Architectures for Multinode Superconducting Quantum Computers
James Ang, Gabriella Carini, Yanzhu Chen, Isaac Chuang, Michael Austin, DeMarco, Sophia E. Economou, Alec Eickbusch, Andrei Faraon, Kai-Mei Fu,, Steven M. Girvin, Michael Hatridge, Andrew Houck, Paul Hilaire, Kevin, Krsulich, Ang Li, Chenxu Liu, Yuan Liu, Margaret Martonosi

TL;DR
This paper analyzes the performance tradeoffs in multinode superconducting quantum computers using optical links, proposing a co-design approach to optimize hardware and software components for scalable quantum systems.
Contribution
It introduces a co-design framework to quantify and optimize the performance of MNQCs, addressing the interplay of entanglement, hardware, and software improvements.
Findings
Tradeoff between entanglement generation and distillation affects performance.
Optimized compiler strategies can improve overall system efficiency.
Noisy quantum links can sometimes outperform classical links under certain conditions.
Abstract
Many proposals to scale quantum technology rely on modular or distributed designs where 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, a limiting factor of these machines will be internode gates, which may be two to three orders of magnitude noisier and slower than local operations. Surmounting the limitations of internode gates will require a range of techniques, including improvements in entanglement generation, the use of entanglement distillation, and optimized software and compilers, and it remains unclear how improvements to these components interact to affect overall system performance, what performance from each is required, or even how to quantify the performance of each. In this paper, we…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Quantum and electron transport phenomena
