Improving clustering methods for the FoCal detector

dc.rights.license	CC-BY-NC-ND
dc.contributor.advisor	van Leeuwen, Dr. Ir. M.
dc.contributor.author	Bannink, T.R.
dc.date.accessioned	2013-08-15T17:01:33Z
dc.date.available	2013-08-15
dc.date.available	2013-08-15T17:01:33Z
dc.date.issued	2013
dc.identifier.uri	https://studenttheses.uu.nl/handle/20.500.12932/14049
dc.description.abstract	The Forward Calorimeter, FoCal for short, is a proposed detector for the ALICE project at CERN. It is an electromagnetic calorimeter with high position granularity layers allowing separation of nearby particles like the decay photons of the neutral pion. Monte Carlo simulations were used to simulate the detection of these particles and a clustering algorithm is used to reconstruct the particle locations and energies based on the detector's response. The methods used in the clustering algorithm that deal with separation of particles that are close together will be discussed in this thesis. Modifications of the algorithm are introduced which slightly improve the efficiency from 85.8% to 87.4%.
dc.description.sponsorship	Utrecht University
dc.format.extent	1422790 bytes
dc.format.mimetype	application/pdf
dc.language.iso	en
dc.title	Improving clustering methods for the FoCal detector
dc.type.content	Bachelor Thesis
dc.rights.accessrights	Open Access
dc.subject.keywords	FOCAL, FoCal, clustering, algorithm, ALICE, LHC
dc.subject.courseuu	Natuur- en Sterrenkunde