Missing Et at CMS review, status, discussion, plan

1. Missing Et at CMSreview, status, discussion, plan Haifeng Pi, University of Florida USCMS/CDF/D0 Workshop 1/28/2004 1

2. OUTLINE • Review (only highlight several major milestones) • Trigger Study at High/Low Luminosity • Tracking for Missing Et • Jet and Min.Bias Scale for MET • Energy Flow in Calorimetry • Missing Et Resolution • MET Normalization • Pileup Subtraction • Latest Result (led by Jim and Chris) • Understand the Resolution of MET • Eta Coverage of Detector • Very Low Pt Hadrons • Low Pt track in 4T magnetic filed • MinBias Event • Electronic Noise • Stochastic Term in Response • Pileup Effect in Low/High luminosity • Jet Reconstruction for MET • Lepton and Photon in MET and Jet • Detector Resolution Quantities for MET • Muon Correction for MET • MET Reconstruction and Analysis subsystem in ORCA • Plan and Discussion 2

3. REVIEW : CMS Trigger Study for MET MET Reconstruction and Selection in DAQ TDR (11/2002) 1. Vector sum of Et in Ecal and Hcal towers with Et threshold > 0.5 GeV and angle from z=0 2. Energy Scale Correction : type 1: jet energy correction with Et > 30GeV, no correction for un-clustered towers type 2: jet energy correction with Et > 30GeV, correction for 30GeV for un-clustered No Correction algorithm founded as good as performance as correction algorithm 3. Remove abnormal events (large energy deposit in a single readout) 4. Topological cuts (opening angle): back-to-back jets veto for 1st and 2nd highest Et jets MET and leading jet MET and 2nd leading jet 1st and 2nd jet MET and sum of 2nd & 3rd jets 3

4. REVIEW: Tracking for MET (Dan Green’s Talk) Combination of tracker and calorimeter (1) identify energy deposits from extra vertices and subtract it from the calorimeter deposit (2) the measurement of energy with good resolution from tracker can be used to replace matched energy deposits in calorimeter Major Techniques (1) Track reconstruction (2) Track-Cluster matching (3) Energy Subtraction (4) Particle Identification (particle response library in calorimeter) (5) lepton/Photon Identification The scheme was used later in Jet reconstruction and got big success 4

5. REVIEW: Minbias Event for MET (Dan Green’s Talk) The transverse energy in a beam bunch crossing induced by truncation of the angular coverage and by calorimetric energy resolution has been studied. For low LHC luminosity, with 1 event per crossing there is ~ 5 GeV transverse energy on average, with a 1% chance to exceed a threshold of 12 GeV for the crossing. The mean Et increases as the square root of n, with a constant r.m.s./mean. At a luminosity with 20 events/crossing, there is a 1% chance per crossing to pass a missing Et cut of 40 GeV. The effect of placing cuts on the entries put into the Et global sum was studied. An angular restriction of |y| < 3 and 2 was compared to the basic |y| < 5 cut. Assuming that poorly measured particles were at fault, a cut of E > 10 and 20 GeV was also made on single pions. Assuming that low Pt entries were fluctuating, a cut of Pt > 1.0 and 2.0 GeV on single particles was studied. None of these cuts made any significant improvement in the Et distribution of a crossing in the case of 20 events per crossing. The distribution seems to be almost “holographic”; no matter how it is cut the same distribution, mean and r.m.s. is obtained. 5

6. REVIEW: Energy Flow (Dan Green’s Paper) Eta Match “Energy Flow in CMS Calorimetry ” (2001) Transverse Shape in Ecal Calorimeter Clusters Tracker-Cluster Matches Jet Properties Di-Jet Mass Azimuthal Angle Match Using an assumed calorimetric resolution with a stochastic term of 60% and a constant term of 3% , the contribution of the energy error to the mass resolution was ~ 7.2 %. The contributions due to fragmentation and the underlying event depend on the cone size. For R = 0.6 the fragmentation error is 5.5 %, while the underlying event contributes 9.4 %. At a larger cone size, R = 1.0, the fragmentation outside the cone has a reduced 3.6 % contribution, while the fluctuations on the underlying event within the cone rise to 13.8%. Energy Match The severity of the effect of radiation prompted a more complete study. This study has been made of the effects of initial state and final state radiation on the dijet mass resolution for Z bosons. For a cone size of R = 0.7 the fractional mass error was 11% without radiation, rising to 19 % with radiation turned on. Unfolding in quadrature, radiation appears to contribute 15% to the mass error by itself. Note that in this study a toy detector was used. Correlation of dijet from cluster and cluster-track 6

7. REVIEW: MET Resolution(DAQ TDR & Dan Green’s talk) dEt ~ aEtsin dEt ~ Etcosd 7

8. REVIEW: MET Normalization & Pileup Subtraction MET rate Invisible Higgs Above MET of about 80 GeV, the bins below 80-120 GeV are negligible Pileup yield 500-1000 GeV Et sum @ high lumi. With pileup substraction, L1/2 rate are expected to be lower 8

9. MET Reconstruction for Physics Analysis Offline Reconstruction for MET is becoming more and more important 1. Concentrate on more channels other than QCD Di-jets, such as TTbar, W+jets, Z+jets. (The origin of MET in QCD Di-jets is very different from other processes) 2. Trigger efficiency study of those channels under the current CMS DAQ 3. Improving MET resolution quantities 4. Reconstruction of Semi-leptonic decayed W boson for Top, Higgs 5. Combination of MET spectrum and other quantities (Di-jets mass, Di-lepton, leading Jet, leading Lepton) TTbar for MET offline reconstruction and analysis Three major aspects summation of Calorimetry hits OR Jets reconstruction and Energy Scale Lepton Identification Pileup subtraction ( might be done in Jet energy correct if MET is reconstructed from jets) Detector Analysis Eta Coverage of Detector Very Low Pt Hadrons Low Pt track in 4T magnetic field MinBias Event Electronic Noise Pileup Effect in Low/High luminosity Jet Reconstruction for MET Lepton and Photon in MET and Jet Detector Resolution Quantities for MET Muon Correction for MET Other channels for MET analysis in the row WBF Higgs, W+jets, Z+jets, Invisible Higgs, SUSY 9

10. Detector Eta Coverage on MET (1) Linear depend between Eta Error ( Et Resolution) and detector Eta coverage (2) A limit of intricacy 7-10% of MET resolution introduced before the events interacting with the detector because of the limited eta coverage 10

11. Detector Eta Coverage on MET (cont.) (1) Current MET trigger is very inefficient for TTbar events (2) 4-5% sum of Et is lost because of limited Eta coverage (3) As eta coverage smaller, the sum Et resolution become much wider, indicates a bigger fluctuation in Energy Flow. 11

12. Effects of Very Low Pt Hadrons • A linear relationship between Phi Error (MET Resolution) and Pt with Cut Pt Threshold Cut from 0.4 to 2.7GeV. It shows the fluctuation in Energy low is very small in the very Low Pt Hadrons • Does this character indicate a less-sensitive of Calorimeter Pt Threshold cut while building towers, clusters and jets ? • Or a more aggressive pileup subtraction? 12

13. Effects of Very Low Pt Hadrons (cont.) We see very little change in Sum of Et resolution, but its value (sum of Et) decreases by 20-25%. Noticing the resolution with 0.5GeV hadron threshold is 7.5%, which is integrated with that of Eta coverage. So we can estimate the standalone resolution coming from low Pt hadron threshold is roughly 5%. Comparing to that from limited detector Eta coverage ( 4-5% of change in sum of Et cause 7% resolution), we need to understand the physics origin of these phenomenon. It is necessary to check with other channels, QCD di-jets events should show very different behavior. 13

14. Effects of Low Pt Charges Particles Motive: The understanding of Low Pt Charged particles on MET resolution is extremely important. Low Pt charged tracks are highly deviated due to 4T field in CMS This analysis mainly estimate the limits of its influence on MET. Which will provide a very important threshold on the correction of Low Pt tracks The limit of low pt tracks can also help determine the calorimeter tower threshold for pileup subtraction. 14

15. Minimum Bias Pileup Event Study Motive: 1. Evaluate the fraction of MET originating from pileup Minimum Bias event 2. Since its contribution for MET is independent on Signal, so its relative contribution should be smaller for high MET. But its real influence is on jet energy scale. An over-corrected jet might worsen the MET resolution. 3. Pileup contribute dramatic amount of transverse energy to Calorimeter. Does MinBias pileup events change the signal MET topology? where is the low-bound of the MET resolution at 30% under Low/High Luminosity. High Lumi Low Lumi 15

16. Minimum Bias Pileup Event Study (cont.) Minbias Event TTbar Event Minimum Bias Transverse Energy Distribution Ttbar Transverse Energy Distribution TTbar Et is more centrally deposit than Minimum Bias. Under Low (High) luminosity, pileup Minimum bias events cause average 2-4 GeV(8-9 GeV) MET Total Transverse Energy for pileup events is average 100-300 GeV (1000-1500 GeV) An absolute 8-10 % (15-25%) contribution of 40GeV MET resolution from Pileup. This calculation is based on total energy without an energy cut on particle Et. The threshold of Calorimeter tower might change the MET spectrum of Minimum Bias event. 16

17. Effects of Electronic Noise This analysis concentrates on the overall effects of Electronic Noise and on MET Resolution. The Calorimeter Electronic results in an absolute 12% contribution to the MET resolution. Without Muon correction, the value decrease to 9%. No improvement in the angular distribution (Phi error). From Non-Pileup sample, we can also derive the overall effects of Calorimeter Resolution on that of MET, assuming an absolute 15% of particle level MET resolution. The Calorimeter (detector level) have an absolute 20% contribution to the MET resolution. No apparent different in Phi error between particle level and Calorimeter. (very good!) 17

18. Stochastic Variance in Calorimeter Response Through samples with non electronic noise and non-pileup, comparing to particle level MET, we can have a coarse estimation of how calorimeter stochastic term contribute to MET resolution. Calculation is based on: The stochastic term in Calorimeter response contribute to MET (40GeV above) an absolute 15%. This contribution is related to the sum of transverse energy in Calorimeter in theory. But the dependence is not so obvious, because pileup sample will deposit much more energy than the signal, while does not hurt the resolution at the same ratio. Further analysis based on binned MET samples and binned Sum of Et sample will answer this question. In order to make this analysis feasible, an accurate particle level MET simulation is necessary, particularly taking into consideration of Low Pt particles, Magnetic filed on charged particles) 18

19. Pileup under Low Luminosity A standalone effects of pileup on the variation of MET resolution can be estimated from non-Pileup samples and pileup samples. With Muon correction absolute 16.7% variation in MET, without muon correction, 12.4% variation in MET. In general, a standalone 12%-16% variation of MET is caused by pileup in Low luminosity case, which is bigger than expected (10%). The Phi error become worse from 0.12 to 0.14 (Muon correction can slightly improve angular resolution) The pileup will deposit a lot of energy in Calorimeter, so the stochastic variance in detector response will result in a big effect comparing to non-pile samples. In current analysis, this effects is in the pileup “noise”. But we should note, this “noise” has two very different origin: minimum bias event itself and its energy deposit on Calorimeter. 19

20. Pileup under High Luminosity With Muon correction, we see an absolute 21.1% variation in MET ( without muon correction 19.6%). In general, a standalone 20% variation of MET is caused by pileup in High luminosity case, which is as expected (15-25%) comparing to non-pileup MET resolution. The Phi error become worse from 0.12 to 0.14 (Muon correction can slightly improve angular resolution) The discussion on pileup noise applies to high luminosity too, and the two origin of pileup noise behave very different. If the stochastic term play a important role, the high pileup case show be much “un-predicated”, since current estimation is primarily based on the particle level MET from minimum bias events. The stochastic dependence is missing (or being suppressed) for those pileup minimum bias events!?? 20

21. Sum of Et Distribution in Different Samples High Luminosity Pileup events deposit more transverse energy than signal events. But its overall geometric Et distribution in eta-phi gird is very balanced. So it does not introduce much deviation of the signal MET. The large amount of Et from pileup events cause much difficulty to the study on sensitivity of MET to the detector intricacy resolution. This facts indicates the difficulty to improve the current linear weighting for CaloRecHit between Ecal and Hcal. This facts also indicates analysis favors a simple strategy of pileup effects subtraction. But a linear weighting and linear subtraction won’t improve MET resolution in general. Low Luminosity With Noise No Noise Particle Et 21

22. MET Resolution Variables (based on Chris’s DC04 plan) • General MET quantities • Px, Py ( Pt & Phi) • Sum of Et, Sum of Et in Hcal/Ecal • Sum of Et measured in Tracker • Reconstruction Algorithm: • From Calorimeter Hits • From Jets ( Iterative Cone, Kt ; Et Scheme, E Scheme) • Lepton Photon Reconstruction • Correction Methods: • Pileup Subtraction (Threshold of Calorimeter Tower) • Jet Energy Correction • Un-clustered Calorimeter Tower Correction • Charged Track Correction • Still looking for good parameters to identify the MET resolution from different eta region • Using Sum of Et, local MET seems not work well in current analysis because pileup events deposit much transverse energy • Some other quantities that will potentially help MET resolution • Weighting of Calorimeter hits. Non-linear response for low pt hadrons • Calibration of Jets • Calibration of Minbias Event • Trigger Quantities • Can MET-Lepton trigger possible in CMS ? • Improve trigger efficiency for some important channels 22

23. Photon and Lepton in MET and Jet • 3750 muons and 3700 electrons found in 84875 jets • about 9% of jets have 1 lepton • Muon Pt correction is non-trivial for jet energy correction • Only lepton seems not enough to explain the large fluctuation of Energy ratio between Ecal and Hcal in jets ( because of photons ?) • A further detector level analysis of Ecal energy deposition of hadrons in Jets will provide the direct answer and possible solution for reconstruction electron in jet 23

24. Photon and Lepton in MET and Jet (cont.) • Most of photons are low Pt • Effects of photon radiation of charged particle and photon conversion might be the resources of the puzzle. • How efficient of PreShower and Tracker for phone veto ( identification ) in jet ? 24

25. Lepton/Photon Correction for MET • Muon Correction • Muon Correction for MET has been proved useful and effective in TTbar ( no doubt about WBF higgs, W+jets … ) • In general (Low/High luminosity), 3-5% improvement in resolution for 40GeV and above MET can be achieved. • In the study of calorimeter without electronic noise and pileup, effects of muon correction is more prominent. This does not necessarily mean the reduction of Muon correction in pileup and electronic. • Electron Correction • Electron Correction means identify the electron tracks from track and electron super-cluster in Ecal • Subtract corresponding electron energy (measured by Tracker) from Ecal • Help Jet energy correction • Photon Correction • Photon Reconstruction solely from super-cluster in Ecal and non tracks in tracker • Help Jet energy correction 25

26. Jet Reconstruction for MET • R • Charged hadrons are our major concern • Track can help improve the resolution of Low Pt (10-20GeV) charged hadron tracks • Observing a roughly 3 GeV cut on hadron Pt, need to understand the origin of it. Which provide a reference point for charged Hadron’s lowest Pt reconstruction. 26

27. Jet Reconstruction for MET (cont.) • T • Also observing a 3GeV Pt cut on neutral Hadron pt distribution • The neutral and charged energy are comparable. Does this set a limits of Jet resolution because neutral hadron completely depends on Hcal. 27

28. Understand the Overall MET Resolution • Summary of the table about MET Resolution (based on TTbar channels, 40+GeV MET) • Eta Coverage effect 7-10% • Low Pt Hadron effect 5% • Low Pt Charged Particle in Magnetic Field 10% • Minimum Bias Event in particle level 10-15% • Calorimeter Electronic Noise 10-12% • Stochastic Term in detector Response 15% • Low Luminosity Pileup Noise 13% • High Luminosity Pileup Noise 20% • Further analysis will give more accurate results of above number • Binned MET sample • Binned Sum of Et sample • Binned Sum of E sample • Pileup, non-pileup, non-noise samples • Strategy of improving MET resolution • Tracking for MET (decrease low pt charged particle effects and detector stochastic response) • Pileup subtraction (decrease minimum bias pileup effects and low pt hadron effects) • Physics channels dependent MET reconstruction 28

29. Developing MET Subsystem in ORCA • In current goal of MET reconstruction, it should be very analysis-oriented with the flexibility to integrate various quantities. • The MET reconstruction scenario are mainly organized in several levels. The hierarchy only reflected the dependency of reconstruction objects, not the algorithm and methods. In each level, a MET object and other relevant target objects can be reconstructed and output for analysis. • Major strategy for this organization of code is: constructing a vertical analysis chain for MET reconstruction; the higher the level, the more parameters for user to optimize; lower level objects are transparent to high level analysis, but its methods can be re-used for higher level objects (especially useful for calibration analysis). • 6 levels of hierarchy. From calorimeter MET to global energy flow MET • Aligned with the comprehensive architecture of JetMet analysis, MET should be able to reconstruct various quantities and provide a number of relevant methods. Some examples of typical MET analysis topics: • how Calorimeter noise affect MET • how QCD 2 jets energy scale affect MET resolution • which scenario, jet-based MET reconstruction or Cluster-based MET reconstruction, has better resolution in a specific event topology for a certain range of scalar sum of Pt • what criterion for isolating high pt leptons for MET reconstruction for a physics channel • how forward jet tagging influences MET reconstruction • how sensitive of various jet reconstruction algorithm on MET • How to combine tracks with calorimeter clusters for energy correction of Calorimeter towers or jets 29

30. Issues and Plan Trigger Study Several MET activities in a short term 1. MET online trigger and calibration 2. QCD Di-jet MET trigger analysis (in DC04, there is a bigger QCD di-jet samples) 3. Generator level QCD Di-jet reconstruction and selection (up to 100 milion events) 4. Redo this analysis in DC04 data (finalize those MET quantities) 5. Develop Energy Flow algorithm with global correction of low Pt Tracks 6. MET related event production 7. MET pre-selection in CMKIN generation 8. MET reconstruction with other topology, such as “central Lepton” + “forward jets” 9. Optimization of weighting of CaloRecHit 10. Comparison study between QCD di-jets and TTbar 11. MET-dedicated Jet energy scale 12. Primitive study on Vertex Constraint of MET reconstruction 13. WBF Higgs MET analysis 14. W/Z + jets MET analysis 15. W reconstruction MET Reconstruction Technique MET Selection 30