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HK: Fachverband Physik der Hadronen und Kerne
HK 17: Heavy-Ion Collisions and QCD Phases III
HK 17.3: Vortrag
Mittwoch, 1. September 2021, 17:15–17:30, H1
Machine Learning Application for Λ Hyperon Reconstruction in CBM at FAIR — •Shahid Khan1, Ali Imdad Khan1, Viktor Klochkov1, Olha Lavoryk2, Oleksii Lubynets3,4, Andrea Dubla3, and Ilya Selyuzhenkov3,5 for the CBM collaboration — 1University of Tübingen — 2University of Kyiv — 3GSI, Darmstadt — 4University of Frankfurt — 5NRNU MEPhI, Moscow
The Compressed Baryonic Matter (CBM) experiment at FAIR will investigate the QCD phase diagram in the region of high net-baryon densities (B > 500 MeV) in the collision energy range of √sNN = 2.7-4.9 GeV with high interaction rate, up to 10 MHz, provided by the SIS100 accelerator. Enhanced production of strange baryons can signal a transition to a new phase of the QCD matter. Λ hyperons are the most abundantly produced strange baryons. They weakly decay, with a branching ratio of 64%, into a proton (p+) and a pion (π−). To reconstruct the Λ → p++π− decay kinematics, Particle-Finder Simple package is used. It uses the mathematics of the Kalman Filter Particle package and provides a convenient interface to control the reconstruction parameters. For the reduction of combinatorial background specific selection criteria need to be applied to the proton and π− tracks and Λ-candidates decay topology.
In this work, the performance for Λ reconstruction in CBM with Machine Learning algorithms such as XGBoost will be presented. These algorithms allow efficient, non-linear and multi-dimensional selection criteria to be implemented whilst achieving high signal to background ratio in the region around the Λ candidate invariant mass peak.