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Quantum Error Correction Fault Tolerance Quantum Machine Learning

Challenges in Scaling-up the Control Interface of a Quantum Computer

arXiv
Authors: D. J. Reilly

Year

2019

Paper ID

39981

Status

Preprint

Abstract Read

~2 min

Abstract Words

98

Citations

N/A

Abstract

Challenges at the quantum-classical interface are examined with the goal of architecting a scaled-up quantum computer comprising many thousands of qubits in the solid-state. Separating the distinct sub-systems of the interface that perform readout and control, general arguments are given for why distributing the components of these sub-systems over significant distances and across large temperature gradients presents a major challenge to scaling-up the technology. Largely addressing these issues, an architecture for the interface that leverages cryo-CMOS circuits proximal to the quantum plane is motivated in addition to protocols that enable massively parallel readout of qubits via frequency multiplexing.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2019 reference point for readers tracking recent quantum research.
  • Challenges at the quantum-classical interface are examined with the goal of architecting a scaled-up quantum computer comprising many thousands of qubits in the solid-state.

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References & Citation Signals

[1] DOI https://doi.org/arXiv:1912.05114 [2] arXiv https://arxiv.org/abs/1912.05114 [3] Publisher https://arxiv.org/abs/1912.05114

Local Citation Graph (Related-Paper Links)

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External citation index: OpenAlex citation signal

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