Performance of the ATLAS Inner Detector trigger algorithms in pp collisions at √s = 900 GeV

Abstract

The ATLAS Inner Detector (ID) trigger algorithms ran online during data taking with proton-proton collisions at the Large Hadron Collider (LHC) in December 2009. Preliminary results on the performance of the algorithms in collisions at centre-of-mass energy of 900 GeV are presented, including comparisons to the ATLAS offline tracking algorithms and to simulations. The ATLAS trigger performs the online event selection in three stages. The ID information is used in the second and third triggering stages, called Level-2 trigger (L2) and Event Filter (EF) respectively, and collectively the High Level Triggers (HLT). The HLT runs software algorithms in a large farm of commercial CPUs and is designed to reject collision events in real time, keeping the most interesting few in every thousand. The average execution time per event at L2(EF) is about 40 ms(4s) and the ID trigger algorithms can take only a fraction of that. Within this time, the data from interesting regions of the ID have to be accessed from central buffers through the network, unpacked, clustered and converted to the ATLAS global coordinates, then pattern recognition follows to identify the trajectories of charged particles (tracks), and finally these tracks are used in combination with other information to accept or reject events, according to whether they satisfy one or more trigger signatures. The various clients of the ID trigger information impose different constraints in the performance of the pattern recognition, in terms of efficiency and fake rate for tracks. An overview of the different uses of the ID trigger algorithms is given, and their online performance is exemplified with results from the use of L2 tracks for the online determination of the LHC beam position.