Simple PYTHIA8 program that uses fastjet to generate events, precluster them with the anti-kt algorithm with R = 0.8, and write events with the leading jet satisfying pt > 170 GeV to a ROOT TTree.
There are several examples, including
-
$Z$ +jets events where the Z decays to electron or muon pairs (zjets.cfg) - QCD multijets events (
qcd_multijet.cfg) - KK gravitons with various masses decaying to
$Z$ boson pairs (gravkk_zz_1TeV.cfg, also for 2 and 3 TeV) - SM
$ZZ$ production (zz.cfg)
This Docker image is based on RIVET.
To launch the container from your host computer, execute this command:
bash ./runDockerCommandLine.sh 8888 srappoccio/pythia-gen-jets:latest
You then have a few options when you are running in the docker container:
Once you are in the docker image, to run ROOT:
source setup.sh
root -l
If you want to run jupyter with ROOT,
root --notebook --no-browser --ip 0.0.0.0
Then point your local browser to localhost and put in the generated token from the previous command.
Once you are in the docker image, to run jupyter with scipy ecosystem things like coffea and tensorflow, make sure you have NOT run setup.sh (this will set up ROOT) and instead:
source launch.sh
If you are running on winterfell, the bash script in the above examples should be runDockerWinterfell.sh instead of runDockerCommandLine.sh in order to mount the /mnt directory.
Since ROOT (the software package) only allows the "root" linux user in the docker container, there are often problems with running the jupyter version in ROOT. This may give na error like
PermissionError: [Errno 13] Permission denied: '/usr/local/root/etc/notebook/migrated'
If this is the case, log out and log in, but DO NOT source the setup.sh script.
If you're on the command line, you can generate events with pythia2root. Several of the notebooks also contain commented-out configurations that can be run directly.
source setup.sh
pythia2root
Output:
usage: pythia2root config_file root_file n_events
Example:
pythia2root test_run_all.cfg test.root 1000
Currently we use AK8 jets and store those with pt > 170 GeV, where <90% of the jet's energy arises from leptons. The latter is to remove jets comprised almost entirely of isolated leptons (like Z->ll).
The leading 3 jets are stored, and the indices of the first 500 constituents of those 3 jets.
The output TTree uses the default PYTHIA8 "Event" for the gen particle information. It also stores the AK8 jets and the indices of their constituents in flat branches. Here is the structure:
nJet = number of jets (ignores lepton-only jets)
nParticle = number of particles in those jets
jet_pt = array of pt
jet_eta = array of eta
jet_phi = array of phi
jet_m = array of m
jet_nc = array of number of constituents per jet
particle_ndx = indices of particles preclustered by jet
jet_ndx = jet "this" particle belongs to.
%\cite{Cacciari:2011ma}
\bibitem{Cacciari:2011ma}
M.~Cacciari, G.~P.~Salam and G.~Soyez,
%``FastJet user manual,''
Eur.\ Phys.\ J.\ C {\bf 72} (2012) 1896
[arXiv:1111.6097 [hep-ph]].
%%CITATION = ARXIV:1111.6097;%%
%\cite{hep-ph/0512210}
\bibitem{hep-ph/0512210}
M.~Cacciari and G.~P.~Salam,
%``Dispelling the $N^{3}$ myth for the $k_t$ jet-finder,''
Phys.\ Lett.\ B\ {\bf 641} (2006) 57
[hep-ph/0512210].
%%CITATION = PHLTA,B641,57;%%
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@article{Bierlich:2019rhm,
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archivePrefix = "arXiv",
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}