Speaker
Summary
As the LHC luminosity is ramped up to the SLHC Phase I level and beyond, the high rates, multiplicities, and energies of particles seen by the detectors will pose a unique challenge. Only a tiny fraction of the produced collisions can be stored on tape and immense real-time data reduction is needed. An effective trigger system must maintain high trigger efficiencies for the physics we are most interested in, and at the same time suppress the enormous QCD backgrounds. This requires massive computing power to minimize the online execution time of complex algorithms. A multi-level trigger is an effective solution for an otherwise impossible problem. The Fast Tracker (FTK), is a proposed upgrade to the current ATLAS trigger system that will operate at full Level-1 output rates and provide high quality tracks reconstructed over the entire detector by the start of processing in Level-2. FTK solves the combinatorial challenge inherent to tracking by exploiting massive parallelism of associative memories that can compare inner detector hits to millions of pre-calculated patterns simultaneously. The tracking problem within matched patterns is further simplified by using pre-computed linearized fitting constants and leveraging fast DSPs in modern commercial FPGAs. Overall, FTK is able to compute the helix parameters for all tracks in an event and apply quality cuts in less than 100 microseconds.
The system design is defined and studied with respect to high-PT Level-2 objects: b-jets, tau-jets, and isolated leptons. We test FTK algorithms using ATLAS full simulation with WH events up to the Phase I luminosity and beyond, comparing FTK results with the offline tracking capability. We present the architecture and the reconstruction performance for the mentioned high-PT Level-2 objects.
The most interesting processes at hadron colliders are very rare and hidden in an extremely high level of background. Implementing the most powerful selections in real time is therefore essential to fully exploit the physics potential of experiments where only a very limited fraction of the produced data can be stored on tape. Enormous real-time data reduction must be realized.
Real time track reconstruction can be an important element in triggering at CERN’s Large Hadron Collider (LHC), and even more so after the Super LHC (SLHC) luminosity upgrade. There are numerous examples of the importance of tracking in the trigger. The source of electroweak symmetry breaking couples in proportion to mass. Thus heavy fermions are likely in the final state, in particular b quarks and tau leptons.
High trigger efficiency for these processes requires sensitivity to the generic hadronic decays of the heavy fermions. The challenge comes from the enormous background from QCD produced light quark and gluon jets, which can be suppressed using tracking. Tracks coming from a secondary vertex or not pointing to the beam line identify b quark jets, while tau jets can be separated from background using the number of tracks within a narrow “signal cone” and the number in a larger “isolation region”.
Electron and muon triggers can also be improved at high luminosity using track information. Traditionally background is suppressed by applying an isolation requirement using the calorimeters. At SLHC luminosity the energy added by the 75 additional collisions results in either decreased lepton efficiency or increased background contamination. The effect can be greatly ameliorated with a track-based isolation only using tracks pointing to the lepton candidate at the beam line.
The Fast TracKer (FTK) [1] will enable early rejection of background events and thus leave more execution time for sophisticated algorithms by moving track reconstruction into a hardware system with massively parallel processing [2] that produces global track reconstruction with near offline resolution.
For the first time FTK performance is estimated with the expected pile-up at 3×10^34 cm^−2 s^−1 luminosity consisting on average of 75 minimum bias interaction. Resolution and efficiency for individual tracks and identification capabilities for physics objects, together with timing performance, are presented. We present results obtained with a full simulation of the associate production of the W and the Higgs bosons.
This channel contains all the signatures we are interested in: bjets, taus and muons.
[1] A. Andreani et al., The FastTracker Real Time Processor and Its Impact on Muon Isolation, Tau and b-Jet Online Selections at ATLAS, Conference Record 17th IEEE NPSS Real Time Conference Record of the 17th Real Time Conference, Lisbon, Portugal, 24 - 28 May 2010.
[2] A. Annovi et al., “A VLSI Processor for Fast Track Finding Based on Content Addressable Memories “, IEEE Trans. Nucl. Sci. 53, 2428 (2006)
