew M. "Advantages and limitations of quantum routing" ArXivorg , 2022 Citation Details
Anshu, Anurag and Harrow, Aram W. and Soleimanifar, Mehdi "Entanglement spread area law in gapped ground states" Nature Physics , 2022 https://doi.org/10.1038/s41567-022-01740-7 Citation Details
Baker, Jonathan M. and Chong, Frederic T. "Emerging Technologies for Quantum Computing" IEEE Micro , v.41 , 2021 https://doi.org/10.1109/MM.2021.3099139 Citation Details
Balasubramanian, Shankar and Gopalakrishnan, Sarang and Khudorozhkov, Alexey and Lake, Ethan "Glassy Word Problems: Ultraslow Relaxation, Hilbert Space Jamming, and Computational Complexity" Physical Review X , v.14 , 2024 https://doi.org/10.1103/PhysRevX.14.021034 Citation Details
Bapat, Aniruddha and Childs, Andrew M. and Gorshkov, Alexey V. and King, Samuel and Schoute, Eddie and Shastri, Hrishee "Quantum routing with fast reversals" Quantum , v.5 , 2021 https://doi.org/10.22331/q-2021-08-31-533 Citation Details
Bapat, Aniruddha and Childs, Andrew M. and Gorshkov, Alexey V. and Schoute, Eddie "Advantages and Limitations of Quantum Routing" PRX Quantum , v.4 , 2023 https://doi.org/10.1103/PRXQuantum.4.010313 Citation Details
Belyansky, Ron and Bienias, Przemyslaw and Kharkov, Yaroslav A. and Gorshkov, Alexey V. and Swingle, Brian "Minimal Model for Fast Scrambling" Physical Review Letters , v.125 , 2020 https://doi.org/10.1103/PhysRevLett.125.130601 Citation Details
Bene Watts, Adam and Yunger Halpern, Nicole and Harrow, Aram "Nonlinear Bell inequality for macroscopic measurements" Physical Review A , v.103 , 2021 https://doi.org/10.1103/physreva.103.l010202 Citation Details
(Showing: 1 - 10 of 134)

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

The Software-Tailored Architecture for Quantum codesign (STAQ) project focused on increasing the performance of quantum computers by integrating research in hardware, software, and applications. The project developed ion trap quantum computers with control software capable of implementing a wide range of quantum simulations and computations.  This systems level approach to quantum computing revealed new research directions and opportunities. 

Quantum hardware was improved by building robust ion trap systems, designing laser control sequences, and understanding the physics leading to noise in ion trap quantum computers.  Scientific applications were expanded from an initial focus on chemistry and materials physics problems to science problems in high-energy physics.  The research in machine learning applications led to new methods for hybrid algorithms that use classical and quantum computation. Software research at the application layer revealed ways to compile the applications to greatly increase performance and runtime of quantum algorithms. Improved software at the control layer enabled more complex quantum experiments and the remote control of quantum devices. 

STAQ impacted the broader community by providing educational content, research tools, and increasing the quantum workforce. The annual STAQ Summer School engaged over 600 students outside the STAQ program. The lecture notes and videos from the summer school are available for download. The control system built for STAQ, the Duke Artiq eXtensions (DAX), is released under an open-source license and the DAX tools for debugging Artiq control systems are widely used. Most former students and postdoctoral scholars on the STAQ project remain engaged with quantum information science and engineering and currently work in academia, the quantum computing industry, or national laboratories.  

 


Last Modified: 11/26/2024
Modified by: Kenneth R Brown

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