Quantum-enhanced dark matter detection with in-cavity control: mitigating the Rayleigh curse

Haowei Shi, Anthony J. Brady, Wojciech Górecki, Lorenzo Maccone, Roberto Di Candia, Quntao Zhuang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The nature of dark matter is a fundamental puzzle in modern physics. A major approach of searching for dark matter relies on detecting feeble noise in microwave cavities. However, the quantum advantages of common quantum resources such as squeezing are intrinsically limited by the Rayleigh curse—a constant loss places a sensitivity upper bound on these quantum resources. In this paper, we propose an in situ transient control to mitigate such Rayleigh limit. The protocol consists of three steps: in-cavity quantum state preparation, axion accumulation with tunable time duration, and measurement. For the quantum source, we focus on the single-mode squeezed state (SMSS), and the entanglement-assisted case using signal-ancilla pairs in two-mode squeezed state (TMSS), where the ancilla does not interact with the axion. From quantum Fisher information rate evaluation, we derive the requirement of cavity quality factor, thermal noise level and squeezing gain for quantum advantage. When the squeezing gain becomes larger, the optimal axion accumulation time decreases, which reduces loss and mitigates the Rayleigh curse—i.e., the quantum advantage increases with the squeezing gain. Overall, we find that TMSS is more sensitive in the low-temperature limit. In the case of SMSS, as large gain is required for an advantage over vacuum, homodyne detection is sufficient to achieve optimality. Whereas, for TMSS, anti-squeezing and photon counting is optimal. Thanks to recent advances in magnetic field-resilient in-cavity squeezing and rapidly coupling out for photon counting, the proposed protocol is compatible with axion detection scenario.

Original languageEnglish (US)
Article number48
Journalnpj Quantum Information
Volume11
Issue number1
DOIs
StatePublished - Dec 2025
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Statistical and Nonlinear Physics
  • Computer Networks and Communications
  • Computational Theory and Mathematics

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