Track reconstruction at LHC as a collaborative data challenge use case with RAMP

¹ University of Geneva, Switzerland
² Karlsruhe Institute of Technology, Germany
³ Lawrence Berkeley National Laboratory, CA, USA
⁴ LAL and LRI, Orsay, France
⁵ LPNHE, Paris, France
⁶ LRI and Université Paris-Saclay, France
⁷ Yandex School of Data Analysis (YSDA), Moscow, Russia
⁸ CERN, Geneva, Switzerland
⁹ LAL, Univ. Paris-Sud, CNRS/IN2P3, Université Paris-Saclay, Orsay, France
¹⁰ Center for Data Science, Université Paris-Saclay, France
¹¹ Max Planck Institute for Physics, Munich, Germany
¹² Higher School of Economics (HSE), Moscow, Russia
¹³ California Institute of Technology, CA, Germany
¹⁴ University of Bonn, Germany

Published online: 8 August 2017

Abstract

Charged particle track reconstruction is a major component of data-processing in high-energy physics experiments such as those at the Large Hadron Collider (LHC), and is foreseen to become more and more challenging with higher collision rates. A simplified two-dimensional version of the track reconstruction problem is set up on a collaborative platform, RAMP, in order for the developers to prototype and test new ideas. A small-scale competition was held during the Connecting The Dots / Intelligent Trackers 2017 (CTDWIT 2017) workshop. Despite the short time scale, a number of different approaches have been developed and compared along a single score metric, which was kept generic enough to accommodate a summarized performance in terms of both efficiency and fake rates.