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Report
A Study of
Electron Identification
Jim Branson
UCSD
with collaborators from FNAL, UCSB & UCSD
Electron ID in CMS
• Need high efficiency, particularly in H4 lepton channel.
• Need efficiency at low ET for for low mass H4 lepton and
HWW
– Background increases at low ET
– High background from fakes will complicate analyses
• CMS has some unusual features that impact electron ID.
– High field
– Thick tracker
– Ecal with e/ near 2
• Need to use all the tools available to understand and
optimize electron ID.
– Understand physics of electron measurement now,
– multivariate analyses… could come later, perhaps.
2
This is a Study of e ID
• Attempt to learn about e ID in CMS
– No multivariate analysis for now
• Don’t feel constrained by current algorithms
– But benefit from what was learned
• Aim for high selection efficiency, 97%
• Try to compare to current cut-based e-ID
– But “the current ID” is not fully ready
– And we’ve changed enough that comparison won’t be
fair.
• Look at very simple 5 cuts
• And at what we can gain with some understanding
of the measurement.
– Hopefully still “simple enough” (and more stable?)
3
Standard Electron ID
•
•
•
•
Match in  and 
Loose cut on E/p (not very useful in CMS)
Shower shape requirements (only in CMS)
E/H cut (not very powerful in CMS (barrel))
We can use other “features” of CMS to help with electron ID.
4
E/p often Affected by p Measurement
Zee
ptrack  pMC
pMC
ESC  EMC
E MC
E/p
E/p
5
Remove Some Producer Cuts
Some producer cuts are too tight.
**See talk of Matteo Sani
double maxEOverPBarrel = 3.
double maxEOverPEndcaps = 5.
double minEOverPBarrel = 0.35
double minEOverPEndcaps = 0.35
double maxHOverE = 0.2
double maxDeltaEta = 0.02
double maxDeltaPhi = 0.1
double ptCut = 5.  1.5
Keep these
This increases the denominator for selection efficiency calculations
and therefore decreases the efficiency calculated.
6
Apply Simple Cuts on Five Variables
1.
2.
3.
4.
5.
 < cut
in < cut
Eseed/Pout > cut
in < cut
H/E < cut
*can we replace this?
With straight cuts on these quantities, we get 97.3%
selection efficiency and 4.1% of dijet(50-80) events
having a fake electron.
7
How much better can we do
by using a bit more complex
cut-based analysis?
To describe the electron ID
algorithm, we will show plots from
the Barrel only for simplicity.
Others in backup slides.
8
Use this 2D Plot to Study e ID
E/p
Fakes from jets
Electrons from Zee
fbrem
9
Color the Picture
Electrons from Zee
Mainly GOOD electrons
Fakes from jets
Mainly fakes
Electrons and jets overlap (Pyrite).
We call a color in this picture a category.
Are there selection differences beween the categories?
10
What is the Physics Behind
Electrons from Zee
E/p
fbrem
1. E/p is often well
measured for
electrons
2. Electrons
usually radiate a
good deal of
energy in the
tracker
3. E/p is not often
measured to be
less than 1 for
electrons
11
What is the Physics Behind
1. Fakes from jets
usually have fbrem
around 0 (just
charged pion
tracks…)
2. Many fakes from
jets have E/p<1
partly because of
the low response of
ECAL to charged
pions...
Maybe some
enhancement
due to interaction
in tracker
12
Why Categories?
Electrons
fakes
Jets
• Large differences in s/b in regions of this plot.
– Looser cuts in high s/b regions.
• Try to use robust differences between
electrons and jets.
13
Categories do two things
• Separate regions of high signal to background
from low.
• Put events of similar characteristics together.
–
–
–
–
–
Well measured electrons
Electrons with track problems
Electrons with supercluster problems.
Fakes due to overlap
Fakes due to charge exchange…
14
Apply simple cuts in each category
1.
2.
3.
4.
5.
 < cut
in < cut
Eseed/Pout > cut
in < cut
H/E < cut
Look in Seven categories (for STUDY).
Look at barrel and endcap separately.
No Isolation Cuts Applied
15
Selection Cuts
All electrons
Surviving electrons
ET<15 electrons failing cuts
All fake candidates
Surviving fakes

E/p

Fbrem

H/E
16
Eseed/Pout
Base Categories on This Plot
E/p
2
5
1
3
0
4
7
Fbrem=(Pin-Pout)/Pin
17
 in Categories
“n-1” plots
Looser cuts in
best category
1
0
3
4
Electrons
2
5
Jets
18
 in Categories
“n-1” plots
0
1
1
43
5
4
Electrons
2
2
5
3
7
Jets
Tighter cuts in
overlap category
Basically, we tighten the cut until it
starts to cut more than a few electrons.
19
 in Categories
Looser 
cut for worst
E/p category
“n-1” plots
0
1
1
43
5
4
Electrons
2
2
5
3
7
Jets
20
Eseed/Pout in Categories
“n-1” plots
0
4
1 2
1
0
3
5
4
Electrons
3 2
5
7
Jets
21
H/E in Categories
“n-1” plots
0
1
1
43
5
4
Electrons
2
2
5
3
7
Jets
22
The Cuts: 22 values
Barrel
 bad
if E/p bad
Endcap
Cat.
0
1
2
3
4
5
Ncut
<
0.014
0.0125 0.0125 0.0125 0.0125 0.0125
2

0.009
0.0085 0.0085 0.0035 0.0085 0.0035
3

0.06
0.06
E/Pout>
0.55
H/E
0.10
0.02
0.06
0.06
3
0.88
0.88
0.88
0.88
0.88
2
0.125
0.055
0.055
0.10
0.055
0.055
3
<
0.031
0.028
0.028
0.028
0.028
0.028
2

0.009
0.009
0.009
0.009
0.009
0.009
1

0.06
0.10
0.10
0.02
0.10
0.10
3
E/Pout>
0.85
0.85
0.85
0.85
0.85
1
H/E<
0.125
0.10
0.10
0.10
0.10
2
0.85
0.10
Use looser cuts
Critical overlap
for the best
Category with
electrons.
E/p=1
For selection, we really only need 3-4 categories.
23
Why 22 Cut Parameters
Barrel Endcap
Sum
5 Cut-Variables
5
5
10
Looser Cuts on best
electrons
4
3
7
3
1
4
1
0
1
5+8
5+4
22
Claim looser cuts on best electrons make us less sensitive
at startup!
Different Cuts in overlap
region
and high E/p overlap
Open  cut for worst
E/p
Total
24
Simplification
• Reduce to 3 categories
– Brem e with E/p1
– Little brem e
– Bad track E/p≠1 (brem)
• Open up  cut a bit for E/p>>1
• (Cut out low E/p && low fbrem region where there are
almost no e)
25
Why I Like this Selection
• Looser cuts for best electrons makes
selection more robust.
• Tighter cuts in overlap region maintains
robust rejection of fakes.
• Robust separation of regions since pion
tracks should have fbrem0.
– No dependence on clustering algorithms.
• (We must work with E/p for energy
measurement anyway)
26
Nota Bene
• The 3 Categories can just be used for the
selection.
• There is no reason we need to use them for
later analysis.
27
Results on Standard Electron Reco
ETSC>5
-2.5<<2.5
THIS Selection
22 param.
THIS
Just 5 cuts,
Not tuned
Selection
Efficiency for e
from Zee
97.0%
97.3%
91.8%**
Fakes per di-jet
event QCD_50_80
1.5%
(0.75%per jet)
4.7%
(2.3%per jet)
8.8%**
(4.4% per jet)
No Isolation
Cuts
Applied
Standard
Selection
CrackGold
*Not fair: All crack electrons are accepted in the standard
selection.
** Coded by us for comparison under same conditions.
highly preliminary.
28
Efficiency
Reco Eff.
Reco*Sel. Eff. (THIS)
Reco*Sel. Eff. ootb
All use same standard reco.
ET
Crack electrons treated
as golden for ootb selec.

29
Cracks
• Selection efficiency dips by about 5% in the
cracks in the ECAL.
– The crack events have distributions similar to
background
– They are removed by all of the cuts.
– Special selection in cracks would clearly allow
background in cracks.
• We don’t think there is much to be gained in
the cracks.
30
Accepted Crack Electrons: SC OK
All electrons
Crack electrons
ESC/E
31
Low ET Electrons
• Our selection efficiency also dips by about
5% at low ET.
• Some events with low E/p populate
background regions.
• Probably best to look at SuperCluster reco
to see if some energy can be recovered.
• Would also help reconstruction efficiency.
32
More Cuts? No.
Isolation
33
Summary of Loose Selection
• We can have a loose selection for electrons
with about 97% efficiency and low fake rate.
• A hopefully “robust” categorization uses E/p
and fbrem.
– Electrons and fakes separate to a great extent
in this categorization.
– Separate different types of measured events.
• Simple cuts are used to work on
understanding of electrons.
34
New Electron Sequence
• Try to match each reconstructed Super Cluster to a standard
Combinatorial Track Finder (CTF) seed:
– using the GlobalMixedSeed collection:
• we expect an efficiency improvement at least at large eta since
the number of pixel layers is lower and the CTF seeder uses the
Silicon Strip hits in addition.
– at the moment the matching is done with all the seeds inside a fixed
size cone around the Super Cluster direction.
• For each matched seed we propagate the track using the standard
Gaussian Sum Filter (GSF) builder:
• Feed the matched pair (Super Cluster & track) to the standard
electron producer adapted to return a new collection of identical
objects labelled as “GlobalGsfElectrons”.
GGE
- EGamma POG
From Matteo Sani 06/08/2007meeting
See also talk in
Higgs meeting by
Boris Mangano.
35
Comparison in Zee events
• The following table reports the number of candidate
electrons reconstructed by either our custom or the standard
algorithm.
• A candidate is defined by a Super Cluster and a CTF track
matching the MC electron direction.
GGE reconstructs electron
but OOTB152 fails.
OOTB152 – OK OOTB152 – FAILS
GGE – OK
5296
734
GGE - FAILS
28
84
OOTB152 reconstructs
electron but GGE fails.
From Matteo Sani
06/08/2007 - EGamma POG
meeting
36
Preliminary e-ID Performance
On GGE reco sequence
Standard
ETSC>5
THIS
This reco is
Selection
Selection
new and a
-2.5<<2.5
CrackGold
rapidly
Selection
moving
Efficiency
target.
96.8%
90.7%
for e from
Results are
Zee
therefore
Fakes per
very
1.2%
5.6%
dijet event
preliminary.
(0.6%
per
jet)
(2.8%
per
jet)
QCD_50_80
37
A Look at Tighter e-ID
-2.5<<2.5
PTMC>5
Selection
Efficiency for e
from Zee
Fakes per
dijet event
QCD_50_80
ETSC>5
Fakes per
dijet event
QCD_50_80
ETSC>10
Loose Selection
5 cut params.
TkIso<7
96.9%
3.1%
2.2%
96.9%
1.5%
0.99%
Loose Selection
(6 cat  60 param.)
TkIso<7
97.2%
1.3%
0.95%
97.4%
0.60%
0.42%
Loose Selection
(22 cut param.)
TkIso<7
96.8%
1.2%
0.94%
96.6%
0.56
0.40%
Tight Selection
TkIso<7
94.1%
94.4%
0.53%
0.22%
0.40%
0.16%
38
Summary
• New electron loose electron selection with high
efficiency and low background.
– Even good with very simple cuts
• Study of simple vs. “less simple” selection
– Factor of 2.5 in fake rate
• Study of tighter selection
– 2.7% lower eff. For more than factor of 2 in fake rate
• Isolation seems to commute with selection
• New reconstruction sequence using standard
seeder from tracker, also shows similar high
selection efficiency and low background.
– With higher reco efficiency
39

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