Production-cross-sections-of-Inert-Doublet-Model
OpenML dataset with id 43534
Author name not available (Why is that?)
Full work available at URL: https://api.openml.org/data/v1/download/22102359/Production-cross-sections-of-Inert-Doublet-Model.arff
Upload date: 23 March 2022
Dataset Characteristics
Number of features: 13 (numeric: 13, symbolic: 0 and in total binary: 0 )
Number of instances: 50,625
Number of instances with missing values: 0
Number of missing values: 0
Context 'Learning the production cross-sections of the Inert Doublet Model'
Cite as Humberto Reyes-Gonzlez, Andre Lessa, Sydney Otten. (2020). 'Learning the production cross sections of the Inert Doublet Model' training data set. [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3689678 Content Pheno AI training dataset used in the Learning the production cross-sections of the Inert Doublet Model subproject, made of 50000 samples with 5 input values:
MH0 MA0 MHC lam2 lamL
and 8 target values
xsec353513TeV xsec363613TeV xsec373713TeV xsec353713TeV xsec363713TeV xsec373513TeV xsec373613TeV xsec353613TeV
from a parameter space of the Inert Doublet Model chosen as: 50 MH0, MA0, MHC3000GeV; 2 lam2, lamL2. The cross-sections were computed at leading order using MADGRAPH2.6.4 and the IDM UFO implementation from the FeynRules database. Inert Doublet Model The inert doublet model, a minimal extension of the Standard Model by a second higgs doublet with no direct couplings to quarks or leptons, is one of the simplest scenarios that can explain the dark matter. Additional information Pheno AI training data Les Houches project for a database of networks for regression and classification of quantities relevant for particle physics phenomenology. Curated by: scaron123 Curation policy: Contact organisers of the Les Houches project Created: June 25, 2019 Harvesting API: OAI-PMH Interface Acknowledgements
darkmachines.org
phenomldata.org
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