Decorrelated jet substructure tagging using adversarial neural networks

doi:10.1103/PhysRevD.96.074034

Title: Decorrelated jet substructure tagging using adversarial neural networks

Authors:: Shimmin, Chase; Sadowski, Peter; Baldi, Pierre; Weik, Edison; Whiteson, Daniel; Goul, Edward; Søgaard, Andreas

Publication Date:: 2017-10-30

Sponsoring Org.:: USDOE

OSTI Identifier:: 1405551

Resource Type:: Publisher's Accepted Manuscript

Journal Name:: Physical Review D

Additional Journal Information:: Journal Name: Physical Review D Journal Volume: 96 Journal Issue: 7; Journal ID: ISSN 2470-0010

Publisher:: American Physical Society

Country of Publication:: United States

Language:: English

Citation Formats


                    Shimmin, Chase, Sadowski, Peter, Baldi, Pierre, Weik, Edison, Whiteson, Daniel, Goul, Edward, and Søgaard, Andreas. Decorrelated jet substructure tagging using adversarial neural networks.  United States: N. p., 2017. 
        Web.  doi:10.1103/PhysRevD.96.074034.

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                    Shimmin, Chase, Sadowski, Peter, Baldi, Pierre, Weik, Edison, Whiteson, Daniel, Goul, Edward, & Søgaard, Andreas. Decorrelated jet substructure tagging using adversarial neural networks.  United States.  doi:10.1103/PhysRevD.96.074034.

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                    Shimmin, Chase, Sadowski, Peter, Baldi, Pierre, Weik, Edison, Whiteson, Daniel, Goul, Edward, and Søgaard, Andreas. Mon .  
        "Decorrelated jet substructure tagging using adversarial neural networks".  United States.  doi:10.1103/PhysRevD.96.074034.

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@article{osti_1405551,

  title        = {Decorrelated jet substructure tagging using adversarial neural networks},

  author       = {Shimmin, Chase and Sadowski, Peter and Baldi, Pierre and Weik, Edison and Whiteson, Daniel and Goul, Edward and Søgaard, Andreas},

  abstractNote = {},

  doi          = {10.1103/PhysRevD.96.074034},

  journal      = {Physical Review D},

  number       = 7,

  volume       = 96,

  place        = {United States},

  year         = {2017},

  month        = {10}

}

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DOI: 10.1103/PhysRevD.96.074034

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Works referenced in this record:

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Title: Decorrelated jet substructure tagging using adversarial neural networks

Citation Formats

Towards an understanding of the correlations in jet substructure: Report of BOOST2013, hosted by the University of Arizona, 12th–16th of August 2013 journal, September 2015

Jet Substructure as a New Higgs-Search Channel at the Large Hadron Collider journal, June 2008

Boosted objects and jet substructure at the LHC. Report of BOOST2012, held at IFIC Valencia, 23rd–27th of July 2012 journal, March 2014

Identifying boosted objects with N-subjettiness journal, March 2011

Parameterized neural networks for high-energy physics journal, April 2016

Maximizing boosted top identification by minimizing N-subjettiness journal, February 2012

Event generation with SHERPA 1.1 journal, February 2009

Jet substructure at the Tevatron and LHC: new results, new tools, new benchmarks journal, May 2012

Boosting low-mass hadronic resonances journal, September 2016

Thinking outside the ROCs: Designing Decorrelated Taggers (DDT) for jet substructure journal, May 2016

Presentation of search results: the CL s technique journal, September 2002

Jet substructure classification in high-energy physics with deep neural networks journal, May 2016

Asymptotic formulae for likelihood-based tests of new physics journal, February 2011

Energy correlation functions for jet substructure journal, June 2013

Power counting to better jet observables journal, December 2014

Jet trimming journal, February 2010

Learning Factorial Codes by Predictability Minimization journal, November 1992

PYTHIA 6.4 physics and manual journal, May 2006

DELPHES 3: a modular framework for fast simulation of a generic collider experiment journal, February 2014

Boosted objects: a probe of beyond the standard model physics journal, June 2011

The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations journal, July 2014

Confidence level computation for combining searches with small statistics journal, September 1999

FastJet user manual: (for version 3.0.2) journal, March 2012

Towards an understanding of the correlations in jet substructure: Report of BOOST2013, hosted by the University of Arizona, 12th–16th of August 2013
journal, September 2015

Jet Substructure as a New Higgs-Search Channel at the Large Hadron Collider
journal, June 2008

Boosted objects and jet substructure at the LHC. Report of BOOST2012, held at IFIC Valencia, 23rd–27th of July 2012
journal, March 2014

Identifying boosted objects with N-subjettiness
journal, March 2011

Parameterized neural networks for high-energy physics
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Maximizing boosted top identification by minimizing N-subjettiness
journal, February 2012

Event generation with SHERPA 1.1
journal, February 2009

Jet substructure at the Tevatron and LHC: new results, new tools, new benchmarks
journal, May 2012

Boosting low-mass hadronic resonances
journal, September 2016

Thinking outside the ROCs: Designing Decorrelated Taggers (DDT) for jet substructure
journal, May 2016

Presentation of search results: the CL _s technique
journal, September 2002

Jet substructure classification in high-energy physics with deep neural networks
journal, May 2016

Asymptotic formulae for likelihood-based tests of new physics
journal, February 2011

Energy correlation functions for jet substructure
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Power counting to better jet observables
journal, December 2014

Jet trimming
journal, February 2010

Learning Factorial Codes by Predictability Minimization
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PYTHIA 6.4 physics and manual
journal, May 2006

DELPHES 3: a modular framework for fast simulation of a generic collider experiment
journal, February 2014

Boosted objects: a probe of beyond the standard model physics
journal, June 2011

The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations
journal, July 2014

Confidence level computation for combining searches with small statistics
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journal, March 2012