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Exploration of Jet Substructure with Energy Flow Polynomials
The Energy Flow Polynomials (EFPs) are a set of jet substructure observables which forms an overcomplete basis for all infrared- and collinear-safe jet observables. In this study, an in-depth look into the EFPs is conducted. Comparisons of EFPs distributions are made between experimental and simulat...
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Lenguaje: | eng |
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2019
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Acceso en línea: | http://cds.cern.ch/record/2689625 |
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author | Yu, Yu-Heng |
author_facet | Yu, Yu-Heng |
author_sort | Yu, Yu-Heng |
collection | CERN |
description | The Energy Flow Polynomials (EFPs) are a set of jet substructure observables which forms an overcomplete basis for all infrared- and collinear-safe jet observables. In this study, an in-depth look into the EFPs is conducted. Comparisons of EFPs distributions are made between experimental and simulated dataset; strong correlations between different EFPs are found; Principal Component Analysis is done to 53 different EFPs, where they can be reduced to 6 principal components without much loss of information; Linear Regression is done to the same set of EFPs, and also to the 6 reduced components, to find the coefficients for them to linearly combine into some traditional jet shapes. Similar performances are found between the 53 EFPs and the 6 principal components. |
id | cern-2689625 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2019 |
record_format | invenio |
spelling | cern-26896252019-09-30T06:29:59Zhttp://cds.cern.ch/record/2689625engYu, Yu-HengExploration of Jet Substructure with Energy Flow PolynomialsPhysics in GeneralThe Energy Flow Polynomials (EFPs) are a set of jet substructure observables which forms an overcomplete basis for all infrared- and collinear-safe jet observables. In this study, an in-depth look into the EFPs is conducted. Comparisons of EFPs distributions are made between experimental and simulated dataset; strong correlations between different EFPs are found; Principal Component Analysis is done to 53 different EFPs, where they can be reduced to 6 principal components without much loss of information; Linear Regression is done to the same set of EFPs, and also to the 6 reduced components, to find the coefficients for them to linearly combine into some traditional jet shapes. Similar performances are found between the 53 EFPs and the 6 principal components.CERN-STUDENTS-Note-2019-206oai:cds.cern.ch:26896252019-09-16 |
spellingShingle | Physics in General Yu, Yu-Heng Exploration of Jet Substructure with Energy Flow Polynomials |
title | Exploration of Jet Substructure with Energy Flow Polynomials |
title_full | Exploration of Jet Substructure with Energy Flow Polynomials |
title_fullStr | Exploration of Jet Substructure with Energy Flow Polynomials |
title_full_unstemmed | Exploration of Jet Substructure with Energy Flow Polynomials |
title_short | Exploration of Jet Substructure with Energy Flow Polynomials |
title_sort | exploration of jet substructure with energy flow polynomials |
topic | Physics in General |
url | http://cds.cern.ch/record/2689625 |
work_keys_str_mv | AT yuyuheng explorationofjetsubstructurewithenergyflowpolynomials |