Search for Annual Modulation in Combined ANAIS 112 and COSINE 100 Data using Bayesian Model Comparison

TL;DR

This study tests for a dark matter–induced annual modulation in the combined COSINE-100 and ANAIS-112 data by performing a Bayesian model comparison between a cosine modulation and a constant-background hypothesis. Four prior configurations on the modulation parameters are explored, and the Bayesian evidence is computed via a Gaussian likelihood on 15-day residuals using Dynesty. For both the $1-6$ keV and $2-6$ keV intervals, the natural log Bayes factor satisfies $\ln(B_{21}) < 1.15$, indicating no evidence for a dark matter–like annual modulation and consistency with previous C25 results. The authors also provide public access to their analysis code, enhancing transparency and reproducibility.

Abstract

We perform a Bayesian model comparison test between a sinusoidal modulation model and a constant value model using about three years of combined COSINE-100 and ANAIS-112 data. We use both uniform priors and normal priors (based on DAMA best-fit values) for the angular frequency and phase of the cosine signal. We find natural log of Bayes factor for the cosine model comapred to the constant value model to be less than 1.15 for the data in both 1-6 keV and 2-6 keV energy intervals. This shows that there is no evidence for cosine signal from dark matter interactions in the combined ANAIS-112/COSINE-100 data. Our analysis codes have also been made publicly available.