ARQUIN : Architectures for Multinode Superconducting Quantum Computers

Author:

Ang James12ORCID,Carini Gabriella32ORCID,Chen Yanzhu42ORCID,Chuang Isaac52ORCID,DeMarco Michael352ORCID,Economou Sophia42ORCID,Eickbusch Alec62ORCID,Faraon Andrei782ORCID,Fu Kai-Mei92ORCID,Girvin Steven62ORCID,Hatridge Michael102ORCID,Houck Andrew112ORCID,Hilaire Paul42ORCID,Krsulich Kevin82ORCID,Li Ang12ORCID,Liu Chenxu412ORCID,Liu Yuan52ORCID,Martonosi Margaret112ORCID,McKay David82ORCID,Misewich Jim32ORCID,Ritter Mark82ORCID,Schoelkopf Robert62ORCID,Stein Samuel12ORCID,Sussman Sara112ORCID,Tang Hong62ORCID,Tang Wei122ORCID,tomesh teague112ORCID,Tubman Norm132ORCID,Wang Chen142ORCID,Wiebe Nathan1512ORCID,Yao Yongxin16172ORCID,Yost Dillon132ORCID,Zhou Yiyu62ORCID

Affiliation:

1. Pacific Northwest National Laboratory, Richland, United States

2. No address

3. Brookhaven National Laboratory, Upton, United States

4. Virginia Tech, Blacksburg, United States

5. Massachusetts Institute of Technology, Cambridge, United States

6. Yale University, New Haven, United States

7. Caltech, Pasadena, United States

8. IBM TJ Watson Research Center, Yorktown Heights, United States

9. University of Washington, Seattle, United States

10. University of Pittsburgh, Pittsburgh, United States

11. Princeton University, Princeton, United States

12. Computer Science, Princeton University, Princeton, United States

13. NASA Ames Research Center, Moffett Field, United States

14. University of Massachusetts Amherst, Amherst, United States

15. University of Toronto, Toronto, Canada

16. Ames Laboratory, Ames, United States

17. Kent State University, Kent, United States

Abstract

Many proposals to scale quantum technology rely on modular or distributed designs wherein individual quantum processors, called nodes, are linked together to form one large multinode quantum computer (MNQC). One scalable method to construct an MNQC is using superconducting quantum systems with optical interconnects. However, internode gates in these systems may be two to three orders of magnitude noisier and slower than local operations. Surmounting the limitations of internode gates will require improvements in entanglement generation, use of entanglement distillation, and optimized software and compilers. Still, it remains unclear what performance is possible with current hardware and what performance algorithms require. In this paper, we employ a systems analysis approach to quantify overall MNQC performance in terms of hardware models of internode links, entanglement distillation, and local architecture. We show how to navigate tradeoffs in entanglement generation and distillation in the context of algorithm performance, lay out how compilers and software should balance between local and internode gates, and discuss when noisy quantum internode links have an advantage over purely classical links. We find that a factor of 10-100x better link performance is required and introduce a research roadmap for the co-design of hardware and software towards the realization of early MNQCs. While we focus on superconducting devices with optical interconnects, our approach is general across MNQC implementations

Publisher

Association for Computing Machinery (ACM)

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