Abstract
In order to generate the huge number of Monte Carlo events that will be required by the ATLAS experiment over the next several runs, a very fast simulation is critical. Fast detector simulation alone, however, is insufficient: with very high numbers of simultaneous proton-proton collisions expected in Run 3 and beyond, the digitization (detector response emulation) and event reconstruction time quickly become comparable to the time required for detector simulation. The ATLAS Fast Chain simulation has been developed to solve this problem. Modules are implemented for fast simulation, fast digitization, and fast track reconstruction. The application is sufficiently fast—several orders of magnitude faster than the standard simulation—that the simultaneous proton-proton collisions can be generated during the simulation job, so Pythia8 also runs concurrently with the rest of the algorithms. The Fast Chain has been built to be extremely modular and flexible, so that each sample can be custom-tailored to match the resource and modeling accuracy needs of an analysis. It is ideally suited for analysis templating, systematic uncertainty evaluation, signal parameter space scans, and simulation with alternative detector configurations (e.g. upgrade), among other applications.
Highlights
Monte-Carlo simulation plays a key role in ATLAS experiment [1]—it is the only tool available to predict the response of the complex detector, and to be able to compare experimental results with theoretical predictions
The Geant4 package is traditionally used in ATLAS for the simulation step, it has proven to be reliable and accurate for a wide range of particle types, energies and detector materials
With increased average number of simultaneous proton-proton collisions (μ) expected in Run 3 and beyond, the digitization and event reconstruction time quickly become comparable to the time required for detector simulation
Summary
Monte-Carlo simulation plays a key role in ATLAS experiment [1]—it is the only tool available to predict the response of the complex detector, and to be able to compare experimental results with theoretical predictions. The ATLAS Fast Calorimeter Simulation (FastCaloSim) package [3] was developed It uses a parameterisation based on the Geant. Is improvement of resource consumption needed on every step of the simulation and reconstruction chain (“full chain”), but the configuration of the chain has to be flexible, tailored for the needs of specific analyses, allowing users to plug in more precise tools where the accuracy is critical, saving resources in other places. This idea is underlying the Fast Chain project. As a first step it is possible to generate pileup for just two bunch crossings per HS event
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