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Trapped Ion Quantum Computing Quantum Simulation

Eliminating Incoherent Noise: A Coherent Quantum Approach in Multi-Sensor Dark Matter Detection

arXiv
Authors: Jing Shu, Bin Xu, Yuan Xu

Year

2024

Paper ID

37503

Status

Preprint

Abstract Read

~2 min

Abstract Words

129

Citations

N/A

Abstract

We propose a novel dark matter detection scheme by leveraging quantum coherence across a network of multiple quantum sensors. This method effectively eliminates incoherent background noise, thereby significantly enhancing detection sensitivity. This is achieved by performing a series of basis transformation operations, allowing the coherent signal to be expressed as a combination of sensor population measurements without introducing background noise. We present a comprehensive analytical analysis and complement it with practical numerical simulations. These demonstrations reveal that signal strength is enhanced by the square of the number of sensors, while noise, primarily due to operational infidelity rather than background fluctuations, increases only linearly with the number of sensors. Our approach paves the way for next-generation dark matter searches that optimally utilize an advanced network of sensors and quantum technologies.

Why This Paper Matters

  • This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
  • It adds a 2024 reference point for readers tracking recent quantum research.
  • We propose a novel dark matter detection scheme by leveraging quantum coherence across a network of multiple quantum sensors.

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