http://dspace.bsu.edu.ru/handle/123456789/64216| Title: | Search for low mass dark matter in DarkSide-50: the Bayesian network approach |
| Authors: | Agnes, P. Albuquerque, I. F. M. Alexander, T. Alton, A. K. Kubankin, A. Oleinik, A. Shchagin, A. |
| Keywords: | physics theoretical physics dark matter Bayesian networks Markov chain probability distribution functions background spectra detectors |
| Issue Date: | 2023 |
| Citation: | Search for low mass dark matter in DarkSide-50: the Bayesian network approach / P. Agnes, Albuquerque I.F.M., T. Alexander [et al.] // The European Physical Journal C. - 2023. - Vol.83, №4.-Art. 322. - Doi: 10.1140/epjc/s10052-023-11410-4. |
| Abstract: | The article presents a new approach to the search for dark matter in the DarkSide-50 experiment based on Bayesian networks. Having formulated the problem in terms of Bayesian networks, a logical inference algorithm based on a Markov chain Monte Carlo was developed to calculate the a posteriori probability |
| URI: | http://dspace.bsu.edu.ru/handle/123456789/64216 |
| Appears in Collections: | Статьи из периодических изданий и сборников (на иностранных языках) = Articles from periodicals and collections (in foreign languages) |
| File | Description | Size | Format | |
|---|---|---|---|---|
| Agnes_Search_Low_23.pdf | 1 MB | Adobe PDF | View/Open |
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