https://doi.org/10.1051/epjconf/201715000015
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
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.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
