Bayesian analysis of time dependence of DAMA annual modulation amplitude

Bhagvati, S. and Desai, S. (2021) Bayesian analysis of time dependence of DAMA annual modulation amplitude. Journal of Cosmology and Astroparticle Physics, 2021 (9). 022. ISSN 14757516

Full text not available from this repository. (Request a copy)

Abstract

We implement a test of the variability of the per-cycle annual modulation amplitude in the different phases of the DAMA/LIBRA experiment using Bayesian model comparison. Using frequentist methods, a previous study 1 had demonstrated that the DAMA amplitudes spanning over the DAMA/NaI and the first phase of the DAMA/LIBRA phases, show a mild preference for time-dependence in multiple energy bins. With that motivation, we first show using Bayesian techniques that the aforementioned data analyzed in 1 show a moderate preference for exponentially varying amplitudes in the 2-5 and 2-6 keV energy intervals. We then carry out a similar analysis on the latest modulation amplitudes released by the DAMA collaboration from the first two phases of the upgraded DAMA/LIBRA experiment. We also analyze the single-hit residual rates released by the DAMA collaboration to further look for any possible time-dependency. However, we do not find any evidence for variability of either of the two datasets by using Bayesian model selection. All our analysis codes and datasets have been made publicly available. © 2021 IOP Publishing Ltd and Sissa Medialab.

[error in script]
IITH Creators:
IITH CreatorsORCiD
Desai, Shantanuhttp://orcid.org/0000-0002-0466-3288
Item Type: Article
Uncontrolled Keywords: dark matter detectors, dark matter experiments
Subjects: Physics
Divisions: Department of Physics
Depositing User: Mrs Haseena VKKM
Date Deposited: 17 Feb 2022 05:16
Last Modified: 17 Feb 2022 05:16
URI: http://raiithold.iith.ac.in/id/eprint/9171
Publisher URL: https://iopscience.iop.org/article/10.1088/1475-75...
OA policy: https://v2.sherpa.ac.uk/id/publication/11312
Related URLs:

Actions (login required)

View Item View Item
Statistics for RAIITH ePrint 9171 Statistics for this ePrint Item