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Reducing Noisy Clusters in the NA61/SHINE Project with Help of Machine Learning

We live in an era where huge amounts of data are being generated in all sectors of science and industry. We call it “Big Data”. With Big data, we face the challenge of its analysis and interpretation. Therefore, the need for novel machine learning and artificial intelligence methods has drastically...

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Autor principal: Pawlowski, Janik
Lenguaje:eng
Publicado: 2021
Materias:
Acceso en línea:http://cds.cern.ch/record/2766095
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author Pawlowski, Janik
author_facet Pawlowski, Janik
author_sort Pawlowski, Janik
collection CERN
description We live in an era where huge amounts of data are being generated in all sectors of science and industry. We call it “Big Data”. With Big data, we face the challenge of its analysis and interpretation. Therefore, the need for novel machine learning and artificial intelligence methods has drastically increased in recent years. Likewise, the range of areas in which machine learning has been successfully applied has increased significantly: including image recognition, speech recognition, natural language processing, computational biology and particle physics. Modern tracking devices for particle collision experiments, such as the four large-volume Time Projection Chambers (TPC) used for the NA61/SHINE project at the European Organization for Nuclear Research (CERN), collect huge amounts of data produced by particle collisions. This data contains not only valuable information but also a lot of noise. As recent breakthroughs inspire us to apply machine learning techniques in more and more areas, the question arises: Can we reduce the noise with help of Machine Learning? In this thesis work, the above mentioned question is answered and multiple machine- and deep learning algorithms are not only proposed, but the underlying principles explained and visualized. This thesis tries to answer why those algorithms work and what they might learn.
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institution Organización Europea para la Investigación Nuclear
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spelling cern-27660952021-05-10T20:12:20Zhttp://cds.cern.ch/record/2766095engPawlowski, JanikReducing Noisy Clusters in the NA61/SHINE Project with Help of Machine LearningDetectors and Experimental TechniquesWe live in an era where huge amounts of data are being generated in all sectors of science and industry. We call it “Big Data”. With Big data, we face the challenge of its analysis and interpretation. Therefore, the need for novel machine learning and artificial intelligence methods has drastically increased in recent years. Likewise, the range of areas in which machine learning has been successfully applied has increased significantly: including image recognition, speech recognition, natural language processing, computational biology and particle physics. Modern tracking devices for particle collision experiments, such as the four large-volume Time Projection Chambers (TPC) used for the NA61/SHINE project at the European Organization for Nuclear Research (CERN), collect huge amounts of data produced by particle collisions. This data contains not only valuable information but also a lot of noise. As recent breakthroughs inspire us to apply machine learning techniques in more and more areas, the question arises: Can we reduce the noise with help of Machine Learning? In this thesis work, the above mentioned question is answered and multiple machine- and deep learning algorithms are not only proposed, but the underlying principles explained and visualized. This thesis tries to answer why those algorithms work and what they might learn.CERN-THESIS-2021-041oai:cds.cern.ch:27660952021-05-07T08:33:16Z
spellingShingle Detectors and Experimental Techniques
Pawlowski, Janik
Reducing Noisy Clusters in the NA61/SHINE Project with Help of Machine Learning
title Reducing Noisy Clusters in the NA61/SHINE Project with Help of Machine Learning
title_full Reducing Noisy Clusters in the NA61/SHINE Project with Help of Machine Learning
title_fullStr Reducing Noisy Clusters in the NA61/SHINE Project with Help of Machine Learning
title_full_unstemmed Reducing Noisy Clusters in the NA61/SHINE Project with Help of Machine Learning
title_short Reducing Noisy Clusters in the NA61/SHINE Project with Help of Machine Learning
title_sort reducing noisy clusters in the na61/shine project with help of machine learning
topic Detectors and Experimental Techniques
url http://cds.cern.ch/record/2766095
work_keys_str_mv AT pawlowskijanik reducingnoisyclustersinthena61shineprojectwithhelpofmachinelearning