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FPGA Implementation of an Artificial Neural Network for Subatomic Physics Experiment Particles Recognition

Authors :
Yann Hu
M. Goffe
Ruiguang Zhao
A. Besson
Luis Alejandro Perez perez
Christine Hu-Guo
Kimmo Jaaskelainen
Institut Pluridisciplinaire Hubert Curien (IPHC)
Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)
Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)
Source :
PoS, Topical Workshop on Electronics for Particle Physics, Topical Workshop on Electronics for Particle Physics, Sep 2018, Antwerpen, Belgium. pp.066, ⟨10.22323/1.343.0066⟩
Publication Year :
2018
Publisher :
HAL CCSD, 2018.

Abstract

International audience; CMOS Pixel Sensors have been used in subatomic physics experiments for charged particles detection. In the International Linear Collider (ILC) vertex detector, the occupancy will be mainly driven by impacts coming from the beam background. This will have a huge impact to the data flow of the system. We propose a design of CMOS pixel sensors with on-chip Artificial Neural Network (ANN) to tag and remove these hits. It is based on different features of hits clusters. In this paper, we will describe the structure of an ANN implemented in an FPGA device. We will show and analyze the distribution of incident angles reconstructed by the ANN.

Details

Language :
English
Database :
OpenAIRE
Journal :
PoS, Topical Workshop on Electronics for Particle Physics, Topical Workshop on Electronics for Particle Physics, Sep 2018, Antwerpen, Belgium. pp.066, ⟨10.22323/1.343.0066⟩
Accession number :
edsair.doi.dedup.....f2cceec05f66dc91630d7e340e42deaf