Electron/Photon group overview
US CMS Meeting, Princeton
April 30, 2004
Rick Wilkinson, Caltech
USCMS in e/gamma
• UCSD: Higgs  gg
– Jim Branson, Satyaki Bhattacharya, James Letts, Kyle Armour
• Caltech: Higgs  gg, h  gg calibration
– Harvey Newman, Sergey Shevchenko, Vladimir Litvin, Tony Lee
• Caltech: Calorimetry core software
– Vladimir Litvin, Rick Wilkinson
• Yale: Calorimetry core software
– Homer Neal
• Minnesota: Simulation
– Maria Obertino
• UC Riverside: e/gamma software, calibration
– David Futyan
Higgs  gg (Caltech)
• Traditional, cuts-based counting experiment
• Background simulation uses generator-level preselection
– Look for g, p0, e, h, h’, r, w
– Saves factor of ~3000 in CPU for QCD background
• Resulting luminosity required 5s discovery:
– Inclusive Higgs production (pp  H  gg)
39.2 fb-1
• Also look for Vector Boson Fusion
– pp  qqH  qqgg
– Has two forward jets with |h| ~ 3
– Surprisingly good discovery reach, 41 fb-1
Higgs  gg (UCSD)
• More aggressive; avoid cuts. Keep all the information you can.
• Sort events by their cleanliness, using
– Photon quality (narrowness of the worst one)
– Kinematics, using a neural net
– Even use the lineshape of the Higgs mass hypothesis!
• Combine all these factors into a S/B estimate for the event
• Plot the event by its S/B
• Results are amazingly good!
– 5s discovery only needs:
• 2 fb-1 for jet-jet bg
• 2 fb-1 for g-jet bg
• 0.5 fb-1 for gg bg
– Need to combine somehow
– Too good?
background
signal
log(s/b)
H  gg photon quality
• Categorize events by the quality of
their worst photon.
• r9 = (Sum of 9)/ESC (uncorrected)
– 4 bins in narrowness r9
x2 bins (barrel, endcap)
makes 8 categories of events
• Better photons have
– better mass resolution
– Less QCD background
• Analyze event categories
separately
– Only combine in final plot
signal
unconverted
background
H  gg Kinematics Neural Net
• Neural Net Inputs are:
– Jet-jet and g-jet
• Calo isolation, track isolation,
ET1/(ET1+ET2), ET2, |h1-h2|
– Irreducible background
• ET1, ET2, ESC1, ESC2, |h1-h2|
• S/B obtained from the black fitted
curves
γ-jet cat1 (cleanest)
background
signal
H  gg Mass shape & discovery reach
• Include mass information in s/b
• Fit resulting plot for signal,
background
background
signal
• Do many trials:
– background-only experiments
– signal+background.
• Some overlap
– Luck will play a role in how
fast we find the Higgs
log(s/b)
Calibration
• Baseline: Track momenta from electrons from W decay
– Problem: Can we avoid strict cuts on brem?
– May take months
• Other, faster techniques
– h  gg (V. Litvin & S. Shevchenko, Caltech)
• Photons usually separated by 3-10 crystals
• Needs a day or two of dedicated running with the full DAQ bandwidth!
– Combine f-symmetry + Z  ee
• See next slide
Calibration
• Start by looking at f-symmetry, comparing summed
energy in crystals around a ring in h (D. Futyan, UCR)
SET vs f:
– In min-bias events
• Too low energy?
• Sensitive to tracker material
– In jet triggers
• Trigger biases
– trigger region boundaries!
All rings combined
• Then, calibrate between the rings with Z  ee (Rome)
– 170 parameters in barrel, 80 in endcap
– Math. Lots of math. (Iterative algorithm now, others possible)
Calorimetry Software
• Skeleton transplant in progress!
– Switching to common framework with Tracker, Muon
– Allows us gain functionality they already have:
• Track propagation
• DAQ readout grouping
• Misalignment
• To-do list:
– Calibration constants
– Analyze HCAL testbeam data with ORCA
e/gamma code: Physics Objects
Persistent Physics Objects in DST data for Data Challenge ’04 datasets:
(D. Futyan, E. Meschi)
• EGBCluster (basic cluster)
• ET threshold gives EGCluster
• Brem recovery gives EGSCluster (supercluster)
• Endcap preshower gives EGECluster
• Fiducial cuts give EgammaCandidates
– Offline
• EgCandFromEGSCluster
• EgCandFromEGECluster
– Level 2 trigger
• EgCandL2FromEGSCluster
• EgCandL2FromEGECluster
• If there’s an associated pixel track: EGElectron
• If no associated pixel track, EGPhoton
• Also EPTrack, EgammaMC
GEANT4/OSCAR Validation
• Long-running mystery about the
electron energy resolution.
• There was a bug in the simulation
thresholds used in the material
description. Tracker cooling
ledges were opaque to their own
brem. (M. Obertino)
Why this difference
in the energy
distribution ?
OSCAR
CMSIM
Emeas/Etrue
Electrons: Resolution vs. h
• ECAL Barrel resolution gets
worse with h. (Takahashi, ICL)
Doesn’t seem to be because of
lateral shower spread.
• Maybe back or front leakage?
<2nd sub-module>
<16th sub-module>
back leakage
~26 radn.
lengths
<<26 radn.
lengths
front leakage
High Energy Electrons
•
•
•
•
For Randall-Sundrum graviton studies (Collard, Lemaire)
Need to re-optimize clustering algorithms & corrections
Synchrotron radiation not a problem
ADC saturation is a problem, but can be corrected