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arXiv · 2109.02435

Machine Learning Application for $\mathbf{\Lambda}$ Hyperon Reconstruction in CBM at FAIR

Shahid Khan·Viktor Klochkov·Olha Lavoryk·Oleksii Lubynets·Ali Imdad Khan·Andrea Dubla·Ilya Selyuzhenkov
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Abstract

The Compressed Baryonic Matter experiment at FAIR will investigate the QCD phase diagram in the region of high net-baryon densities. Enhanced production of strange baryons, such as the most abundantly produced $\Lambda$ hyperons, can signal transition to a new phase of the QCD matter. In this work, the CBM performance for reconstruction of the $\Lambda$ hyperon via its decay to proton and $\pi^{-}$ is presented. Decay topology reconstruction is implemented in the Particle-Finder Simple (PFSimple) package with Machine Learning algorithms providing efficient selection of the decays and high signal to background ratio.

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Shahid Khan, Viktor Klochkov, Olha Lavoryk, Oleksii Lubynets, Ali Imdad Khan, Andrea Dubla, Ilya Selyuzhenkov. 2021-08-30. Machine Learning Application for $\mathbf{\Lambda}$ Hyperon Reconstruction in CBM at FAIR. https://doi.org/10.1051/epjconf/202225913008

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