This repository contains the recommended scale factors for several tau discriminators, and tools to read them. More detailed recommendations can be found on this TWiki page: https://twiki.cern.ch/twiki/bin/viewauth/CMS/TauIDRecommendationForRun2
To install the tool for reading the tau ID scale factors, do
export SCRAM_ARCH=slc6_amd64_gcc700 # for CMSSW_10_3_3, check "scram list"
CMSSW_BASE=CMSSW_10_3_3 # or whichever release you desire
cmsrel $CMSSW_BASE
cd $CMSSW_BASE/src
git clone https://github.com/cms-tau-pog/TauIDSFs TauPOG/TauIDSFs
cmsenv
scram b -j8
After compiling with this respective directory hierarchy, you can acces the tool (python/TauIDSFTool.py) in python as
from TauPOG.TauIDSFs.TauIDSFTool import TauIDSFTool
A test of the tool can be run with
./test/testTauIDSFTool.py
A similar C++ implementation is available (src/TauIDSFTool.cc). A test in C++ (test/testTauIDSFTool.cc) can be compiled and run with
scram b runtests -j8
The SFs in data are meant for the following campaigns:
| Year label | MC campaign | Data campaign |
|---|---|---|
2016Legacy |
RunIISummer16MiniAODv3 |
17Jul2018 |
2017ReReco |
RunIIFall17MiniAODv2 |
31Mar2018 |
2018ReReco |
RunIIAutumn18MiniAOD |
17Sep2018/22Jan2019 |
As an example, to get the scale factors for the tight working point of the 'MVAoldDM2017v2' tau ID in 2017, initialize the tool as
from TauPOG.TauIDSFs.TauIDSFTool import TauIDSFTool
tauSFTool = TauIDSFTool('2017ReReco','MVAoldDM2017v2','Tight')
and to retrieve the scale factor for a given tau pT, do
sf = tauSFTool.getSFvsPT(pt)
The scale factor should only be applied to tau objects that match "real" taus at gen-level (genmatch==5). You can pass the optional genmatch argument and the function will return the appropriate SF if genmatch==5, and 1.0 otherwise,
sf = tauSFTool.getSFvsPT(pt,genmatch)
The recommended uncertainties can be retrieved as
sf_up = tauSFTool.getSFvsPT(pt,genmatch,unc='Up')
sf_down = tauSFTool.getSFvsPT(pt,genmatch,unc='Down')
or, all three in one go:
sf_down, sf, sf_up = tauSFTool.getSFvsPT(pt,genmatch,unc='All')
Analysis using ditau triggers and tau pT > 40 GeV, may use DM-dependent SFs as
from TauPOG.TauIDSFs.TauIDSFTool import TauIDSFTool
tauSFTool = TauIDSFTool('2017ReReco','MVAoldDM2017v2','Tight',dm=True)
sf = tauSFTool.getSFvsDM(pt,dm,genmatch)
sf_up = tauSFTool.getSFvsDM(pt,dm,genmatch,unc='Up')
sf_down = tauSFTool.getSFvsDM(pt,dm,genmatch,unc='Down')
where genmatch is optional.
To apply SFs to electrons or muons faking taus, use the eta of the reconstructed tau and the genmatch code (1 for prompt electrons, 2 for prompt muons, 3 for electrons from tau decay and 4 for muons from tau decay):
python/TauIDSFTool.py
antiEleSFTool = TauIDSFTool('2017ReReco','antiEleMVA6','Loose')
antiMuSFTool = TauIDSFTool('2017ReReco','antiMu3','Tight')
antiEleSF = antiEleSFTool.getSFvsEta(eta,genmatch)
antiMuSF = antiMuSFTool.getSFvsEta(eta,genmatch)
The uncertainty is obtained in a similar way as above.
The tau energy scale (TES) is provided in the files data/TauES_dm_*.root. Each file contains one histogram ('tes') with the TES centered around 1.0. It should be applied to a genuine tau by multiplying the tau TLorentzVector, or equivalently, the tau energy, pT and mass as follows:
file = TFile("data/TauES_dm_2016Legacy.root")
hist = file.Get('tes')
tes = hist.GetBinContent(hist.GetXaxis().FindBin(dm))
# scale the tau's TLorentzVector
tau_tlv *= tes
# OR, scale the energy, mass and pT
tau_E *= tes
tau_pt *= tes
tau_m *= tes
A simple class, TauESTool, is provided to obtain the TES as
from TauPOG.TauIDSFs.TauIDSFTool import TauESTool
testool = TauESTool('2017ReReco')
tes = testool.getTES(dm)
tesUp = testool.getTES(dm,unc='Up')
tesDown = testool.getTES(dm,unc='Down')