Revealing the dark matter halo with axion direct detection
The next generation of axion direct-detection experiments may rule out or confirm axions as the dominant source of dark matter. We develop a general likelihood-based framework for studying the time-series data at such experiments, with a focus on the role of dark matter astrophysics, to search for s...
Main Authors: | , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
American Physical Society
2018
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Online Access: | http://hdl.handle.net/1721.1/116445 https://orcid.org/0000-0003-3472-7606 |
Summary: | The next generation of axion direct-detection experiments may rule out or confirm axions as the dominant source of dark matter. We develop a general likelihood-based framework for studying the time-series data at such experiments, with a focus on the role of dark matter astrophysics, to search for signatures of the QCD axion or axionlike particles. We illustrate how in the event of a detection the likelihood framework may be used to extract measures of the local dark matter phase-space distribution, accounting for effects such as annual modulation and gravitational focusing, which is the perturbation to the dark matter phase-space distribution by the gravitational field of the Sun. Moreover, we show how potential dark matter substructure, such as cold dark matter streams or a thick dark disk, could impact the signal. For example, we find that when the bulk dark matter halo is detected at 5σ global significance, the unique time-dependent features imprinted by the dark matter component of the Sagittarius stream, even if only a few percent of the local dark matter density, may be detectable at ∼2σ significance. A corotating dark disk, with lag speed ∼50 km/s, that is ∼20% of the local dark matter density could dominate the signal, while colder but as-of-yet unknown substructure may be even more important. Our likelihood formalism, and the results derived with it, are generally applicable to any time-series-based approach to axion direct detection. |
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