Abstract
We perform an independent search for annual modulation caused by dark matter-induced scatterings in the recently released COSINE-100 data. 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 frequentist, information theoretic techniques (such as AIC and BIC), and also using the Bayesian model comparison technique. 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. The Bayesian test however strongly prefers a background model. This is the first proof of principles demonstration of application of Bayesian and information theory based techniques to COSINE-100 data to assess the significance of annual modulation.
Highlights
About 25% of the universe’s matter density consists of cold dark matter (Planck Collaboration et al 2018), we have no clue about the mass of the dark matter particle or its non-gravitational couplings (Jungman et al 1996)
The Bayesian test strongly prefers a background model. This is the first proof of principles demonstration of application of Bayesian and information theory based techniques to COSINE-100 data to assess the significance of annual modulation
Herrero-Garcia et al 2012; Catena et al 2016; Nobile et al 2015; Herrero-Garcia et al 2018; Kang et al 2019, and references therein) have been made to reconcile the results of DAMA with the null results of other experiments using non-standard particle physics or astrophysics assumptions, the jury is still out on whether any of them can satisfactorily reconcile with the latest results from all the direct detection experiments
Summary
About 25% of the universe’s matter density consists of cold dark matter (Planck Collaboration et al 2018), we have no clue about the mass of the dark matter particle or its non-gravitational couplings (Jungman et al 1996). The COSINE-100 experiment (Adhikari et al 2019) is one of the first experiments, whose detector is designed to be a replica of the DAMA target, and can confirm or refute their annual modulation claims in a model-independent fashion. In a recent work (Krishak et al 2019), we did an independent assessment of the DAMA/LIBRA annual modulation claims from their most recent data release, using three disparate model comparison techniques: frequentist (Desai 2016), Bayesian (Trotta 2017; Kerscher and Weller 2019), and information theoretic techniques (Liddle 2004, 2007). The Bayesian and information theoretical techniques are widely used for model comparison in Astrophysics and Cosmology, but rarely used in direct dark matter detection experiments.
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