BjetTLA.jl
Run 3 TLA analysis with Beautiful jets
ANA-EXOT-2024-01
Skip to content 
The Big Picture
The scope of this package is to take TLA private ntuples (produced by these xAH config files) and produce analysis plots and histograms. In the future, it may include also fitting or statistical interpretations.
Where to find input ntuples
If you have access to /eos/atlas are, you can find the input files at:
/eos/atlas/atlascerngroupdisk/phys-exotics/jdm/ANA-EXOT-2024-01_dibjetISR/ntuplesIf you are running analysis on AF UChicago, you can find the same set of input files at:
/data/jiling/TLA/eos_ntuplesNote
See Private ntuple schema page for the full description about data and how it's prepared.
Minimal Working Example
MC ntuples
To get the "right" number of expected events into histograms when using MC samples, you need to worry keep track of weights. In particular, you need three weights, the sumOfWeight and pmgWeight are not event-wise, you obtain them from metadata (either in a histogram inside the same file, or from a PMG file on /cvmfs/ are), see also get_pmg_weight.
julia
julia> using BjetTLA, UnROOT, FHist
julia> file_path = "/data/jiling/TLA/eos_ntuples/mc23a/Zprime_bb/user.sfranche.510392.MGPy8EG_S1_qqa_Ph25_mRp125_gASp1_qContentUDSC.e8514_s4162_r15315._nv0.1_tree.root/user.sfranche.38342968._000001.tree.root";
julia> weight_hist = UnROOT.parseTH(ROOTFile(file_path)["MetaData_EventCount"]; raw=false);
julia> sumOfWeight = bincounts(weight_hist)[3]
111726.1421289444
julia> dsid = BjetTLA.extract_dsid(file_path)
"510392"
julia> pmgWeight = BjetTLA.get_pmg_weight(dsid)
0.7831930217100002Then you can write your event-loop and fill histograms using the obtained weights in combination with the per-event evt.mcEventWeight:
julia
julia> tree = LazyTree(file_path, "TreeAlgo_noCalib/nominal");
julia> myhist = Hist1D(; binedges = 0:10)
julia> for evt in tree
genWeight = evt.mcEventWeight
wgt = genWeight * (pmgWeight / sumOfWeight)
n_hard_photon = count(>(20), evt.ph_pt)
push!(myhist, n_hard_photon, wgt)
end
julia> myhist
edges: [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0]
bin counts: [0.010480257533107834, 0.26589324498441064, 0.004167311195126139, 3.1301815413685986e-5, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
total count: 0.2805721155280583At the end of this example, the bincounts of myhist correspond to number of expected events for this signal process if we have
julia
julia> run2022_lumi = 24537.39;
julia> myhist * run2022_lumi
edges: [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0]
bin counts: [257.1581663903048, 6524.326250548028, 102.25494004617617, 0.7680648525136243, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
total count: 6884.507421837022Developer Note
The packages that are good to be familiar with: