# An independent assessment of significance of annual modulation in COSINE-100 data

## TL;DR

This study independently tests for annual modulation signals in COSINE-100 dark matter data using Bayesian and information-theoretic methods, finding no significant evidence for such modulation.

## Contribution

It introduces the first application of Bayesian and information theory techniques to assess annual modulation significance in COSINE-100 data.

## Key findings

- Information theory tests favor a constant background over modulation.
- Bayesian analysis strongly supports the background-only model.
- No significant annual modulation signal detected in the data.

## 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.