Abstract

The Monte Carlo simulation of the detector response is an integral component of any analysis performed with data from the LHC experiments. As these simulated data sets must be both large and precise, their production is a CPU-intensive task. ATLAS has developed full and fast detector simulation techniques to achieve this goal within the computing limits of the collaboration. At the current early stages of data-taking, it is necessary to reprocess the Monte Carlo event samples continuously, while integrating adaptations to the simulation modules in order to improve the agreement with data taken by means of the detector itself. FATRAS is a fast track simulation engine which produces a Monte Carlo simulation based on modules and the geometry of the standard ATLAS track reconstruction algorithm. It can be combined with a fast parametrized-response simulation of the calorimeters. This approach shows a high level of agreement with the full simulation, while achieving a relative timing gain of two orders of magnitude. 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 current conditions, as well as calibration at the hit level. We present the updated and calibrated version of FATRAS based on the first LHC data. Extensive comparisons of the fast track simulation with the full simulation and data at 900 GeV are shown.

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