Abstract

The Tile Calorimeter (TileCal) is the central section of the hadronic calorimeter of ATLAS experiment of the Large Hadron Collider (LHC) and has about 10,000 eletronic channels. An Optimal Filter (OF) has been used to estimate the energy sampled by the calorimeter and applies a Quality Factor (QF) for signal acceptance. An approach using Matched Filter (MF) has also been pursued. In order to cope with the luminosity rising foreseen for LHC operation upgrade, different algorithms have been developed. Currently, the OF measurement for signal acceptance is implemented through a chi-square test. At a low luminosity scenario, such QF measurement has been used as a way to describe how the acquired signal is compatible to the pulse shape pattern. However, at high-luminosity conditions, due to pile up, this QF acceptance is no longer possible when OF is employed, and the QF becomes a measurement to indicate whether the reconstructed signal suffers or not from pile up. Methods are being developed in order to recover the superimposed information, and the QF may be used again as signal acceptance criterion. In this work, a new QF measurement is introduced. It is based on divergence statistics, which measures the similarity of probability density functions.

Highlights

  • The Large Hadron Collider (LHC) accelerates and collides protons with a center-of-mass energy of up to 8 TeV in its operation from 2010 to 2012

  • The official energy reconstruction method is Optimal Filter (OF), but other methods can be used during offline data processing, for example, the Matched Filter (MF)

  • A Constrained Optimal Filter (COF) that uses a deconvolution technique to recover the energy in the bunch crossing of interest from the out of time pile-up

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Summary

Introduction

The Large Hadron Collider (LHC) accelerates and collides protons with a center-of-mass energy of up to 8 TeV in its operation from 2010 to 2012. The official energy reconstruction method is Optimal Filter (OF), but other methods can be used during offline data processing, for example, the Matched Filter (MF). Both methods’ performance are sensitive to the increasing pile-up. It has to be mentioned that the planned LHC luminosity increase in the future will require pile-up mitigation in order to preserve the signal reconstruction performance. A Constrained Optimal Filter (COF) that uses a deconvolution technique to recover the energy in the bunch crossing of interest from the out of time pile-up. A signal under the effect of pile-up noise provokes a considerable deterioration of the energy estimation performance, as we can see in the Figures below.

Energy Reconstruction
Quality Factor
Results
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