21-25 March 2022
Academia Sinica
Europe/Zurich timezone

The automatic reconstruction of the particles with machine learning at e+e- collider

Mar 24, 2022, 11:20 AM
Room 1

Room 1

Oral Presentation Track 1: Physics (including HEP) and Engineering Applications Physics & Engineering


Dr Kyungho Kim (KISTI) Prof. Kihyeon Cho (KISTI/UST)


We have studied the automatic reconstruction of particles at e+e- collider, especially B meson, using machine learning algorithm. The main purpose of the research with e+e- collider is to precisely measure the Standard Model and search for the evidence of New Physics beyond the Standard Model. The analyses of B meson are the main objects for e+e- collider. A pair of B meson are created from e+e- collider and one of them are regarded as signal and reconstructed. Automatic reconstruction of other B makes it possible to improve the quality of events by utilizing information provided by other B, even in a situation where complete reconstruction of signal B is impossible due to non-searchable particles, such as neutrino, are included in the decay mode. In order to take advantage of automatic reconstruction, a ‘tagging’ method has been developed and used in B meson analyses with e+e- collider. We introduce the tagging method of ‘other’ B meson using machine learning algorithm. We have applied the method of automatic reconstruction and checked the effect of it when studying one of lepton-flavor-violating decay modes with simulated samples.

Primary authors

Dr Kyungho Kim (KISTI) Prof. Kihyeon Cho (KISTI/UST)

Presentation materials