Report for the ASCR Workshop on Basic Research Needs in Quantum Computing and Networking - 2023

Technical Report · Tue Jul 11 04:00:00 EDT 2023

DOI:https://doi.org/10.2172/2001045· OSTI ID:2001045

Lougovski, Pavel ^[1]; Parekh, Ojas ^[2]; Broz, Joe ^[3]; Byrd, Mark ^[4]; Chapman, Joseph C. ^[5]; Chembo, Yanne ^[6]; de Jong, Wibe A. ^[7]; Figueroa, Eden ^[8]; Humble, Travis S. ^[5]; Larson, Jeffrey ^[9]; Quiroz, Gregory ^[10]; Ravi, Gokul ^[11]; Shammah, Nathan ^[12]; Svore, Krysta M. ^[13]; Wu, Wenji ^[7]; Zeng, William J. ^[12]

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1. Amazon Web Services, Seattle, WA (United States)
2. Sandia National Laboratories (SNL), Albuquerque, NM, and Livermore, CA (United States)
3. International Business Machines Corp., Armonk, NY (United States)
4. Southern Illinois University, Carbondale, IL (United States)
5. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
6. University of Maryland, College Park, MD (United States)
7. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
8. Stony Brook University, NY (United States)
9. Argonne National Laboratory (ANL), Argonne, IL (United States)
10. Johns Hopkins University, Baltimore, MD (United States)
11. Univ. of Michigan, Ann Arbor, MI (United States)
12. Unitary Fund, Walnut, CA (United States)
13. Microsoft Corporation, Redmond, WA (United States)

Employing quantum mechanical resources in computing and networking opens the door to new computation and communication models and potential disruptive advantages over classical counterparts. However, quantifying and realizing such advantages face extensive scientific and engineering challenges. Investments by the Department of Energy (DOE) have driven progress toward addressing such challenges. Quantum algorithms have been recently developed, in some cases offering asymptotic exponential advantages in speed or accuracy, for fundamental scientific problems such as simulating physical systems, solving systems of linear equations, or solving differential equations. Empirical demonstrations on nascent quantum hardware suggest better performance than classical analogs on specialized computational tasks favorable to the quantum computing systems. However, demonstration of an end-to-end, substantial and rigorously quantifiable quantum performance advantage over classical analogs remains a grand challenge, especially for problems of practical value. The definition of requirements for quantum technologies to exhibit scalable, rigorous, and transformative performance advantages for practical applications also remains an outstanding open question, namely, what will be required to ultimately demonstrate practical quantum advantage?

• Research Organization: USDOE Office of Science (SC) (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
• OSTI ID: 2001045
• Country of Publication: United States
• Language: English

Related Subjects

97 MATHEMATICS AND COMPUTING