Published February 7, 2017
| Version v1
Dataset
Open
Pythia Generated Jet Images for Location Aware Generative Adversarial Network Training
- 1. Lawrence Berkeley National Laboratory
- 2. Yale University
Description
Dataset containing 872666 jet images to train Location Aware Generative Adversarial Networks (LAGAN) for High Energy Physics. Results are published in [arXiv:1701.05927].
Format:
HDF5 file with the following fields:
- 'image' : array of dim (872666, 25, 25), contains the pixel intensities of each 25x25 image
- 'signal' : binary array to identify signal (1, i.e. W boson) vs background (0, i.e. QCD)
- 'jet_eta': eta coordinate per jet
- 'jet_phi': phi coordinate per jet
- 'jet_mass': mass per jet
- 'jet_pt': transverse momentum per jet
- 'jet_delta_R': distance between leading and subleading subjets if 2 subjets present, else 0
- 'tau_1', 'tau_2', 'tau_3': substructure variables per jet (a.k.a. n-subjettiness, where n=1, 2, 3)
- 'tau_21': tau2/tau1 per jet
- 'tau_32': tau3/tau2 per jet
Details:
- Simulated using Pythia 8.219 at √ s = 14 TeV
- Image pre-processing using method from in L. de Oliveira et al., Jet-Images -- Deep Learning Edition [arXiv:1511.05190]
- scikit-image==0.12.0 implementation of cubic spline rotation
- Finite calorimeter granularity simulated with 0.1×0.1 grid in η and φ, with η × φ ∈ [−1.25, 1.25] × [−1.25, 1.25]
- Jet clustering with anti-kt algorithm with a radius R = 1.0 using FastJet 3.2.1; constituent re-clustering into R = 0.3 kt subjets
- Intensity of pixel = pT of cell
- 60 GeV < mjet < 100 GeV
- 250 GeV < pTjet < 300 GeV
- Sparse images (~10% NNZ)
Full dataset description in [arXiv:1701.05927].
Notes
Files
Files
(2.2 GB)
Name | Size | Download all |
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md5:f9b11c46b6a0ff928bec2eccf865ecf0
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2.2 GB | Download |
Additional details
Related works
- Is new version of
- 10.5281/zenodo.268592 (DOI)
- Is supplement to
- arXiv:1701.05927 (arXiv)
References
- L. de Oliveira, M. Kagan, L. Mackey, B. Nachman and A. Schwartzman, Jet-images — deep learning edition, JHEP 07 (2016) 069 [1511.05190].
- T. Sjostrand, S. Mrenna and P. Z. Skands, A Brief Introduction to PYTHIA 8.1, Comput. Phys. Commun. 178 (2008) 852–867 [0710.3820].
- T. Sjostrand, S. Mrenna and P. Z. Skands, PYTHIA 6.4 Physics and Manual, JHEP 0605 (2006) 026 [hep-ph/0603175].