Trigger and reconstruction farms in the HERA-B experiment and algorithms for a Third Level Trigger

by Schwanke, Ullrich

Abstract (Summary)
The HERA-$B$ experiment at Deutsches Elektronen-Synchrotron (DESY) Hamburg aims at investigating the physics of particles containing $b$ quarks. The experiment focusses on measuring CP violation in the system of neutral $B$ mesons. It is expected that the precise determination of the CP asymmetry in the channel $B^0(\bar{B}^0)\to J/\psi K_S^0$ will have an impact on the further development of the Standard Model of Elementary Particle Physics and cosmological theories. The HERA-$B$ experiment uses the proton beam of the HERA storage ring in fixed-target mode. $B$ hadrons are produced in pairs when protons from the beam halo interact with target nuclei. The interactions are recorded by a forward-spectrometer with roughly 600.000 readout channels. At the HERA-$B$ centre-of-mass energy of 42.6\,GeV, the $b\bar{b}$ cross section is only a tiny fraction of the total inelastic cross section. Only one in about 10$^6$ events contains $b$ quarks, which turns the selection of signal events into a particular challenge. The selection is accomplished by a four-stage data acquisition and trigger system reducing the event rate from 10\,MHz to about 20\,Hz. Besides custom-made electronics, several hundreds of PCs are used in the trigger system. The computers are arranged in two so-called PC farms with more than 200 processors each. The PC farms provide the computing capacity for trigger decisions and the prompt analysis of event data. One farm executes fast trigger programs with a computing time of 1--100\,ms per event. The other farm performs online reconstruction of the events before data are archived on tape. The computing time per event is in the range of several seconds. This thesis covers two topics. In the beginning, the technical implementation of the trigger and the reconstruction farm are described. In doing so, emphasis is put on the software systems which make calibration data available to the farms and which provide a centralised view on the results of the executing processes. The principal part of this thesis deals with algorithms for a Third Level Trigger. This trigger is to come into operation on the trigger farm together with existing programs. Processes of the type $B^0(\bar{B}^0)\to J/\psi X$ have a very clean signature when the $J/\psi$ decays to a $e^+e^-$ or $\mu^+\mu^-$ pair. The trigger system attempts to identify two unlike-sign leptons of the same flavour whose invariant mass matches the $J/\psi$. In later steps, the tracks are required to originate from a common vertex close to the target. It is assumed that these kinematic constraints are sufficient to pick out events of this type among the copious background processes. In contrast, the Third Level Trigger is to be applied to signal processes with fewer kinematic constraints. Such events occur for example when two $B$ mesons, which were created in a proton-target collision, decay semileptonically. The trigger system selects merely the two leptons which do not originate from a common vertex in this case. The Third Level Trigger has 100\,ms at its disposal to extract further criteria from the data which can serve to distinguish between signal and background events. This thesis investigates with the aid of Monte-Carlo simulations how the data of the experiment's silicon vertex detector can contribute to the decisions of a Third Level Trigger. The trigger aims at reconstructing tracks from the decay cascade of $B$ mesons in addition to the leptons selected by the preceding trigger levels. A fast pattern recognition for the vertex detector demonstrates that the reconstruction of all tracks and the application of trigger algorithms are possible within the given time slot of 100\,ms. The determination of track parameters in the target region exploits the Kalman-filter method to account for the multiple scattering of particles in the detector material. The application of this method is, however, made difficult by two facts. First, the momentum of the reconstructed tracks is not known. And, second, the material distribution in the detector cannot be taken into consideration in detail due to timing limitations. Adequate approximations for the momentum and the material traversed by a particle help to accomplish a sufficient accuracy of the track parameters. The reconstructed tracks constitute the starting point of several trigger algorithms, whose suitability to select signal events is investigated. Our studies indicate that the reconstruction of tracks with large impact parameters is a more promising approach than a search for secondary vertices.
This document abstract is also available in German.
Bibliographical Information:


School:Humboldt-Universität zu Berlin

School Location:Germany

Source Type:Master's Thesis

Keywords:HERA-$B$-Experiment PC Cluster Triggeralgorithmen HERA-$B$ experiment cluster pattern recognition trigger algorithms


Date of Publication:10/30/2000

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