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arXiv:1707.05312 (physics)
[Submitted on 16 Jul 2017 (v1), last revised 17 Oct 2017 (this version, v3)]

Title:The Cosmic Axion Spin Precession Experiment (CASPEr): a dark-matter search with nuclear magnetic resonance

Authors:Antoine Garcon, Deniz Aybas, John W. Blanchard, Gary Centers, Nataniel L. Figueroa, Peter W. Graham, Derek F. Jackson Kimball, Surjeet Rajendran, Marina Gil Sendra, Alexander O. Sushkov, Lutz Trahms, Tao Wang, Arne Wickenbrock, Teng Wu, Dmitry Budker
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Abstract:The Cosmic Axion Spin Precession Experiment (CASPEr) is a nuclear magnetic resonance experiment (NMR) seeking to detect axion and axion-like particles which could make up the dark matter present in the universe. We review the predicted couplings of axions and axion-like particles with baryonic matter that enable their detection via NMR. We then describe two measurement schemes being implemented in CASPEr. The first method, presented in the original CASPEr proposal, consists of a resonant search via continuous-wave NMR spectroscopy. This method offers the highest sensitivity for frequencies ranging from a few Hz to hundreds of MHz, corresponding to masses $ m_{\rm a} \sim 10^{-14}$--$10^{-6}$ eV. Sub-Hz frequencies are typically difficult to probe with NMR due to the diminishing sensitivity of magnetometers in this region. To circumvent this limitation, we suggest new detection and data processing modalities. We describe a non-resonant frequency-modulation detection scheme, enabling searches from mHz to Hz frequencies ($m_{\rm a} \sim 10^{-17}$--$10^{-14} $ eV), extending the detection bandwidth by three decades.
Subjects: Instrumentation and Detectors (physics.ins-det); High Energy Physics - Phenomenology (hep-ph); Applied Physics (physics.app-ph); Data Analysis, Statistics and Probability (physics.data-an); Quantum Physics (quant-ph)
Cite as: arXiv:1707.05312 [physics.ins-det]
  (or arXiv:1707.05312v3 [physics.ins-det] for this version)
  https://doi.org/10.48550/arXiv.1707.05312
arXiv-issued DOI via DataCite
Journal reference: Quantum Science and Technology 2017
Related DOI: https://doi.org/10.1088/2058-9565/aa9861
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Submission history

From: Antoine Garcon AntoineGarcon [view email]
[v1] Sun, 16 Jul 2017 16:37:32 UTC (1,012 KB)
[v2] Sun, 15 Oct 2017 13:58:29 UTC (1,014 KB)
[v3] Tue, 17 Oct 2017 07:35:11 UTC (1,014 KB)
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