| DC Field | Value | Language |
|---|
| dc.contributor.author | Agnes, P. | - |
| dc.contributor.author | Albuquerque, I. F. M. | - |
| dc.contributor.author | Alexander, T. | - |
| dc.contributor.author | Alton, A. K. | - |
| dc.contributor.author | Kubankin, A. | - |
| dc.contributor.author | Oleinik, A. | - |
| dc.contributor.author | Shchagin, A. | - |
| dc.date.accessioned | 2024-12-24T12:46:54Z | - |
| dc.date.available | 2024-12-24T12:46:54Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.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. | ru |
| dc.identifier.uri | http://dspace.bsu.edu.ru/handle/123456789/64216 | - |
| dc.description.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 | ru |
| dc.language.iso | en | ru |
| dc.subject | physics | ru |
| dc.subject | theoretical physics | ru |
| dc.subject | dark matter | ru |
| dc.subject | Bayesian networks | ru |
| dc.subject | Markov chain | ru |
| dc.subject | probability distribution functions | ru |
| dc.subject | background spectra | ru |
| dc.subject | detectors | ru |
| dc.title | Search for low mass dark matter in DarkSide-50: the Bayesian network approach | ru |
| dc.type | Article | ru |
| Appears in Collections: | Статьи из периодических изданий и сборников (на иностранных языках) = Articles from periodicals and collections (in foreign languages)
|
