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Tau ID scale factors

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

Installation

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

Python

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

C++

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

Scale factor versions

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

Usage

pT-dependent SFs

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')

DM-dependent SFs

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.

Eta-dependent SFs for the anti-lepton discriminators

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.

DM-dependent tau energy scale

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')