Exploring the space of jets with CMS open data
Abstract
We explore the metric space of jets using public collider data from the CMS experiment. Starting from of proton-proton collisions at collected at the Large Hadron Collider in 2011, we isolate a sample of 1,690,984 central jets with transverse momentum above 375 GeV. To validate the performance of the CMS detector in reconstructing the energy flow of jets, we compare the CMS Open Data to corresponding simulated data samples for a variety of jet kinematic and substructure observables. Even without detector unfolding, we find very good agreement for track-based observables after using charged hadron subtraction to mitigate the impact of pileup. We perform a range of novel analyses, using the “energy mover’s distance” (EMD) to measure the pairwise difference between jet energy flows. The EMD allows us to quantify the impact of detector effects, visualize the metric space of jets, extract correlation dimensions, and identify the most and least typical jet configurations. To facilitate future jet studies with CMS Open Data, we make our datasets and analysis code available, amounting to around two gigabytes of distilled data and one hundred gigabytes of simulation files.
- Authors:
- Publication Date:
- Research Org.:
- Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Nuclear Physics (NP); USDOE Office of Science (SC), High Energy Physics (HEP); Heising-Simons Foundation; Simons Foundation
- OSTI Identifier:
- 1599516
- Alternate Identifier(s):
- OSTI ID: 1630642
- Grant/Contract Number:
- SC0011090; SC0012567; SC0019128
- Resource Type:
- Published Article
- Journal Name:
- Physical Review. D.
- Additional Journal Information:
- Journal Name: Physical Review. D. Journal Volume: 101 Journal Issue: 3; Journal ID: ISSN 2470-0010
- Publisher:
- American Physical Society (APS)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 73 NUCLEAR PHYSICS AND RADIATION PHYSICS; 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS
Citation Formats
Komiske, Patrick T., Mastandrea, Radha, Metodiev, Eric M., Naik, Preksha, and Thaler, Jesse. Exploring the space of jets with CMS open data. United States: N. p., 2020.
Web. doi:10.1103/PhysRevD.101.034009.
Komiske, Patrick T., Mastandrea, Radha, Metodiev, Eric M., Naik, Preksha, & Thaler, Jesse. Exploring the space of jets with CMS open data. United States. https://doi.org/10.1103/PhysRevD.101.034009
Komiske, Patrick T., Mastandrea, Radha, Metodiev, Eric M., Naik, Preksha, and Thaler, Jesse. Tue .
"Exploring the space of jets with CMS open data". United States. https://doi.org/10.1103/PhysRevD.101.034009.
@article{osti_1599516,
title = {Exploring the space of jets with CMS open data},
author = {Komiske, Patrick T. and Mastandrea, Radha and Metodiev, Eric M. and Naik, Preksha and Thaler, Jesse},
abstractNote = {We explore the metric space of jets using public collider data from the CMS experiment. Starting from 2.3fb-1 of proton-proton collisions at s=7TeV collected at the Large Hadron Collider in 2011, we isolate a sample of 1,690,984 central jets with transverse momentum above 375 GeV. To validate the performance of the CMS detector in reconstructing the energy flow of jets, we compare the CMS Open Data to corresponding simulated data samples for a variety of jet kinematic and substructure observables. Even without detector unfolding, we find very good agreement for track-based observables after using charged hadron subtraction to mitigate the impact of pileup. We perform a range of novel analyses, using the “energy mover’s distance” (EMD) to measure the pairwise difference between jet energy flows. The EMD allows us to quantify the impact of detector effects, visualize the metric space of jets, extract correlation dimensions, and identify the most and least typical jet configurations. To facilitate future jet studies with CMS Open Data, we make our datasets and analysis code available, amounting to around two gigabytes of distilled data and one hundred gigabytes of simulation files.},
doi = {10.1103/PhysRevD.101.034009},
journal = {Physical Review. D.},
number = 3,
volume = 101,
place = {United States},
year = {Tue Feb 11 00:00:00 EST 2020},
month = {Tue Feb 11 00:00:00 EST 2020}
}
https://doi.org/10.1103/PhysRevD.101.034009
Web of Science
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