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A Neural-Network Clusterisation Algorithm for the ATLAS Silicon Pixel Detector
A novel technique using a set of artificial neural networks to identify and split merged measurements created by multiple charged particles in the ATLAS pixel detector is presented. Such merged measurements are a common feature of boosted physics objects such as tau leptons or strongly energetic jet...
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Lenguaje: | eng |
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2013
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Acceso en línea: | https://dx.doi.org/10.1088/1742-6596/523/1/012023 http://cds.cern.ch/record/1599552 |