Systems Architecture for Quantum Random Access Memory-Reference-Cited by-同舟云学术

Systems Architecture for Quantum Random Access Memory

Published:2023-10-28 Issue: Volume: Page:
ISSN:
Container-title:56th Annual IEEE/ACM International Symposium on Microarchitecture
language:
Short-container-title:

Author:

Xu Shifan¹^ORCID,Hann Connor T.²^ORCID,Foxman Ben³^ORCID,Girvin Steven M.⁴^ORCID,Ding Yongshan⁵^ORCID

Affiliation:

1. Departments of Physics and Applied Physics, Yale University, United States of America and Yale Quantum Institute, Yale University, USA

2. AWS Center for Quantum Computing, Amazon AWS, USA and IQIM, California Institute of Technology, USA

3. Department of Computer Science, Yale University, USA and Yale Quantum Institute, Yale University, USA

4. Departments of Physics and Applied Physics, Yale University, USA and Yale Quantum Institute, Yale University, USA

5. Department of Computer Science, Yale University, United States of America and Yale Quantum Institute, Yale University, USA

Funder

Air Force Office of Scientific Research

NSF (National Science Foundation)

Yale University

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3613424.3614270

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4. Jacob Biamonte , Peter Wittek , Nicola Pancotti , Patrick Rebentrost , Nathan Wiebe , and Seth Lloyd . 2017. Quantum machine learning. Nature 549, 7671 ( 2017 ), 195–202. Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd. 2017. Quantum machine learning. Nature 549, 7671 (2017), 195–202.

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