Improved background modeling for dark matter search with COSINE-100

G. H. Yu; N. Carlin; J. Y. Cho; J. J. Choi; S. Choi; A. C. Ezeribe; L. E. Franca; C. Ha; I. S. Hahn; S. J. Hollick; E. J. Jeon; H. W. Joo; W. G. Kang; M. Kauer; B. H. Kim; H. J. Kim; J. Kim; K. W. Kim; S. H. Kim; S. K. Kim; W. K. Kim; Y. D. Kim; Y. H. Kim; Y. J. Ko; D. H. Lee; E. K. Lee; H. Lee; H. S. Lee; H. Y. Lee; I. S. Lee; J. Lee; J. Y. Lee; M. H. Lee; S. H. Lee; S. M. Lee; Y. J. Lee; D. S. Leonard; N. T. Luan; B. B. Manzato; R. H. Maruyama; R. J. Neal; S. L. Olsen; B. J. Park; H. K. Park; H. S. Park; J. C. Park; K. S. Park; S. D. Park; R. L. C. Pitta; H. Prihtiadi; S. J. Ra; C. Rott; K. A. Shin; D. F. F. S. Cavalcante; M. K. Son; N. J. C. Spooner; L. T. Truc; L. Yang

arXiv · 2408.09806

Improved background modeling for dark matter search with COSINE-100

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Abstract

COSINE-100 aims to conclusively test the claimed dark matter annual modulation signal detected by DAMA/LIBRA collaboration. DAMA/LIBRA has released updated analysis results by lowering the energy threshold to 0.75 keV through various upgrades. They have consistently claimed to have observed the annual modulation. In COSINE-100, it is crucial to lower the energy threshold for a direct comparison with DAMA/LIBRA, which also enhances the sensitivity of the search for low-mass dark matter, enabling COSINE-100 to explore this area. Therefore, it is essential to have a precise and quantitative understanding of the background spectrum across all energy ranges. This study expands the background modeling from 0.7 to 4000 keV using 2.82 years of COSINE-100 data. The modeling has been improved to describe the background spectrum across all energy ranges accurately. Assessments of the background spectrum are presented, considering the nonproportionality of NaI(Tl) crystals at both low and high energies and the characteristic X-rays produced by the interaction of external backgrounds with materials such as copper. Additionally, constraints on the fit parameters obtained from the alpha spectrum modeling fit are integrated into this model. These improvements are detailed in the paper.

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G. H. Yu, N. Carlin, J. Y. Cho, J. J. Choi, S. Choi, A. C. Ezeribe, L. E. Franca, C. Ha, I. S. Hahn, S. J. Hollick, E. J. Jeon, H. W. Joo, W. G. Kang, M. Kauer, B. H. Kim, H. J. Kim, J. Kim, K. W. Kim, S. H. Kim, S. K. Kim, W. K. Kim, Y. D. Kim, Y. H. Kim, Y. J. Ko, D. H. Lee, E. K. Lee, H. Lee, H. S. Lee, H. Y. Lee, I. S. Lee, J. Lee, J. Y. Lee, M. H. Lee, S. H. Lee, S. M. Lee, Y. J. Lee, D. S. Leonard, N. T. Luan, B. B. Manzato, R. H. Maruyama, R. J. Neal, S. L. Olsen, B. J. Park, H. K. Park, H. S. Park, J. C. Park, K. S. Park, S. D. Park, R. L. C. Pitta, H. Prihtiadi, S. J. Ra, C. Rott, K. A. Shin, D. F. F. S. Cavalcante, M. K. Son, N. J. C. Spooner, L. T. Truc, L. Yang. 2024-08-19. Improved background modeling for dark matter search with COSINE-100. https://arxiv.org/abs/2408.09806

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