Real-Time Flavor Tagging Algorithms in ATLAS

In high-energy physics experiments, online selection is crucial to select interesting collisions from the large data volume. ATLAS b-jet triggers are designed to identify heavy-flavour content in real-time and provide the only option to efficiently record events with fully hadronic final states containing b-jets. In doing so, two different, but related, challenges are faced. The physics goal is to optimise as far as possible the rejection of light jets, while retaining a high efficiency on selecting b-jets and maintaining affordable trigger rates without raising jet energy thresholds. This results in a challenging computing task, as tracks and their corresponding vertices must be reconstructed and analysed for each jet above the desired threshold, regardless of the increasingly adverse pile-up conditions. We present an overview of the ATLAS strategy for online b-jet selection for the LHC Run 2, including the use of novel methods and sophisticated algorithms designed to face the above mentioned challenges. A first look at the performance in Run 2 data is shown and compared to the performance during Run 1. The ATLAS FastTracKer (FTK) system does global track reconstruction for each event accepted at Level 1 to enable early access to tracking information for the High Level Trigger. We also present the status of the FTK commissioning (expected to be completed in 2016) and discuss how the system can be exploited to improve the current b-jet trigger performance.