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Monte Carlo simulation of the detector response is an essential part of any kind of analysis of contemporary High Energy Physics experimental data. At the LHC these simulated data sets are needed with large statistics and high precision level, which makes their production a CPUintensive task. ATLAS has thus concentrated on optimising both full and fast detector simulation techniques to achieve this goal within the computing limits of the collaboration. At the early stages of data-taking, in particular, it is necessary to reprocess Monte Carlo event samples continuously, while tuning the simulation modules to improve the agreement with the data taken from the detector itself. We present a new, fast track simulation engine which implements a full Monte Carlo simulation based on modules and the geometry of the standard ATLAS track reconstruction application. This is combined with a fast parametric-response simulation of the Calorimeter. This approach shows a high level of agreement with the full simulation, while achieving a relative timing gain of about 100. FATRAS was designed to provide a fast feedback cycle for tuning the MC simulation with real data: this includes the material distribution inside the detector, the integration of misalignment and conditions status, like inactive detector modules, dead and noisy channels, as well as calibration at the hit level. We explain the concepts of the fast track simulation and show the performance with respect to first data taken with the ATLAS detector in December 2009.

FATRAS — A Novel Fast Track Simulation Engine for the ATLAS Experiment