100 TeV pp collisions, Exotics type, PYTHIA6 generator: tev100pp_zprime_pythia6_ttbar

doi:10.34664/1575574

Title: 100 TeV pp collisions, Exotics type, PYTHIA6 generator: tev100pp_zprime_pythia6_ttbar

Abstract

Zprime (M=10 TeV) to ttbar at a 100 TeV collider. Zprime decays to ttbar. Events generated with PYTHIA6 for full simulation. The sample was made for detector studies and does not have modern underlying event tune. Consider using samples generated with Pythia8.

Authors:

Chekanov, S.

Argonne National Lab. (ANL), Argonne, IL (United States)

Publication Date:: 2016-11-15

DOE Contract Number:: AC02-06CH11357

Product Type:: Dataset

Research Org.:: Argonne National Lab. (ANL), Argonne, IL (United States). HepSim Monte Carlo Event Repository

Sponsoring Org.:: USDOE Office of Science (SC)

Subject:: 72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Keywords:: Exotics; PYTHIA6; LO+PS+hadronisation; Monte Carlo; simulations; particle physics; high energy physics

OSTI Identifier:: 1575574

DOI:: 10.34664/1575574

Citation Formats


                    Chekanov, S. 100 TeV pp collisions, Exotics type, PYTHIA6 generator: tev100pp_zprime_pythia6_ttbar.  United States: N. p., 2016. 
        Web.  doi:10.34664/1575574.

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                    Chekanov, S. 100 TeV pp collisions, Exotics type, PYTHIA6 generator: tev100pp_zprime_pythia6_ttbar.  United States.  doi:10.34664/1575574.

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                    Chekanov, S. 2016.  
"100 TeV pp collisions, Exotics type, PYTHIA6 generator: tev100pp_zprime_pythia6_ttbar".  United States.  doi:10.34664/1575574.  https://www.osti.gov/servlets/purl/1575574. Pub date:Tue Nov 15 00:00:00 EST 2016

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@article{osti_1575574,

  title        = {100 TeV pp collisions, Exotics type, PYTHIA6 generator: tev100pp_zprime_pythia6_ttbar},

  author       = {Chekanov, S.},

  abstractNote = {Zprime (M=10 TeV) to ttbar at a 100 TeV collider. Zprime decays to ttbar. Events generated with PYTHIA6 for full simulation. The sample was made for detector studies and does not have modern underlying event tune. Consider using samples generated with Pythia8.},

  doi          = {10.34664/1575574},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {2016},

  month        = {11}

}

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DOI: 10.34664/1575574

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