Details

Autor(en) / Beteiligte

• Palken, D. A.
• Brubaker, B. M.
• Malnou, M.
• Kenany, S. Al
• Backes, K. M.
• Cahn, S. B.
• Gurevich, Y. V.
• Lamoreaux, S. K.
• Lewis, S. M.
• Maruyama, R. H.
• Rapidis, N. M.
• Root, J. R.
• Simanovskaia, M.
• Shokair, T. M.
• Singh, Sukhman
• Speller, D. H.
• Urdinaran, I.
• van Bibber, K.
• Zhong, L.
• Lehnert, K. W.

Titel

Improved analysis framework for axion dark matter searches

Ist Teil von

• Physical review. D, 2020-06, Vol.101 (12), p.1, Article 123011

Ort / Verlag

College Park: American Physical Society

Erscheinungsjahr

2020

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• In experiments searching for axionic dark matter, the use of the standard threshold-based data analysis discards valuable information. We present a Bayesian analysis framework that builds on an existing processing protocol [B. M. Brubaker, L. Zhong, S. K. Lamoreaux, K. W. Lehnert, and K. A. van Bibber, Phys. Rev. D 96, 123008 (2017)] to extract more information from the data of coherent axion detectors such as operating haloscopes. The analysis avoids logical subtleties that accompany the standard analysis framework and enables greater experimental flexibility on future data runs. Performing this analysis on the existing data from the HAYSTAC experiment, we find improved constraints on the axion-photon coupling gγ while also identifying the most promising regions of parameter space within the 23.15 – 24.0 μ eV mass range. A comparison with the standard threshold analysis suggests a 36% improvement in scan rate from our analysis, demonstrating the utility of this framework for future axion haloscope analyses.