Transcript Document 7472212

D
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Jet and Electron Identification in
the Run 2 DØ Detector
Tevatron Run 2
DØ Detector upgrade
 SMT
 CFT
 Preshower + ICD
 Calorimeter
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Jet ID
 Algorithms
 NADA
 Trigger
 Selection
 Energy Scale
 QCD Results
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EM ID
 Reconstruction
 Trigger
 Profile
 Scale
Leslie Groer
Columbia University, New York
DPF 2002, Colonial Williamsburg, VA
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Leslie Groer
Columbia University
May 25, 2002
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
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Tevatron Run 2
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Chicago
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Booster
CDF
New Main Injector and Recycler rings
Increased luminosity and energy
48 pb-1 delivered
15.2 pb-1 recorded physics events
 L dt expected for 2002: 300 pb-1
Run 2a: 2 fb-1
DØ
Tevatron
p source Main Injector
(new)
Run 1b
Run 2a
Run 2b
#bunches
6x6
36x36
140x103
s (TeV)
1.8
1.96
1.96
1.6x1030
8.6x1031
5.2x1032
 Ldt (pb-1/week)
3.2
17.3
105
bunch xing (ns)
3500
396
132
interactions/xing
2.5
2.3
4.8
typ L (cm-2s-1)
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Leslie Groer
Columbia University
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Detector Commissioning;
Timing in; Improve electronics,DAQ and offline
First Collisions
Run II start
DØ roll-in
DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
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Overview of Run 2a DØ Upgrade
 Upgrade Calorimeter electronics
readout and trigger
 Add scintillator in muon for fast
trigger and extended coverage for
drift chambers
 Replace inner tracking volume with
Silicon and Fiber trackers with 2T
solenoid magnetic field for central
tracking and momentum
measurement
azimuthal angle 
 Add preshower detectors and
pseudorapidity  = -ln tan(/2)
replace intercryostat detectors
 Pipelined 3 Level trigger
Muon, Calorimeter, Silicon fully commissioned and
 Increase DAQ capability for 132 ns
operational
bunch crossings
Fiber tracker and preshowers fully instrumented. Central
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electronics complete, forward in a few weeks—
commissioning this summer
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Leslie Groer
Columbia University
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Silicon Microstrip Tracker
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4 H-Disks
12 F-Disks
6 Barrels
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Tracking up to || = 3
Provide good position resolution for
vertexing
Innermost layer at r = 2.6 cm
Central region
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Forward region
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6 barrels, 4 layers,
axial + 2o/90o stereo
12 cm long each, SS+DS
12 F-disks (SS)
4 H-disks (SS)
793k channels
Radiation hard up to 1 Mrad
>90% channels operational
S:N > 10:1
Leslie Groer
Columbia University
SS: single sided
DS: double sided
More in Harald Fox’s
talk
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Central Fiber Tracker
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0 p.e.
1 p.e.
Tracking out to || = 1.7
Good momentum resolution
2 p.e.
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20 cm < r < 51 cm, 1.8 / 2.6 m fibers
8 double layers (axial, stereo 3o)
77,000 830m fibers readout with
VLPC
Operate at 9 K, 85% Q.E., good S/N
~10 photons/m.i.p. get to the VLPC
Impact parameter resolution ~42 m
for SMT+CFT tracks with pt > 3 GeV
No individual ladder or layer
alignments yet
Beam spot size is about 28 m
Trackers shifted in z by 2.9 cm w.r.t
calorimeter  shifts zo
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Leslie Groer
Columbia University
3 p.e.
pT > 3 GeV
d~42 m
Beam spot ~28 m
CFT axial + stereo + SMT
FPS
d
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
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Preshowers and Intercryostat Detector
Central and Forward Preshowers
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CPS
FPS
Intercryostat Detector (ICD)
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Central mounted on solenoid (|| < 1.2)
Forward on calorimeter endcaps
(1.4 < || < 2.5)
CPS: 7,680 FPS: 14,000 channels
Extruded triangular scintillator strips
with embedded WLS fibers and Pb absorber
Improve energy resolution measurements
Trigger on low-pT EM showers
Reduce overall electron trigger rate by x3-5
Same readout electronics as CFT
384 scintillator tiles with WLS fiber to
phototubes in low-B field region for readout
Improve coverage for the region 1.1 < || < 1.4
Improves jet ET and missing-ET
Readout through Calorimeter electronics
LED pulsers used for PMT calibration
Relative yields measured > 20 p.e./m.i.p.
Leslie Groer
Columbia University
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ICD
DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Calorimeter Overview
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North End Cap
Central Cal.
South End Cap
L. Ar in gap
2.3 mm
Cu pad readout on 0.5 mm
G10 with resistive coat epoxy
Drift time 430 ns
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Liquid argon sampling
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Stable, uniform response, rad. hard, fine spatial seg.
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LAr purity important
Uranium absorber (Cu (CC) or Steel (EC) for coarse hadronic)
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Compensating e/  1, dense  compact
Uniform, hermetic with full coverage
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|| < 4.2 (  2o), l int > 7.2 (total)
Single particle energy resolution
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e: sE / E = 15% /E + 0.3% : sE / E = 45% /E + 4%
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Leslie Groer
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Columbia University
50k readout cells (<0.1% bad) Ur absorber
Fine segmentation,
 5000 semi-projective towers (0.1x0.1)
 4 EM layers, shower-max (EM3): 0.05 x 0.05
 4/5 Hadronic (FH + CH)
L1/L2 fast Trigger readout 0.2x0.2 towers
MG
CH
OH
ICD
FH
MH
EM
FPS
EM
IH
DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
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Calorimeter Electronics Calibration
Electronic readout 
“live” sampled energy in L.Ar. 
calibrated energy scale
Determine electronic calibration coefficients for
absolute and channel-to-channel variations from
pulser charge injection (DACADC)
Dual gain readout with analog storage in
switched capacitor arrays (SCA)
Non-linear behavior of SCA chip observed for
low energies
 ADC to GeV about 300 MeV underestimation
per cell
 Nonlinearity < 0.5% for cells > 1 GeV
 Has significant effect in low energy region
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(jet widths and resolutions etc)
Can apply universal parametrized correction for
all channels
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 Residuals after correction are better than
5 ADC counts on the whole range for both
gains
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Correct energy in cells before clustering
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ADC
ADC
vs DAC
pulser
shaper
output
pulser ADC
readout
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dual gain
Parameterized correction based on
residuals compared to linear fit
1 ADC ~ 4 MeV
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Leslie Groer
Columbia University
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In calibration, correct for signal shape
difference with simulation
Also correct for cell-to-cell gain (ADC/DAC)
dispersion (5 to 10%)
Apply  intercalibration comparing slices
in  -- flat within 2% after correction
Improves both Zmass mean and resolution
DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Jet Finding
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Calorimeter jet
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Jet is collection of towers with a given cone R
R  Δ 2  Δη2
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Cone direction maximizes the total ET of the jet
Various clustering algorithms
Particle jet
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After hadronization
A spread of particles running roughly in the same direction as
the parton
Correct for finite energy resolution
Subtract underlying event (modeled by minimum bias data)
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Parton jet
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Parton hard scattering and parton
showers well described by pQCD
Higher cross-section expected in
Run 2 for higher c.m.s s=1.96TeV
 x2 s for pT > 400 GeV
Jet inclusive pT spectrum
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Leslie Groer
Columbia University
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Run 2 Jet Algorithms
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Draw a cone of fixed size around a seed
Compute jet axis from ET-weighted
mean and jet ET from ET’s
Draw a new cone around the new jet
axis and recalculate axis and new ET
Iterate until stable
Algorithm is sensitive to soft radiation
Improved Run 2 cone
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Run 1 Legacy Cone
Use 4-vectors instead of ET
Add additional midpoint seeds between
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pairs of close jets
Split/merge after stable protojets found
Algorithm is infrared safe
kT-algorithm
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Cell Nearest Neighbor
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Floor-by-floor clustering starting with EM3
Each local maximum starts a floor cluster then
add in neighbors
Energy sharing according to transverse shape
parameterization
Angular matching of floor clusters
Search for minima in longitudinal energy
distribution to separate EM and hadronic
showers
Energy Flow algorithm
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use tracking information to better characterize
the contributions from charged particles
In development
Recombination algorithm based on
relative momentum between ‘particles’
Theoretically favored, no split-merge
To reduce computation time, start with
0.2 x 0.2 preclusters
Most results using simple cone for now
Leslie Groer
Columbia University
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
NADA
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NADA = New Anomalous Deposit
Algorithm
Identify anomalous isolated energy
deposits in the calorimeter = “Hot Cells”
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Improve object resolution and MET
Run 1: AIDA
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Source: electronics, U noise,
beam splash, cosmics etc
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Examine all cells with > 1 GeV
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Remove cells < -1 GeV & > 500 GeV
ET < 5 GeV removed if no neighbor with
E > 100 MeV
ET < 500 GeV removed if no neighbor
with E > 2% Ecell
High efficiency (90%) and low
misidentification
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ET > 1 GeV : ~0.5%
ET > 10 GeV : ~0%
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Only examine neighbors in the same
tower for Ecell > 10 GeV
 On average about 0.8 cells / event
99% efficient,
ETthresold
BUT 5-10% misidentification rate
Not used for cells on boundaries of
layers
FH1 and CH1 have more material
Leslie Groer
Columbia University
ETneighbour> 100 MeV or 0.02Ecell
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Jet Selection
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Central jets (Run 2 cone, R=0.7)
Event Quality Cuts
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CHF
EMF
Leading Jet Cuts
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Number of jets  1
Etotal in the calorimeter  2 TeV
Missing ET  70% of the
leading jet pT
Zvtx < 50 cm
DØ Run 2 Preliminary
Jet pT > 8 GeV (offline cut)
0.05  EMF  0.95
CHF  0.4 (0.25 tight)
HotF  10 (5 tight)
(HotF = ET1st cell / ET2nd cell )
n90 > 1 (number of towers that
contain 90% of jet ET)
HotF
 Data
Efficiencies from MC
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Loose: ~100%
~Flat in eta
n90
Tight: ~ 98%
— MC
 Non-linearity of SCA included in MC
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Leslie Groer
Columbia University
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Jet Energy Scale
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jet
 Correct Jet Energy back to the particle level
ptcl
E jet
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E meas
 Eoffset
jet
cone
R calo
R
jet
jet
 Eoffset energy offset from underlying event, pile-up,
Uranium noise
 determined from Min. Bias Events
Photon-jet Events
 Rcalo calorimeter response
 Calibrate EM response on Zee mass
peak
 Measure from ET balance in +jet events
 Rcone energy contained in jet cone
 Correct for losses due to out-of-cone showering
 Use MC-energy in cones around the jet axis
Preliminary correction being applied with ~10% systematic uncertainty
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Leslie Groer
Columbia University
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Central Jet Triggers
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All L1 trigger towers at || <0.8 are instrumented, complete coverage coming soon
 L2 jet
Efficiency vs jet pT
CJT(1,3)
CJT(1,5)
CJT(1,7)
CJT(1,10)
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 L3 jet
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L1 Trigger efficiency CJT(1,x)
L1 Trigger efficiency CJT(2,x)
 L1 single jet efficiencies
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Simple cone or tower NN
algo’s 0.1x0.1 towers
3 single jet triggers
(single tower):
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Ask for one or two hadronic trigger towers (0.2x0.2)
above threshold
Use muon trigger as unbiased reference for statistics to
measure turn-ons
Ask for one and only one reconstructed jet in ||<0.7
L1 hadronic response about 40% low for current data set
Leslie Groer
Columbia University
Cluster 3x3 or 5x5 trigger
towers around L1 seed
towers
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JT_LO L1: 5 GeV,
L3:10 GeV
JT_HI L1:10 GeV,
L3:15 GeV
CJT40: L1:40 GeV
Efficiency
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Standard jet selection,
offline pT > 8 GeV
Very sharp turn on
DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
First Run 2 QCD Physics
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Inclusive jet pT spectrum at 1.96 TeV
Dijet mass spectrum at 1.96 TeV
Ldt = 1.9 ± 0.2 pb-1
Ldt = 1.9 ± 0.2 pb-1
Only statistical errors
Only statistical errors
Highest 3-jet event
ETjet1 : 310 GeV
Etjet2 : 240 GeV
ETjet3 : 110 GeV
Etmiss : 8 GeV
 Central jets
 Not fully corrected distributions:
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Preliminary correction for jet energy scale
(but no unsmearing or resolution effects)
 30-50% systematic error in cross-section
No trigger selection efficiency corrections
Leslie Groer
Columbia University
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
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EM ID and Reconstruction
Concentrate on high PT objects
Look for
narrow isolated
clusters with high
EM fraction, track
match for electrons,
none for 
Electron object
reconstruction
 PTmin>1.5 GeV
 EM fraction > 0.9
 Isolation
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Hmatrix
Measure compatibility of EM cluster with an
electron shower  2
 Discriminate against hadronic () decays that
pass EM fraction and isolation cuts
 Use longitudinal and transverse shower
shapes to take into account correlations
between energy in cells
 Tuned on MC in   bins of 0.1,  < 3.2 for different
energies
 HMx8 / HMx9 / Hmx41
 Energy fractions in each
floor
 CC: 3x3 EM towers
(PS), EM1, EM2, EM3, EM4
 EC: All cells in cone of 20 cm radius
HM41 Run 1
 ,  in EM3
at EM3 around hottest channel
test beam+We
 grid (6,6)
 Track match pT > 1.5, R<0.5
 log(Etot)
Preliminary fake rate calculated from 2nd
log2
unbiased jet passing standard EM selection  Z/s vertex
z
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in jet triggers  0.60.1%
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e
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Leslie Groer
Columbia University
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Triggering on electrons
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L1 EM Trigger
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L1 TT vs Offline
Use 3x3 NN algorithm with 1 GeV seed
L3 EM Trigger
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To measure the trigger efficiency, select
good EM objects:
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L1 Trigger effic.
CEM(1,x)
L2 EM Trigger
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Look for single EM trigger
tower (0.2 x 0.2) over threshold
Scale calibrated ~10%
No hadronic veto
Use “bootstrap” method to
calculate efficiencies
L3 Trigger effic.
EM frac > 0.9, isolation < 0.2,
HM41 < 200, || < 0.8
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L3EM(1,15,emfr) rejection 5.1
Add shower shape can drop energy
threshold
L3EM(1,12,emfr,shape) rejection 4.2
Leslie Groer
Columbia University
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L3EM(1,15)
L3EM(1,12,shape)
L3EM(2,10)
DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Reconstructed EM profiles
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DØ Run 2 Preliminary
Energy Fractions
 pT>20 GeV from EM_HI trigger
— QCD MC
EM1
Energy Fractions
 good EM candidates that
reconstruct to Z mass
— Zee MC
EM1
EM2
EM2
EM3
EM4
EM4
EM3
Efficiency from 2nd e in Zee sample
(pT>20GeV, with track match)
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HMx9 < 100 : 94%
HMx9 < 25 : 82%
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Leslie Groer
Columbia University
Efficiency vs. 
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Energy Scale from Z ee
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 Compare data and Zee MC Mass
distributions to get absolute energy
scale
 Use standard EM selection with
geometrical corrections (phi
cracks, eta dependence etc)
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CC+EC
 2 EM objects, ET > 20 GeV
isolation < 0.1
0.95 < EM fraction
HMx8 < 100
 Paramaterize Etrue = E(1 + )
 Fit for Z mass with Breit-Wigner
and find  which maximizes a
likelihood
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Leslie Groer
Columbia University
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Not applied phi-intercalibration, pulser
corrections etc. so calculate energy
correction for each cryostat region to
restore Z-peak to its expected value
 Gives correction < few %
Work underway to add tracking
information, calibration for individual
cryostat quadrants
DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Check Energy Scale with W e
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 em objects
 with track match
 el-id criteria
EM cluster
with SMT track
Search for cluster-global track match in EM sample (scale corrected)
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EM Object
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ET>25 GeV in || < 0.8
-0.05 < isolation < 0.1
0.95 < emf < 1.05
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HM8<50, HM41<200
MET > 25 GeV
Global tracks
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10 < Nhits < 16
pT > 5 GeV
Track to EM cluster match
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 < 0.05,  < 0.2
W selection
Fit the electron p spectrum
E/p ~ 1
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Leslie Groer
Columbia University
20
DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
Summary
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 Tevatron Run 2 well underway
 DØ detector performing extremely well but many new systems coming online
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Complete readout and integration of tracking and preshowers
L1: extend coverage in eta; track triggers
L2: calorimeter and track triggers
New EM/jet algorithms (e.g. did not discuss identification of softer electrons in
jets, especially useful for semileptonic b-decays – use road method)
 Expect rich physics program from large statistics for high pT events
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Improve knowledge of QCD, proton structure functions
Measurements of heavy flavor and Electroweak physics
Searches for new phenomena, quark compositeness, extra dimensions, W’, Z’…
The elusive Higgs boson
 D0 detector poised to take full advantage of the higher instantaneous and
integrated luminosities
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Leslie Groer
Columbia University
21
DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002
EM geometric corrections and
resolution
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 EM Geometric Correction
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Energy corrections for
geometric effects
(e.g. phi cracks, eta
dependence due to dead
material in front of
calorimeters)
Single electron MC
Eta correction
factor
5 GeV electrons
EM resolution
s ( E ) / E  (0.23  0.10) E 1 / 2
sampling
 (0.202  0.006) E 1
noise
 (0.004  0.002)
constant
 EM Resolution
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Single electron MC
Calorimeter info only (no
preshower)
Correcting for phi cracks
and eta correction Calculate
 from cluster position in
EM3
Leslie Groer
Columbia University
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E (GeV)
Eta correction factor
E (GeV)
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DPF 2002, Colonial Williamsburg, VA
Jet and Electron Identification in the Run 2 DØ Detector
May 25, 2002