Transcript Calorimeter Algorithms

Calorimeter Algorithms
Gregorio Bernardi for the
CALGO and CAT groups
 A few remarks on the calo. problems
 Overview of the CAT force results
 From CAT to CALGO
 Results of the CALGO workshop
 The road ahead
convenors meeting, Sep 4th 2003
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DISCLAIMER
Different more or less important problems affect
the calorimeter
However:
The calorimeter data are “waiting” for other
subdetector data improvements in order to go to
publication:
The Reprocessing is NEEDED mainly to improve the
Tracking
The Calorimeter “fixing” can be done and redone
and redone from the TMB’s in a few days.
personal opinion: From the analysis point of view the
fake jets problem is, for the moment, our main
problem in the calorimeter.
convenors meeting, Sep 4th 2003
G.B. for CALGO
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D0 Calorimeter Algorithms Task Force
(MAY –JULY 2003)
Members of the Task Force
Gregorio Bernardi (chair), Jonathan Hays, Serban Protopopescu,
Markus Klute, Jan Stark, Robert Zitoun, Vishnu Zutshi
+ Emmanuel Busato, Jean-Roch Vlimant
Charge to the Task Force:
The task force will optimize in collaboration with the Physics and
ID-groups the calorimeter algorithms for precision physics. It will
start from the achievements of the Calorimeter Task Force, continue
to improve the algorithms and propagate them to the physics objects
using as benchmarks the comparison data/simulation of the W (->e nu)
transverse mass spectrum and Jet & Met resolutions in di-jet events.
The task force is expected to coordinate the efforts in the different
groups related to the calorimeter.
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Specifically, the task force should:
1) Make progress on the understanding/correction of the calorimeter noise.
2) Finalize the development of an optimized 0-suppression scheme and study
its consequences for MET, EM, Tau and Jet ID.
3) Make progress on the understanding of the EM response/resolution, using
on-line and off-line tools.
4) Make progress on the data/mc agreement of the calo object
reconstruction and of the energy flow algorithm.
5) Use large statistics of W and di-jets events to display how the
progress achieved on points 1-4 propagates in the corresponding
physics distributions.
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Correcting the DATA
Many problems are not discovered immediately online.
- BLS electronics problems
- cable swaps
- not all hot cells are caught online
 Large datasets on tape with some quality issues.
These data sometimes suffer from isolated problems. Can fix these
isolated problems and use the data for publication quality analyses.
But: need mechanisms to do this.
 cal_corr_dst package
Takes raw calorimeter data and fixes known problems
 included in reprocessing
Can also be included in user analysis jobs
(because we have the individual cell energies in the thumbnail).
Requires some effort as calorimeter reconstruction needs to be rerun.
CAT MODEL HAS BEEN TAKEN ON BOARD BY COMMON SAMPLE GROUP
C. S. group now centrally fixes the TMBs (while we are waiting for the
result of the p14 reprocessing).
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DQ Issues Addressed in
Current Version of cal_corr_dst
- Energy sharing problem
Draft D0 note:
http://www-clued0.fnal.gov/~stark/esp_note.ps
- Tower two problem
Draft D0 note:
http://www-clued0.fnal.gov/~stark/tower2/note.ps
- BLS cable swap
next slide
Short term project:
kill hot cells found by dq_calo
Web page with latest version of cal_corr_dst:
http://www-clued0.fnal.gov/~stark/cal_corr_on_tmb.txt
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Most recent addition to cal_corr_dst
Correction for BLS cable swap:
J. Gardner
The “discovery” of the swap was
triggered by an analysis plot
/ distribution of all EM candidates:
pT > 25 GeV
EM fraction > 0.9
isolation < 0.15
HMx8 < 20
pink boxes: tower two problem
blue boxes: energy sharing problem
red boxes: don’t know yet…
Nice example of constructive feed-back
from analysis.
Donuts ? Cable swaps !
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Reducing influence of Noise: T42
T42: reject ALL isolated cells below 4 sigmas
(and ALL negative energy cells)
Full description is available
in DØNotes 4124, 4146
Select high signal cells (4 sigma)
Keep their significant neighbours (2 sigma)
Thresholds 2 is 2.5 at the moment  T42.5
Available in D0Reco
in shadow mode
Not running yet:
What neighbours means
We wants to have
first a tmbfix
w/o T42
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T42 on high energy electrons
Estimators for EM candidates in data, when pT>13 GeV
OK !
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T42 on Missing and Scalar ET
WZ skim , p13.06 , W e nu selection (ET > 20 GeV, MET > 25 GeV)
Compared to Pythia MC
No T42
After T42
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Jets properties before and after T42
Top group’s alljets skim (reco version p13.06.01) :
* Passes the 4JT10 trigger.
* At least 4 jets (JCCB).
* HT > 100 GeV (just plain sum of uncorrected JCCB jets).
 20000 events
Jets are JES corrected.
No quality cuts applied because jet id distributions change significantly.
t42
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no t42
G.B. for CALGO 11
New Jet Seeding in p14
Remove CH and MG cell energies from the seed
tower energy before starting preclustering
(i.e., a p13 seed might have an energy < 500 MeV
in p14)
Jets not found with
Jets found in
both cases:
new seeding:
about 3-4% less
jets
with new
seeding
Jets not found
with new
seeding :
mean = 0.43
mean = 2.22
- mostly low pT
- in ICR
- large number of
proto-jets merging
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JET – ID: Plans for the future
High priority task remains reduction of fake jets
Are T42, new jet seeding, hardware fixes
enough ?
Jet ID cuts  new certification
Use L1 confirmation ?
Tuning of Jet ID criteria for ICD region.
Tuning of merging algorithm ?
Consider lowering jet pt threshold
6 GeV (to make analysis at 10 - 12 GeV)
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MET subgroup Goals
MET Resolution: related to Jes, T42 …
Treatment of non reconstructed jets
Overall correction strategy of MET
 Decides how to correct EM/Jets etc..
Understanding of unclustered energy
- in QCD processes
- in EW events
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CALGO: Activities & Structure
CALOP - calo
hardware &
operations
CALGO - calorimeter
algorithms & objects
R. Zitoun
U.Bassler/ G. Bernardi
CAT
cal-simulation
Leslie Groer, Michel Jaffre’
em-id
Harald Fox, Jan Stark
calib – online
data taking
hardware
slow control
trigger L1/L2
-id
Yurii Maravin
Alton
cal – dq
jet-id
Slava Shary,
Jan Stark
Slava Kulik
Alexander Kupco
cal/icd-softw.
met
Jan Stark/Lee Sawyer
Patrice Verdier,
Sophie Trincaz
cps-software
eflow
A. Magerkurth/D.Alton
Anna Goussiou
Jon Hays
fps-software
icd
Drew
A. Patwa/A. Turcot
l3cal-software
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jes
Ia Iashvili/
Nirmalya Parua
tau-id
Dhiman Chakraborty /
Serban
Protopopescu
G.B.
for CALGO 15
CALORIMETER WORKSHOP contributions
Welcome/Goals of the Workshop (15')
U. Bassler/G. Bernardi
Shutdown Status/Operation Organization
R. Zitoun
Data Quality
V. Shary/J. Stark
Overview
J. Stark
zero-bias monitoring & bad cell correction V. Shary
Level 3 (20')
V. Buescher
Simulation Status and Prospects
L. Groer
Tau-id
Jet-id
D. Chakraborty/S. Protopopescu
S. Kulik/A. Kupco
jet-id status and plans
S. Kulik
jet reconstruction and simulation
V. Zutshi
Jet and Met while studying Wbb production G. Bernardi
Missing ET (30')
MET status (15')
cal_t42 status (15')
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S. Trincaz/P. Verdier
P. Verdier
J.R. Vlimant
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Jet Energy Scale
I. Iashvili/N. Parua
JES status and plans
I.Iashili
Response measurement for b-jets
T.Kurca
Showering measurement with MC method
J.Rani
Energy Flow (30')
A. Goussiou/J. Hays
electron-id/calibration
H. Fox/J. Stark
Introduction
H. Fox/J. Stark
EM reconstruction packages
S. Crépé-Renaudin
H-matrix, data/MC agreement
M. Jaffré/T. Vu Anh
Electron likelihood (2*)
J. Kozminski, S.-J. Park
EM scale corrections (10')
S. Kermiche
photon-id
D. Alton/Y. Maravin
FPS software
J. Lazaflores/A.Patwa
CPS Status
D. Alton
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Jet Energy Scale
Offset (p13.06 data, p13.08 MC)
Special Min Bias runs
Pythia UE + 0.8 minbias
Response (p13.06
data,
p13.08
MC)
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JES: Smaller Uncertainty
Offset
Luminosity dependence OK
Response
Increased statistics: 15  55 pb-1
EM scale included
Systematics: background, topology, vertex
MC used for extrapolation at high energies
Total
in central region: 9.5%  5.5%
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|η|=0.0
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Response: b-jets vs q-jets (MPF method)
R jet
 mis 
ET  nˆT
 1
ET
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Jet Resolutions
Resolution at ET~50 GeV
Run I
Run II
11.6%
14% (data/MC)
More to Understand !
Z → bb resolution
various algorithms (p13.08, uncor.)
Rcone= 0.5
18.1%
Rcone= 0.7
17.5%
0.4 kT
18.3%
1.0 kT
17.7%
Rcone=0.5
before correction
18.1%
after JES correction
17.0%
Use Tracks+clusters?
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JCCA cone jets have no energy correction applied
CellNN calibrated using linear fit to response measured using
single charged pion Monte-Carlo.
Potential significant improvement: need to calibrate
tracks/objects on data. Here results zqq MC with p13
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Electron identification
calorimeter cells
For low-pT non-isolated
electrons: road method.
cone, cellNN
clusters
C/FPS clusters
electron candidates
calibration
- geometric corrections
- EM scale corrections
- phi cracks
tracks
possibly with dE/dx
Start from tracks, look at
energy deposits in a
narrow road around the
track extrapolated through
the calorimeter; see if these
deposits are EM-like.
electron candidates
for analysis
sophisticated discriminants:
H-matrix, likelihood
The whole chain needs to be certified.
Quite some Monte Carlo dependence: geometric corrections, training of H-matrix, analysis, …
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Low-pT di-EM triggers in trigger list v12.x
Trigger list v12 contains a new low pT di-EM trigger.
 useful data samples for EM validation studies
Summary of the selection criteria used by this trigger:
L1:
CEM(2,3.) CEM(1,6.) TTK(2,3.) TTK(1,5.)
L2:
|| restriction to central region
L3:
two road electrons ( > 3 GeV and > 5 GeV, one tight one loose)
7.6 pb-1
Reconstructed using road method.
Fit result (signal parameters):
N (one tight) = 614 +/- 113
Mass

a
n
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=
=
=
=
3.040 +/- 0.005
0.071 +/- 0.005
0.61 +/- 0.12
1.7 +/- 1.1
G.B. for CALGO 24
Data: J/,   e+ e- using EM clusters
HMx8 < 50
HMx8 < 20
Fit results (signal parameters):
N (J/Psi)
Mass (J/Psi)
Resolution (J/Psi)
= 152 +/- 15
= 3.166 +/- 0.040 GeV
= 0.382 +/- 0.043 GeV
N (J/Psi)
Mass (J/Psi)
Resolution (J/Psi)
= 82 +/- 9
= 3.166 +/- 0.040 GeV
= 0.305 +/- 0.037 GeV
N (Upsilon)
Mass (Upsilon)
Resolution (Ups)
= 70 +/- 18
= 10.31 +/- 0.18 GeV
= 0.584 +/- 0.144 GeV
N (Upsilon)
Mass (Upsilon)
Resolution (Ups)
= 55 +/- 13
= 10.12 +/- 0.17 GeV
= 0.689 +/- 0.190 GeV
comparison of fitted yields gives information on HMx cut efficiency.
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Calibration at low Energy
To investigate the high  mass, take the
HMx8 < 20 sample and compare the mass
distributions obtained from clusters and
tracks for the same events.
 mass obtained from tracks appears to be
more reasonable, but need to check
resolutions with  Monte Carlo.
 yield
 Mass (GeV)
resolution (GeV)
clusters
55 +/ 13
10.12 +/- 0.17
0.69 +/- 0.19
tracks
68 +/- 11
9.43 +/- 0.11
0.62 +/- 0.10
mass from
EM clusters
mass from
tracks
Potential calibration Improvement
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Electron Resolution

S
N

C 
E
E
E
From Monte-Carlo with
corrections
S = (0.199 ± 0.008)%
N = (0.42 ± 0.08) GeV
C = (0.0076 ± 0.0014)%
MC momentum resolution
3% @ 50 GeV
expect:
Z mass resolution 2%
Z MC 2.2%
Data 4.0%  3.1 %
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Various Corrections
Corrections in
D0reco +
emcandidate
Further
calibration
corrections
Other trials
MZ/GeV
Z/GeV
Z/MZ(%)
raw ADC
81.5
3.6
4.4
non linearity
86.7
3.7
4.3
gain correction
86.6
3.6
4.2
crate equalization
86.5
3.6
4.1
geometric correction
90.2
3.6
4.0 ± 0.1
calibration timing
90.2
3.6
4.0
physics timing
90.2
3.6
3.9
calib/phys amplitude
90.0
3.4
3.8
after tuning weights
90.4
3.3
3.7
use 2 calweights
90.4
3.3
3.7
pulser amplitudes
90.2
3.4
3.8
10  slices
90.4
3.3
3.7
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Module Boundaries (Phi) ?
CC has 32 modules with Dj=0.2
loss of clusters (?)
loss of energy
Broader effect on mass
mass
Broader effect on mass
Cluster no
vs track angle
smallest distance to crack→
Origin ? Statistics ?
Cluster E
vs cluster angle
shower profile
out in
MZ/GeV
Z/GeV
Z/MZ
All
90.4
3.3
3.7
|dj|>0.05
91.3
2.8
3.1
|dj|<0.05
89.6
3.2
3.6
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Dead Material Simulation
Modeling of the phi cracks (electric fields and
charge collection)
Modeling of the dead-material
Modeling of preamp charge collection signal
Improvement done for solenoid
Improving the material map for the
SMT cables, infrastructure, cooling…
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EM ID estimators: data vs MC
p14.03.00 data and MC
EM CC Cluster widths in r-phi
EM ID v4.1
2 good electrons, pT > 20 GeV,
|_det| < 2.5, not within
cracks, Mee > 50 GeV
At least 1 track match in data
Many distributions are ok
pT, isolation, transverse shower
shapes in r-phi, EMfractions,
HMx41 CC
EM CC Cluster widths in z
Discrepancies in a few
(MC normally narrower)
HMx8 components:
#2 (~ logE and z) and #4 (z)
Number cells in lower layers CC
CC profile/shower shape in 
and R
HMx6 ?
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CPS
Spatial resolution
MC study: energy resolution
Resolution in  of 1.58 mr (MC 1.5 mr) Green shows the improvement using
Resolution in z of 3.2 mm(MC 2.5 mm) the CPS.
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E/E
G.B. for CALGO 32
Progress on Photon ID
Currently, a photon is an electron with no matched central
track, Why is this not good?
HMatrix does not work well for electrons, not easy to make it
work for photons
NEW TOOLS UNDER STUDY:
Tracks
Matching tracks to CPS-EM objects
Isolation
Hit counting
PS
Use both CFT and SMT
Matching to EM/TRK
Shapes of clusters, p0- separation?
HMx
Check if electron HMx works well enough on photons
Train it on a sample of  (?)
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TRK-CPS-EM matching
d =
0.00683
3d floor
From a sample of good Zee candidate
Require exactly two good EM objects
Match them with CPS clusters:
3d floor method:
Match CPS and EM (3d floor)
in (, ) space
c2 method:
Use all floors
Fit to a straight line
d =
0.00671
3d floor
Wrong cluster
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Good
G.B. forcluster
CALGO 34
Priority Tasks
• Em-energy resolutions (electrons, photons)
• Data/simulation agreement: shower shapes, cracks
• Data quality strategy (on-line/off-line)
• Noise understanding / Fake Jets / T42 integration
• J.E.S. / hadronic energy resolution
• Calorimeter compensation studies (E-Flow)
• -id
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Future dates
 CALGO meetings devoted to specific projects:
…
October 21st: met corrections, DQ
October 28th: em-resolution / simulation
 p14 certification of calorimeter software and
objects: November 21st (JES: Nov. 28th)
god-parenting by CAT
 Next calorimeter workshop: December 2nd/3rd
rd/4th
or
3
convenors meeting, Sep 4th 2003
G.B. for CALGO 36
Backup slides
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MET Run Selection
Using METB (no CH, except in
good JCCB jets)
METxy
Pretty stable with time (METxy
most sensitive)
Good run selection based on
METxy  < METx  2  < METy  2
rms(METxy)
rms MET-xy
<SET>
91% good runs (feb-jun 2003)
could be lower with tighter cuts
could be higher with software
corrections
MUST be update for p14
for TMBfixed data
convenors meeting, Sep 4th 2003
<SET>
G.B. for CALGO 38
TRK-CPS / TRK-CPS-EM matching
Require exactly two CPS-EM objects
Propagate track to the middle of CPS
Calibrate track propagation
Check TRK-CPS relative alignment
Select the closest track in (z, ) space
In the Zee sample:
TRK-EM (traditional) matching probability is 84 ± 2% (AA)
TRK-CPS-EM matching probability is
floor method: 95.8 ± 1.1%
c2 method: 92.8 ± 1.3%
Fake rate estimation is in progress
convenors meeting, Sep 4th 2003
G.B. for CALGO 39
JES: b-quarks & parton-level
New semi-leptonic correction for b-jets (p13.08 MC)
Added dependence on parent quark (in addition to Emu, ptrel, Ebjet
b  μν + X
Parton-level
Correction:
light q
b-q
b  c  μν + X
convenors meeting, Sep 4th 2003
G.B. for CALGO 40