In high-energy physics experiments, track based selection in the online environment is crucial for the efficient real time selection of the rare physics process of interest. This is of particular importance at the Large Hadron Collider (LHC), where the increasingly harsh collision environment is challenging the experiments to improve the performance of their online selection. Principal among these challenges is the increasing number of interactions per bunch crossing, known as pileup. In the ATLAS experiment the challenge has been addressed with multiple strategies.
Firstly, specific trigger objects have been improved by building algorithms using detailed tracking and vertexing in specific detector regions to improve background rejection without loosing signal efficiency. Secondly, since 2015 all trigger areas have benefited from a new high performance Inner Detector (ID) software tracking system implemented in the High Level Trigger. Finally, performance will be further enhanced in future by the installation and commissioning of a hardware based Fast TracKer (FTK) throughout 2017.
This presentation will focus on the performance of the ID tracking software as well as looking ahead to projected improvements from FTK. Specific focus will be given to the case of flavour tagging of b-jets, as an example of the implementation of novel algorithms to improve vertexing and light-jet rejection in real time.