JER mapping
A mapping is needed to transpose from
to
after fitting the resolution for a given
[\eta^\text{rec}, p_T^\text{gen}]
bin.Some information is shared, obtained from colleagues on the implementation of such mapping.
To begin with, we make TH1Fs with the
p_T^\text{rec}
distribution and the jet response p_T^\text{rec}/p_T^\text{gen}
for each [\eta^\text{rec}, p_T^\text{gen}]
bin. Examples of histograms inside the output root file:
KEY: TH1F JetPt_JetEta0.348to0.435_RefPt90to120;1
KEY: TH1F RelRsp_JetEta0.348to0.435_RefPt90to120;1
KEY: TH1F JetPt_JetEta0.348to0.435_RefPt120to150;1
KEY: TH1F RelRsp_JetEta0.348to0.435_RefPt120to150;1 and so on for all other remaining
[\eta^\text{rec}, p_T^\text{gen}]
bins (RefPt = p_T^\text{gen}
, JetPt = p_T^\text{rec}
, RelRsp is the Response).
The code related for this task can be found here.
Then given the above root file we make a loop over all histograms for each
\eta^\text{rec}
bin in order to:Take mean via
TH1F::GetMean() of JetPt_JetEta0.348to0.435_RefPt90to12 histogram and the mean of the RelRsp_JetEta0.348to0.435_RefPt90to120.We then make a point in a graph via
TGraphErrors::SetPoint(point, mean_JetPt, 1/median_RelRSP).We repeat this for all
p_T^\text{gen}
bins and we create a TGraphErrors with 1/median(response) vs \langle p_T^\text{rec}\rangle
(1/median is taken for the sake of their studies, in our case we should plot the quantity of interest, the plain median).We repeat for all other
\eta^\text{rec}
bins.
The code that performs this task can be found here, for example in L213-314.
So since initially you have response vs
p_T^\text{gen}
you go to the median(response) or the inverse of it as a function of \langle p_T^\text{rec}\rangle
.