Issue |
EPJ Web Conf.
Volume 150, 2017
Connecting The Dots/Intelligent Trackers 2017 (CTD/WIT 2017)
|
|
---|---|---|
Article Number | 00012 | |
Number of page(s) | 10 | |
DOI | https://doi.org/10.1051/epjconf/201715000012 | |
Published online | 08 August 2017 |
https://doi.org/10.1051/epjconf/201715000012
Parameterization-based tracking for the P2 experiment
1 Institute for Nuclear Physics, University of Mainz, Germany
2 PRISMA Cluster of Excellence
a e-mail: sorokin@uni-mainz.de
Published online: 8 August 2017
The P2 experiment in Mainz aims to determine the weak mixing angle θW at low momentum transfer by measuring the parity-violating asymmetry of elastic electronproton scattering. In order to achieve the intended precision of Δ(sin2 θW)/sin2θW = 0:13% within the planned 10 000 hours of running the experiment has to operate at the rate of 1011 detected electrons per second. Although it is not required to measure the kinematic parameters of each individual electron, every attempt is made to achieve the highest possible throughput in the track reconstruction chain.
In the present work a parameterization-based track reconstruction method is described. It is a variation of track following, where the results of the computation-heavy steps, namely the propagation of a track to the further detector plane, and the fitting, are pre-calculated, and expressed in terms of parametric analytic functions. This makes the algorithm extremely fast, and well-suited for an implementation on an FPGA.
The method also takes implicitly into account the actual phase space distribution of the tracks already at the stage of candidate construction. Compared to a simple algorithm, that does not use such information, this allows reducing the combinatorial background by many orders of magnitude, down to O(1) background candidate per one signal track. The method is developed specifically for the P2 experiment in Mainz, and the presented implementation is tightly coupled to the experimental conditions.
© 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.
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