EPJ Web Conf.
Volume 214, 201923rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|Number of page(s)||7|
|Section||T6 - Machine learning & analysis|
|Published online||17 September 2019|
New Fitting Concept in ATLAS muon tracking for the LHC Run-2
Deutsches Elektronen-Synchrotron DESY,
Hamburg and Zeuthen,
2 IRFU, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
3 Nikhef National Institute for Subatomic Physics and University of Amsterdam Amsterdam, Netherlands
4 Department of Physics, Technion, Israel Institute of Technology Haifa, Israel
5 Department of Physics, University of Massachussetts Amherst, MA, USA
6 CERN Geneva, Switzerland
Published online: 17 September 2019
Muons with high momentum - above 500 GeV - are an important constituent of new physics signatures in many models. Run-2 of the LHC is greatly increasing ATLAS’s sensitivity to such signatures thanks to an ever-larger dataset of such particles, enhanced further by an increase in the center-of-mass energy. The ATLAS Muon Spectrometer chamber alignment contributes significantly to the uncertainty of the reconstruction of these high-momentum objects. The proper treatment of measurements during tracking and the correct propagation of the alignment effects is extremely challenging. Recently, an innovative approach that imposes Gaussian constraints on ensembles of detector hits was implemented. It provides a significant improvement to high-momentum tracking without increasing the CPU budget. Furthermore, it allows for the verification of the expected alignment quality using high-statistics collision data. A detailed discussion of the algorithmic realization is given, the expected performance gains are presented and prospects for further applications of the approach are outlined.
© The Authors, published by EDP Sciences, 2019
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.
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