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Machine Learning approach to $\gamma/\pi^0$ separation in the LHCb calorimeter
Reconstruction and identification of particles in calorimeters of modern High Energy Physics experiments is a complicated task. Solutions are usually driven by a priori knowledge about expected properties of reconstructed objects. Such an approach is also used to distinguish single photons in the el...
| Autores principales: | , |
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| Lenguaje: | eng |
| Publicado: |
2018
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1088/1742-6596/1085/4/042036 http://cds.cern.ch/record/2664842 |