Fuzzy jets
Abstract
Collimated streams of particles produced in high energy physics experiments are organized using clustering algorithms to form jets . To construct jets, the experimental collaborations based at the Large Hadron Collider (LHC) primarily use agglomerative hierarchical clustering schemes known as sequential recombination. We propose a new class of algorithms for clustering jets that use infrared and collinear safe mixture models. These new algorithms, known as fuzzy jets , are clustered using maximum likelihood techniques and can dynamically determine various properties of jets like their size. We show that the fuzzy jet size adds additional information to conventional jet tagging variables in boosted topologies. Furthermore, we study the impact of pileup and show that with some slight modifications to the algorithm, fuzzy jets can be stable up to high pileup interaction multiplicities.
- Authors:
-
- Stanford Univ., Stanford, CA (United States)
- Stanford Univ., Stanford, CA (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States)
- SLAC National Accelerator Lab., Menlo Park, CA (United States)
- Publication Date:
- Research Org.:
- SLAC National Accelerator Lab., Menlo Park, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1260836
- Grant/Contract Number:
- AC02-76SF00515
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of High Energy Physics (Online)
- Additional Journal Information:
- Journal Name: Journal of High Energy Physics (Online); Journal Volume: 2016; Journal Issue: 6; Journal ID: ISSN 1029-8479
- Publisher:
- Springer Berlin
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; 97 MATHEMATICS AND COMPUTING; jets
Citation Formats
Mackey, Lester, Nachman, Benjamin, Schwartzman, Ariel, and Stansbury, Conrad. Fuzzy jets. United States: N. p., 2016.
Web. doi:10.1007/JHEP06(2016)010.
Mackey, Lester, Nachman, Benjamin, Schwartzman, Ariel, & Stansbury, Conrad. Fuzzy jets. United States. https://doi.org/10.1007/JHEP06(2016)010
Mackey, Lester, Nachman, Benjamin, Schwartzman, Ariel, and Stansbury, Conrad. Wed .
"Fuzzy jets". United States. https://doi.org/10.1007/JHEP06(2016)010. https://www.osti.gov/servlets/purl/1260836.
@article{osti_1260836,
title = {Fuzzy jets},
author = {Mackey, Lester and Nachman, Benjamin and Schwartzman, Ariel and Stansbury, Conrad},
abstractNote = {Collimated streams of particles produced in high energy physics experiments are organized using clustering algorithms to form jets . To construct jets, the experimental collaborations based at the Large Hadron Collider (LHC) primarily use agglomerative hierarchical clustering schemes known as sequential recombination. We propose a new class of algorithms for clustering jets that use infrared and collinear safe mixture models. These new algorithms, known as fuzzy jets , are clustered using maximum likelihood techniques and can dynamically determine various properties of jets like their size. We show that the fuzzy jet size adds additional information to conventional jet tagging variables in boosted topologies. Furthermore, we study the impact of pileup and show that with some slight modifications to the algorithm, fuzzy jets can be stable up to high pileup interaction multiplicities.},
doi = {10.1007/JHEP06(2016)010},
journal = {Journal of High Energy Physics (Online)},
number = 6,
volume = 2016,
place = {United States},
year = {Wed Jun 01 00:00:00 EDT 2016},
month = {Wed Jun 01 00:00:00 EDT 2016}
}
Web of Science
Works referenced in this record:
Charged-particle multiplicities in pp interactions measured with the ATLAS detector at the LHC
journal, May 2011
- Aad, G.; Abbott, B.; Abdallah, J.
- New Journal of Physics, Vol. 13, Issue 5
Performance of electron reconstruction and selection with the CMS detector in proton-proton collisions at √ s = 8 TeV
journal, June 2015
- ,
- Journal of Instrumentation, Vol. 10, Issue 06, p. P06005-P06005
Electron and photon energy calibration with the ATLAS detector using LHC Run 1 data
journal, October 2014
- Aad, G.; Abbott, B.; Abdallah, J.
- The European Physical Journal C, Vol. 74, Issue 10
Performance of CMS muon reconstruction in pp collision events at √s = 7 TeV
journal, October 2012
- collaboration, The CMS
- Journal of Instrumentation, Vol. 7, Issue 10
Measurement of the muon reconstruction performance of the ATLAS detector using 2011 and 2012 LHC proton–proton collision data
journal, November 2014
- Aad, G.; Abbott, B.; Abdallah, J.
- The European Physical Journal C, Vol. 74, Issue 11
Successive combination jet algorithm for hadron collisions
journal, October 1993
- Ellis, Stephen D.; Soper, Davison E.
- Physical Review D, Vol. 48, Issue 7
Better jet clustering algorithms
journal, August 1997
- Dokshitzer, Yu. L.; Leder, G. D.; Moretti, S.
- Journal of High Energy Physics, Vol. 1997, Issue 08
The anti- k t jet clustering algorithm
journal, April 2008
- Cacciari, Matteo; Salam, Gavin P.; Soyez, Gregory
- Journal of High Energy Physics, Vol. 2008, Issue 04
An examination of procedures for determining the number of clusters in a data set
journal, June 1985
- Milligan, Glenn W.; Cooper, Martha C.
- Psychometrika, Vol. 50, Issue 2
Estimating the number of clusters in a data set via the gap statistic
journal, May 2001
- Tibshirani, Robert; Walther, Guenther; Hastie, Trevor
- Journal of the Royal Statistical Society: Series B (Statistical Methodology), Vol. 63, Issue 2, p. 411-423
Longitudinally-invariant k⊥-clustering algorithms for hadron-hadron collisions
journal, September 1993
- Catani, S.; Dokshitzer, Yu. L.; Seymour, M. H.
- Nuclear Physics B, Vol. 406, Issue 1-2
Resolving boosted jets with XCone
journal, December 2015
- Thaler, Jesse; Wilkason, Thomas F.
- Journal of High Energy Physics, Vol. 2015, Issue 12
Optimal Jet Finder
journal, September 2003
- Grigoriev, D. Yu.; Jankowski, E.; Tkachov, F. V.
- Computer Physics Communications, Vol. 155, Issue 1
Nondeterministic Approach to Tree-Based Jet Substructure
journal, May 2012
- Ellis, Stephen D.; Hornig, Andrew; Roy, Tuhin S.
- Physical Review Letters, Vol. 108, Issue 18
Pileup subtraction using jet areas
journal, January 2008
- Cacciari, Matteo; Salam, Gavin P.
- Physics Letters B, Vol. 659, Issue 1-2
Jets in hadron–hadron collisions
journal, April 2008
- Ellis, S. D.; Huston, J.; Hatakeyama, K.
- Progress in Particle and Nuclear Physics, Vol. 60, Issue 2
Maximum Likelihood Estimation from Incomplete Data
journal, June 1958
- Hartley, H. O.
- Biometrics, Vol. 14, Issue 2
A brief introduction to PYTHIA 8.1
journal, June 2008
- Sjöstrand, Torbjörn; Mrenna, Stephen; Skands, Peter
- Computer Physics Communications, Vol. 178, Issue 11
PYTHIA 6.4 physics and manual
journal, May 2006
- Sjöstrand, Torbjörn; Mrenna, Stephen; Skands, Peter
- Journal of High Energy Physics, Vol. 2006, Issue 05
FastJet user manual: (for version 3.0.2)
journal, March 2012
- Cacciari, Matteo; Salam, Gavin P.; Soyez, Gregory
- The European Physical Journal C, Vol. 72, Issue 3
Jet trimming
journal, February 2010
- Krohn, David; Thaler, Jesse; Wang, Lian-Tao
- Journal of High Energy Physics, Vol. 2010, Issue 2
Identifying boosted objects with N-subjettiness
journal, March 2011
- Thaler, Jesse; Van Tilburg, Ken
- Journal of High Energy Physics, Vol. 2011, Issue 3
Pileup per particle identification
journal, October 2014
- Bertolini, Daniele; Harris, Philip; Low, Matthew
- Journal of High Energy Physics, Vol. 2014, Issue 10
Particle-level pileup subtraction for jets and jet shapes
journal, June 2014
- Berta, Peter; Spousta, Martin; Miller, David W.
- Journal of High Energy Physics, Vol. 2014, Issue 6
SoftKiller, a particle-level pileup removal method
journal, February 2015
- Cacciari, Matteo; Salam, Gavin P.; Soyez, Gregory
- The European Physical Journal C, Vol. 75, Issue 2
Works referencing / citing this record:
JUNIPR: a framework for unsupervised machine learning in particle physics
journal, February 2019
- Andreassen, Anders; Feige, Ilya; Frye, Christopher
- The European Physical Journal C, Vol. 79, Issue 2