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Exploring the (Metric) Space of Jets with CMS Open Data

<!--HTML--><div> <div> <div> <p>When are two collider events similar? &nbsp;In this talk, I answer this question by developing a metric between the events based on the earth mover's distance: the “work” required to rearrange one event into the other. With a met...

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Autor principal: Metodiev, Eric
Lenguaje:eng
Publicado: 2019
Materias:
Acceso en línea:http://cds.cern.ch/record/2679340
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author Metodiev, Eric
author_facet Metodiev, Eric
author_sort Metodiev, Eric
collection CERN
description <!--HTML--><div> <div> <div> <p>When are two collider events similar? &nbsp;In this talk, I answer this question by developing a metric between the events based on the earth mover's distance: the “work” required to rearrange one event into the other. With a metric in hand, I will focus on exploring the space of jets using using public collider data from the CMS experiment. Among other applications, our metric allows us to visualize the metric space of jets, extract their correlation dimension, perform jet classification, identify the most and least typical jet configurations, and quantify the impact of detector effects in new ways.</p> <p>&nbsp;</p> </div> </div> </div>
id cern-2679340
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2019
record_format invenio
spelling cern-26793402022-11-02T22:31:43Zhttp://cds.cern.ch/record/2679340engMetodiev, EricExploring the (Metric) Space of Jets with CMS Open DataExploring the (Metric) Space of Jets with CMS Open DataEP-IT Data science seminars<!--HTML--><div> <div> <div> <p>When are two collider events similar? &nbsp;In this talk, I answer this question by developing a metric between the events based on the earth mover's distance: the “work” required to rearrange one event into the other. With a metric in hand, I will focus on exploring the space of jets using using public collider data from the CMS experiment. Among other applications, our metric allows us to visualize the metric space of jets, extract their correlation dimension, perform jet classification, identify the most and least typical jet configurations, and quantify the impact of detector effects in new ways.</p> <p>&nbsp;</p> </div> </div> </div>oai:cds.cern.ch:26793402019
spellingShingle EP-IT Data science seminars
Metodiev, Eric
Exploring the (Metric) Space of Jets with CMS Open Data
title Exploring the (Metric) Space of Jets with CMS Open Data
title_full Exploring the (Metric) Space of Jets with CMS Open Data
title_fullStr Exploring the (Metric) Space of Jets with CMS Open Data
title_full_unstemmed Exploring the (Metric) Space of Jets with CMS Open Data
title_short Exploring the (Metric) Space of Jets with CMS Open Data
title_sort exploring the (metric) space of jets with cms open data
topic EP-IT Data science seminars
url http://cds.cern.ch/record/2679340
work_keys_str_mv AT metodieveric exploringthemetricspaceofjetswithcmsopendata