A Study of Electron Identification Jim Branson UCSD with collaborators from FNAL, UCSB & UCSD

2 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.

3 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?)

4 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.

5 E/p often Affected by p Measurement E/p Z  ee

6 Remove Some Producer Cuts 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 Some producer cuts are too tight. This increases the denominator for selection efficiency calculations and therefore decreases the efficiency calculated. **See talk of Matteo Sani

7 Apply Simple Cuts on Five Variables   < cut  in < cut 3.E seed /P out > cut *can we replace this?  in < cut 5.H/E < cut With straight cuts on these quantities, we get 97.3% selection efficiency and 4.1% of dijet(50-80) events having a fake electron.

8 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.

9 Use this 2D Plot to Study e ID Electrons from Z  ee Fakes from jets E/p fbrem

10 Color the Picture Electrons from Z  ee Fakes from jets Electrons and jets overlap (Pyrite). Mainly GOOD electrons Mainly fakes We call a color in this picture a category. Are there selection differences beween the categories?

11 What is the Physics Behind Electrons from Z  ee 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 fbrem E/p

12 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

13 Why Categories? 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. ElectronsJetsfakes

14 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…

15 Apply simple cuts in each category   < cut  in < cut 3.E seed /P out > cut  in < cut 5.H/E < cut Look in Seven categories (for STUDY). Look at barrel and endcap separately. No Isolation Cuts Applied

16 Selection Cuts E/p  Fbrem   Eseed/Pout H/E  All electrons Surviving electrons ET<15 electrons failing cuts All fake candidates Surviving fakes

17 Base Categories on This Plot E/p Fbrem=(P in -P out )/P in

18   in Categories Electrons Jets “n-1” plots Looser cuts in best category

19  in Categories Electrons Jets Basically, we tighten the cut until it starts to cut more than a few electrons “n-1” plots Tighter cuts in overlap category

20  in Categories Electrons Jets “n-1” plots Looser  cut for worst E/p category

21 E seed /P out in Categories Electrons Jets “n-1” plots

22 H/E in Categories Electrons Jets “n-1” plots

23 The Cuts: 22 values Cat N cut   <   E/P out > H/E   <   E/P out > H/E< Use looser cuts for the best electrons. Critical overlap Category with E/p=1 Barrel Endcap  bad if E/p bad For selection, we really only need 3-4 categories.

24 Why 22 Cut Parameters BarrelEndcapSum 5 Cut-Variables 5510 Looser Cuts on best electrons Claim looser cuts on best electrons make us less sensitive at startup! 437 Different Cuts in overlap region and high E/p overlap 314 Open  cut for worst E/p 101 Total

25 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)

26 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)

27 Nota Bene The 3 Categories can just be used for the selection. There is no reason we need to use them for later analysis.

28 Results on Standard Electron Reco ET SC >5 -2.5<  <2.5 THIS Selection 22 param. THIS Just 5 cuts, Not tuned Standard Selection Crack  Gold 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) *Not fair: All crack electrons are accepted in the standard selection. ** Coded by us for comparison under same conditions.  highly preliminary. No Isolation Cuts Applied

29 Efficiency Reco Eff. Reco*Sel. Eff. (THIS) Reco*Sel. Eff. ootb All use same standard reco. Crack electrons treated as golden for ootb selec.  ET

30 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.

31 Accepted Crack Electrons: SC OK  E SC /E All electrons Crack electrons

32 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.

33 More Cuts? No. Isolation

34 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.

06/08/ EGamma POG meeting 35 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 ”. From Matteo Sani GGE See also talk in Higgs meeting by Boris Mangano.

06/08/ EGamma POG meeting 36 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 reconstructs electron but GGE fails. From Matteo Sani

37 Preliminary e-ID Performance On GGE reco sequence ET SC >5 -2.5<  <2.5 THIS Selection Standard Selection Crack  Gold Selection Efficiency for e from Z  ee 96.8%90.7% Fakes per dijet event QCD_50_80 1.2% (0.6% per jet) 5.6% (2.8% per jet) This reco is new and a rapidly moving target. Results are therefore very preliminary.

38 A Look at Tighter e-ID -2.5<  <2.5 PT MC >5 Selection Efficiency for e from Z  ee Fakes per dijet event QCD_50_80 ET SC >5 Fakes per dijet event QCD_50_80 ET SC >10 Loose Selection 5 cut params. TkIso<7 96.9% 3.1% 1.5% 2.2% 0.99% Loose Selection (6 cat  60 param.) TkIso<7 97.2% 97.4% 1.3% 0.60% 0.95% 0.42% Loose Selection (22 cut param.) TkIso<7 96.8% 96.6% 1.2% % 0.40% Tight Selection TkIso<7 94.1% 94.4% 0.53% 0.22% 0.40% 0.16%

39 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