Abstract Details

Name: Aditi Krishak
Affiliation: Indian Institute of Science Education and Research Bhopal
Conference ID: ASI2021_238
Title : Independent search for annual modulation in DAMA/LIBRA, COSINE-100 and ANAIS-112 data
Authors and Co-Authors : Aditi Krishak (Indian Institute of Science Education and Research Bhopal), Shantanu Desai (Indian Institute of Technology Hyderabad)
Abstract Type : Poster
Abstract Category : Extragalactic Astronomy
Abstract : DAMA/LIBRA, COSINE-100 and ANAIS-112 are dark matter detection experiments aimed to detect annual modulation induced by scatterings due to dark matter particles. The movement of the sun in the galaxy with respect to the Local Standards of Rest, along with the Earth’s revolution around the sun, should cause the detection of a peak flux of dark matter-induced interactions in June and a minimum in December, leading to a sinusoidal annual modulation in residual count rates of the experiments. For each experiment, we test the hypothesis that the data contains a sinusoidal modulation against the null hypothesis that the data consists of only background. We compare the significance using four different model comparison techniques, including frequentist, Bayesian, and two information theory-based criteria (AIC and BIC). For the DAMA/LIBRA data, we find that the sinusoidal model is decisively favored over the constant model using all the three techniques. For COSINE-100, the information theory-based tests mildly prefer a constant background over a sinusoidal signal with the same period as that found by the DAMA collaboration, while the Bayesian test strongly prefers a background model. In case of ANAIS-112, we find that according to the Bayesian model comparison test, the null hypothesis of no modulation is decisively favored over a cosine-based annual modulation for the non-background subtracted dataset in the 2–6 keV energy range, while none of the other model comparison tests decisively favor any one hypothesis over another. This is the first proof of principle demonstration of application of Bayesian and information theory based model comparison techniques to assess the significance of annual modulation in DAMA/LIBRA, COSINE-100 and ANAIS-112 data. All our analysis codes along with the data used in this work are publicly available.