Speaker
Description
Accurate simulation of calorimeter response for high energy electromagnetic
particles is essential for the LHC experiments. Detailed simulation of the
electromagnetic showers using Geant4 is however very CPU intensive and
various fast simulation methods were proposed instead. The frozen shower
simulation substitutes the full propagation of the showers for energies
below $1$~GeV by showers taken from a pre-simulated library. The method is
used for production of the main ATLAS Monte Carlo samples, greatly
improving the production time. The frozen showers describe shower shapes,
sampling fraction, sampling and noise-related fluctuations very well, while
description of the constant term, related to calorimeter non-uniformity,
requires a careful choice of the shower library binning. A new method is
proposed to tune the binning variables, using multivariate techniques. The
method is tested and optimized for the description of the ATLAS forward
calorimeter.
| Primary Keyword (Mandatory) | Simulation |
|---|---|
| Secondary Keyword (Optional) | Artificial intelligence/Machine learning |
