Hadronic Calibration Archive Page
21/11/03:
Latest plots:
24/11/03:
1000 event files:
25/11/03:
2 bugs found:
- H1CalcElec::GetSumOfElectrons did not go through GetElectron(i),
breaking the interfacace to the mODS - result: when doing
GetAllFsLessElectron(), the SumOfElectrons and the first electron
return different vectors for events with only one electron!! This is
because GetElectron(i) allows for using track information, whereas
accessing the mODS directly always goes through the cluster.
- There is a bug in the filling code of elec cones. Eg, in 2
electron events the cones are filled with identical vectors. Emmanuel
will fix this..
26/11/03:
Checking mODS vs HAT vectors.. (UNCALIBRATED)
I'm trying to check what is going on between the HAT and the mODS so
that I can get a coherent picture of what the HFS is.
Output files:
Event 262208/112997 contains 1 isolated electron, and nothing in the
spacal, ie the HAT variables that matter are Lar and Tra.
HAT Total:
Pxh = -13.6585
Pyh = 9.40819
Pth = 16.5852
HAT Lar:
Px = -12.61
Py = 8.99012
Pt = 15.4866
HAT Tra:
Px = -1.04853
Py = 0.418075
Pt = 1.12881
On the mODS there are 20 PartCands, 19 of which are labelled HFS (the
other being the isolated, scattered electron). Of these 19 HFS partcands,
1 is a track and the 18 others are LAr.
mODS Total:
Px = -13.6912
Py = 9.42765
Pt = 16.6231
mODS Lar: (IsEm() || IsCluster())
Px = -12.6426
Py = 9.00957
Pt = 15.5245
mODS tra: (IsHFSChargedTrack() || IsHFSChargedGoodTrack() || IsMuon())
Px = -1.04853
Py = 0.418075
Pt = 1.12881
So the track agrees, but the LAr is different....
Event 262206/21469 contains 2 isolated electron, and nothing in the
spacal. In this event there are 24 PartCands, 2 of which are the
isolated electrons and 22 HFS particles, of which 5 are Tra and the
remaining 17 Lar. In this event I see agreement of all vectors between
mODS and HAT... puzzling... (28/11 - could be Iron/Plug, will check today)
Total:
Px = -0.726466
Py = -12.9517
Pt = 12.972
Lar:
Px = 0.423057
Py = -4.03045
Pt = 4.05259
Tra:
Px = -1.14952
Py = -8.92124
Pt = 8.995
Latest plots:
- Inclusive selection with HadrooII calibrated plots.
- Marseille selection with HadrooII calibrated plots.
- Inclusive selection with HadrooII calibrated with the TProfiles
set to 0.8 -> 1.2 plots (ignore the
other plots).
- Marseille selection with HadrooII calibrated with the TProfiles set to
0.8 -> 1.2 plots
(ignore the other plots).
28/11/03:
Additional plots added of Pth/Pte and Pth/PtDa for different gamma
regions:
- Inclusive selection with (HadrooII calibrated) plots.
- Marseille selection (HadrooII calibrated) plots.
New full sets of plots:
- Inclusive selection with (HadrooII calibrated) plots.
- Inclusive selection with additional requirement of only 1 electron
and 0 muons (HadrooII calibrated) plots.
- Inclusive selection with additional requirement of only 1 electron
and 0 muons and minimum jet theta of 7 degrees (HadrooII calibrated) plots.
- Marseille selection (HadrooII calibrated) plots.
03/12/03:
New plots, uncalibrated (
) and with
HadrooII calibration applied (
).
Decided to stick to the Inclusive selection from now on, after
discussion in the High-Q2 meeting 02/12.
Also new variable, gammah^e = 2*atan((2*27.6 - (Ee-Pze))/Pte) used in
addition to old plots.
The ratio gammah^e/gammah is shown in the kinematics plots below.
The four main plots requested by
Cristi: pth/ptda vs ptda, pth/ptda vs gammah^e and the same dependence
for yh/yda
Basic kinematics, electron quantities
etc including profiles of Ee/Eda as a function of zimpact-electron and
phi-electron
Profiles of Pth/Pte balance as a function of
zimpact-hadrons and phi-hadrons
Profiles of Yh/Yda balance as a function of
zimpact-hadrons and phi-hadrons
Profiles of Pth/Ptda balance as a
function of zimpact-hadrons and phi-hadrons
Profiles of Pte/Ptda balance as a
function of zimpact-hadrons and phi-hadrons
E-pz in zimpact-electron sections
Pth/Pte in zimpact-hadron sections
Profiles of balances as a function of gammah for
different Pte ranges ( with y-axis range 0.9 - 1.1)
Profiles of balances as a function of Ptda for different
Pte ranges ( with y-axis range 0.9 - 1.1)
Profiles of balances as a function of Pte for different
Pte ranges ( with y-axis range 0.9 - 1.1)
Profiles of balances as a function of gammah^e for
different Pte ranges ( with y-axis range 0.9 - 1.1)
Pth/Pte and Pth/Ptda in bins of
gammah
Pth/Pte and Pth/Ptda in bins of
gammah^e
The aim now would be to reproduce these plots, used in the recent
Inclusive analysis T-Zero talk, (initially?) not in bins of Q2 and x,
but in the different gamma bins.
This involves fitting the distributions to a gaussian, which I have
begun, here using 0.5*RMS and 1.1*RMS as the lower and upper bounds
respectively:
Data Pth/Pte and Pth/Ptda in bins of
gammah
Django Pth/Pte and Pth/Ptda in bins
of gammah
Data Pth/Pte and Pth/Ptda in bins of
gammah^e
Django Pth/Pte and Pth/Ptda in bins
of gammah^e
04/12/03:
After discussions in OO meeting, it as decided to add two more bins to
the gamma plots, ie gamma < 10, 10 -> 20, 20 -> 30, ..., 140 -> 150,
gamma > 150 degrees.
I'm still not sure/convinced which gamma to use so here are both for
now.
The calibration seems to make the balances worse at low gammah(^e)..
Pth/Pte in bins of gammah
Pth/Ptda in bins of gammah
Pth/Pte in bins of gammah^e
Pth/Ptda in bins of gammah^e
Fits, once again using using 0.5*RMS and 1.1*RMS as the lower and
upper bounds respectively:
Data Pth/Pte in bins of gammah
Data Pth/Ptda in bins of gammah
Django Pth/Pte in bins of gammah
Django Pth/Ptda in bins of gammah
Data Pth/Pte in bins of gammah^e
Data Pth/Ptda in bins of gammah^e
Django Pth/Pte in bins of gammah^e
Django Pth/Ptda in bins of gammah^e
12/12/03:
Latest plots from calibration checks, with HadrooII calibration using
the full Inclusive sample:
All of the main control plots as one file.
The four main plots requested by Cristi: pth/ptda vs
ptda, pth/ptda vs gammah^e and the same dependence for yh/yda
Profiles of balances as a function of
gammah for different Pte ranges (with y-axis range 0.9 - 1.1)
Profiles of balances as a function of
Ptda for different Pte ranges (with y-axis range 0.9 - 1.1)
Profiles of balances as a function of
Pte for different Pte ranges (with y-axis range 0.9 - 1.1)
Profiles of balances as a function of
gammah^e for different Pte ranges (with y-axis range 0.9 - 1.1)
Fits: I also now added in y-balance plots as a function of gammah and
gammah^e, still using 0.5*RMS and 1.1*RMS as the lower and upper
bounds respectively:
Data Pth/Pte in bins of gammah
Data Pth/Ptda in bins of gammah
Data Yh/Yda in bins of gammah
Django Pth/Pte in bins of gammah
Django Pth/Ptda in bins of gammah
Django Yh/Yda in bins of gammah
Data Pth/Pte in bins of gammah^e
Data Pth/Ptda in bins of gammah^e
Data Yh/Yda in bins of gammah^e
Django Pth/Pte in bins of gammah^e
Django Pth/Ptda in bins of gammah^e
Django Yh/Yda in bins of gammah^e
Now plotting the mean of the fits in each of the gammah(^e) bins for
each of the balances:
Mean of Pth/Pte fit result in bins of gammah ( y-axis range 0.95 - 1.05)
Mean of Pth/Ptda fit result in bins
of gammah ( y-axis range 0.95 - 1.05)
Mean of Yh/Yda fit result in bins of gammah ( y-axis range 0.95 - 1.05)
Mean of Pth/Pte fit result in bins of
gammah^e ( y-axis range 0.95 - 1.05)
Mean of Pth/Ptda fit result in bins
of gammah^e ( y-axis range 0.95 - 1.05)
Mean of Yh/Yda fit result in bins of gammah^e ( y-axis range 0.95 - 1.05)
Finally, the ratio of Data/MC for the six plots above (I have NOT yet
double checked the errors on these plots):
(Pth/Pte)DATA/(Pth/Pte)MC in bins of gammah
(Pth/Ptda)DATA/(Pth/Ptda)MC in bins of gammah
(Yh/Yda)DATA/(Yh/Yda)MC in bins of gammah
(Pth/Pte)DATA/(Pth/Pte)MC in bins of gammah^e
(Pth/Ptda)DATA/(Pth/Ptda)MC in bins of gammah^e
(Yh/Yda)DATA/(Yh/Yda)MC in bins of gammah^e
07/01/04:
Added error bands to "ratio" plots:
The mean of the fits in each of the gammah(^e) bins for each of the
balances ( y-axis range 0.95 - 1.05)
Ratios of Data/MC
David South
Last modified: Thu Jan 8 18:32:06 MET 2004