Machine learning based TOF charged particle identification at BM@N detector of NICA collider
| Autor: | M. M. Stepanova, S. P. Merts, S. A. Nemnyugin, Vladimir Roudnev |
|---|---|
| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Journal of Physics: Conference Series. 1479:012043 |
| ISSN: | 1742-6596 1742-6588 |
| DOI: | 10.1088/1742-6596/1479/1/012043 |
| Popis: | In the article results of charged particles identification for BM@N experiment being performed at NICA acceleration complex of Joint Institute for Nuclear Research are presented. A standard neural network-based technique of constructing a classificator is applied to the data sets obtained both from modelling of a realistic experimental setup and three synthetic data sets. The carried-out analysis demonstrates that the estimated data accuracy is insufficient to make a clear distinction between electrons, muons and pions, and also between -particles and deutrons. The problem could be solved by using an extra data from the detector or by improving the accuracy of the experimental data by two orders of magnitude. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|