14 TeV pp collisions, SM type, PYTHIA8 generator: tev14pp_qcd_pythia8_weighted
Abstract
Inclusive dijet events for pT>40 GeV. (PhaseSpace:pTHatMin=40 GeV). PDF: LHAPDF6:NNPDF23_lo_as_0130_qed and Tune:pp = 14 (Monash 2013 Tune). 5,000 events per file. How to use: The events are weighted to obtain good statistics up to large pT. This feature is set via PhaseSpace:bias2Selection and PhaseSpace:bias2SelectionPow = 5.0. Use the event weights to obtain the correct pT distribution.
- Authors:
-
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Publication Date:
- DOE Contract Number:
- AC02-06CH11357
- 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:
- SM; PYTHIA8; LO+PS+hadronisation; Monte Carlo; simulations; particle physics; high energy physics
- OSTI Identifier:
- 1575701
- DOI:
- https://doi.org/10.34664/1575701
Citation Formats
Chekanov, S. 14 TeV pp collisions, SM type, PYTHIA8 generator: tev14pp_qcd_pythia8_weighted. United States: N. p., 2017.
Web. doi:10.34664/1575701.
Chekanov, S. 14 TeV pp collisions, SM type, PYTHIA8 generator: tev14pp_qcd_pythia8_weighted. United States. doi:https://doi.org/10.34664/1575701
Chekanov, S. 2017.
"14 TeV pp collisions, SM type, PYTHIA8 generator: tev14pp_qcd_pythia8_weighted". United States. doi:https://doi.org/10.34664/1575701. https://www.osti.gov/servlets/purl/1575701. Pub date:Thu Aug 24 00:00:00 EDT 2017
@article{osti_1575701,
title = {14 TeV pp collisions, SM type, PYTHIA8 generator: tev14pp_qcd_pythia8_weighted},
author = {Chekanov, S.},
abstractNote = {Inclusive dijet events for pT>40 GeV. (PhaseSpace:pTHatMin=40 GeV). PDF: LHAPDF6:NNPDF23_lo_as_0130_qed and Tune:pp = 14 (Monash 2013 Tune). 5,000 events per file. How to use: The events are weighted to obtain good statistics up to large pT. This feature is set via PhaseSpace:bias2Selection and PhaseSpace:bias2SelectionPow = 5.0. Use the event weights to obtain the correct pT distribution.},
doi = {10.34664/1575701},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2017},
month = {8}
}
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