• Open Access

Quantum Enhancement in Dark Matter Detection with Quantum Computation

Shion Chen, Hajime Fukuda, Toshiaki Inada, Takeo Moroi, Tatsumi Nitta, and Thanaporn Sichanugrist
Phys. Rev. Lett. 133, 021801 – Published 8 July 2024

Abstract

We propose a novel method to significantly enhance the signal rate in qubit-based dark matter detection experiments with the help of quantum interference. Various quantum sensors possess ideal properties for detecting wavelike dark matter, and qubits, commonly employed in quantum computers, are excellent candidates for dark matter detectors. We demonstrate that, by designing an appropriate quantum circuit to manipulate the qubits, the signal rate scales proportionally to nq2, with nq being the number of sensor qubits, rather than linearly with nq. Consequently, in the dark matter detection with a substantial number of sensor qubits, a significant increase in the signal rate can be expected. We provide a specific example of a quantum circuit that achieves this enhancement by coherently combining the phase evolution in each individual qubit due to its interaction with dark matter. We also demonstrate that the circuit is fault tolerant to dephasing noises, a critical quantum noise source in quantum computers. The enhancement mechanism proposed here is applicable to various modalities for quantum computers, provided that the quantum operations relevant to enhancing the dark matter signal can be applied to these devices.

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  • Received 28 November 2023
  • Accepted 31 May 2024

DOI:https://doi.org/10.1103/PhysRevLett.133.021801

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI. Funded by SCOAP3.

Published by the American Physical Society

Physics Subject Headings (PhySH)

Particles & FieldsQuantum Information, Science & Technology

Authors & Affiliations

Shion Chen1, Hajime Fukuda2, Toshiaki Inada1, Takeo Moroi2,3, Tatsumi Nitta1, and Thanaporn Sichanugrist2,*

Article Text

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Issue

Vol. 133, Iss. 2 — 12 July 2024

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