Towards Physics in Tevatron Run II

1. P. Grannis Manchester Oct. 24, 2001 Towards Physics in Tevatron Run II (some items for discussion) Once the DØ detector, trigger commissioning & offline reconstruction of physics objects are complete – there will still be much to do to optimize the physics analyses. This talk is intended to stimulate discussion and draws on some lessons from Run I. It is aimed at identifying some of the areas where work is needed for Electroweak studies and Searches – probably unimpeded by knowledge on my part of details of recent work in the Physics Groups. Top quark Vector Bosons Higgs Supersymmetry • Some issues to be considered for optimizing Run II analyses – flagged throughout the talk

2. ET ET Top quark measurements tt production: 90% qq annihilation and 10% gg fusion. q g t t g g t t q g • Top BR’s (SM): t → W b (100%) • with W → qq (67%) • → en , mn, tn(11% each) • So final states of tt ( lepton= e or m): • Dileptonbbl lnn= 2 b jets, 2 leptons,(low bknd, small signal)(BR = 5%) • Lepton+jets bbqq’ln = 2b, 2q jets, lepton,(moderate bknd & signal)(BR = 30%) • All jets bbqq’q’’q’’’ = 2 b, 4 q jets(huge QCD bknd, 106 x signal)(BR = 45%) • Taus+jets tnbbqq/tnlnbb(large bknd, t ID issues)(BR = 20%) In all cases, there is an additional hadronic system X formed from gluon radiation, and the spectator partons usually recoiling at small angles from the tt. 2

3. In Run I, top mass was extracted from l + jets, • l l + 2 b-jets (and internally, all jets). • In most cases, the method is to • Choose a kinematic distribution that varies as mt changes; • Monte Carlo set of templates with various top masses, and the backgrounds included; • Likelihood fit for best Mt. • (Many choices of kinematic distribution.) • Illustration for l + jets: Use distribution of fitted top mass. Have 6 final state objects; thus in zero mass approximation, 18 kinematic quantities needed. Measure 3-momentum of 4 jets and one lepton; 2 components of ET. Constraints from equal t and t masses, and (qq), (ln) must have W mass, so have 20 known quantities → 2C fit. • BUT: Did not in general identify the b-jets (only for b→mX in Run I), so have 12 ways to assign the jets to partons (6 if there is a b-tag). Top quark mass Initial state radiation can give extra jets – this should be absorbed into the state X. Final state radiation from top or jets – these should be combined with the parent jet. true mass METHOD: Perform a 2C fit for all associations of the 4 leading jets to the tt hypothesis; choose the smallest c2 solution. Call the best fit mass the fitted mass. Do the same for (Herwig) MC events with a family of known true top mass and get template distributions of fitted mass for each true mass. fitted mass 3

4. Select l, n, jets with high ET (> ~ 20 GeV) • Form topological variables for signal/bknd discrimination: • : missing transverse energy • HT = SET(jets 2 to N): scalar transverse energy for non-leading jets. Large for top events due to large parent top mass, small for dijets. • A (aplanarity) : smallest eigenvalue of momentum tensor large for top events as the top quarks tend to give isotropic decays; QCD jet backgrounds have parent 2-jet topology • Dr : minimum jet angular separation Lepton + jets analysis Example: HT distribution ET data background signal Construct a measure Dfrom variables that indicates the relative probability for event to be top vs. background [two variants – weighting technique for low mass bias (DLB) and Neural Network (DNN)]. Use this Dto make a cut, or as a weight for final event selection. (b) (a) DNN Obs. mass vs. DNN for (a) signal, (b) background;(c) data (c) fitted mass 4

5. Top mass in lepton + jets channel ( lepton = e or m ) Backgrounds: ~ 2/3 of bknd from W+4 jets. Use parton generator VECBOS with HERWIG/ISAJET fragmentation to calculate. Check with W+1, W+2, W+3 jet data and Behrends scaling : [W+(n+1)jet/W+n jet] = a ~ 1/3 of bknd is from multijets, with a jet faking lepton, and mismeasurements giving ET . Determine from data with ‘bad’ leptons. Bknd (low D) sample Best fits: 171.3 6.0 GeV (neural net analysis) 174.0 5.6 GeV (weight analysis) (statistical errors) Combined final DØ result for lepton plus jets: Mt = 173.3 5.6 5.5 GeV Mfit Mtrue Signal (high D) sample Mfit 5

6. Dilepton channel analysis For the dilepton channel, there are two missing neutrinos, so the fit is underconstrained by one. DØ employed two methods: Neutrino weighting (nWT) and matrix element weighting (MWT). For nWT, we assign a weight based on how much of the nn phase space for signal is consistent with the event kinematics, computed for a set of Mt values. For MWT, compute a weight based on the probability to have the lepton energies as observed, and the product of PDFs required, for a set of Mt values. After smearing many times with the known resolution functions, and summing over combinations, each event has a weight distribution as a function of Mt : For the MWT analysis, weight distributions for the 6 observed events The weight distributions for all events are averaged, and compared to MC templates for a known input top mass. A best likelihood fit gives the top mass. Distribution of weight averages for 160 and 180 GeV MC samples, each with 6 events 6

7. Dilepton analysis results nWT Analysis Averaged dilepton mass Mt = 168.4 12.3 3.6 GeV (lower systematic error than l + jets) MWT Analysis DØ Lepton + jets and dilepton top mass combined: Mt = 172.1 7.1 GeV Tevatron average: Mt = 174.3 5.1 GeV Other Run I methods: 1. For l + jet evts, assume set of Mt’s and do 3C fit at each. Form pseudolikelihoodL= e-c2(fit)/2 ; Fit L for maximum. Get: Mt = 176.0 7.9 4.8 GeV 2. Fit pT(b), pT(lepton), HT (= sum of object ET’s) etc. These have lower statistical precision due to less dependence on Mt. 3. Use tt production matrix elements in forming weights (looks promising) 7

8. Top mass in Run 2 • It will certainly be a different optimization: • With x20 data (Run 2a), or x200 (Run 2b), statistical errors get small; thus systematics become more important. • Much improved b-tagging (SVX) mean fewer combinatorics (though b vs. b is hard!), and much improved Signal/Bknd (e.g. double tagging) • Many more overlaid minimum bias events at high L . • Large improvement in MC capability (GRID farms around the world) Look at the Run I systematic errors breakdown: Systematic errors dileptons Jet energy scale 2.4 GeV Signal generator 1.8 Bknd model 1.1 Multiple Int’ns 1.3 MC statistics 0.3 Likelihood fit 1.1 (Tot. syst. 3.6 ) (Stat. 12.3 ) Systematic errors l + jets jet energy scale 4.0 GeV signal generator 1.9 bknd generator 2.5 multiple int’ns 1.3 MC stats 0.9 likelihood fit 1.0 method diff. 0.8 (Tot. syst. 5.5 ) (Stat. 5.6 ) How do we improve these? 8

9. Jet energy scale (dominant error for l + jets). Error = 2.5% + 0.5 GeV obtained from ET balance in g + jets events, taken from difference in balance for data and MC. Check by ET balance in Z(ee)+jets events. Jet scale error • Jet scale error statistically limited in Run I, but there are systematic issues that will arise: • jet widths • min bias contributions to jet scale • MC correction closure • b-jet corrections (= light quarks) • out of cone partons … • Are there alternatives that minimize the jet scale error? • Is the dilepton channel better than l + jets? (only 2 jets, so reduced jet scale effect) • Ratio of W/top mass in tt events, then scale with accurate MW (partly cancel jet scale error?) • Use variables less sensitive to jet scale (QCD radiation-proof variables) but with larger statistical error? (e.g. pT(lepton) for both l + jet and l l ) • Can one do better with kT (JADE-like) jet definition? (force right # jets?) • Energy flow algorithm? (CFT for charged particles, CAL for neutral) • Neural net/H matrix to correct nloss from b-jets? 9

10. MC generators In Run I, HERWIG was the primary signal generator. Error is set by study of top mass variation as fn. of (x = # non b/W jets in 1st 4), (y = # jets –4), (z = # extra FSR jets). Also used FSR-suppressed HERWIG. PDF variation is negligible. VECBOS used for W+jets background. Vary Q2 scale from jet <pT>2 to MW2. Vary VECBOS to alter hW . But: HERWIG, VECBOS are not full NLO, and could have other ‘features’ • We need improved generators: • Implement new NLO top generators including interference of ISR/FSR (Orr, Stirling). These generators need interface to full fragmentation. • Extend W+jets NLO to W+4 jets? (DYRAD does W+1 jet). Add flavor accountability to VECBOS. Seek non-MC methods for W+jets (is Behrends scaling more accurate & reliable? Verify theoretically at NLO?) Likelihood fits Likelihood curves are not parabolic; error depends on # pts used, and on parametrization of L fn. • Get more rigorous definition of fitting procedure. 10

11. Other issues for top studies • Min bias event overlaps: Run I added ~0.7 MC min. bias events on top, adding to Cal. energy. For Run 2, this up to ~4-5. Good minbias MC modelling becomes crucial. Go to use of real minbias events taken at same luminosities for MC overlay (is now available, but needs work). • Top mass definition: Fitted mass (pole mass) is uncertain at level of 0.5 GeV due to non-perturbative renormalon effects. Can DØ help/test these effects ?? • Cross section: Run 1 made 30% measurement, limited by jet scale & background generator (20%). If this improves, can uses(tt) as testof NNLO gluon resummed QCD! What precision for stt? Can this become a useful and meaningful test of resummed QCD? (Note that accurate s(tt) is needed for some Higgs backgrounds.) • Mass measurements: Can use of tt matrix elements improve the constrained fit? Explore the pseudolikelihood mass measurement (lower syst. error in Run 1) 11

12. Other issues for top studies • Spin correlations: Top decays before hadronization; Run 1 made crude measurement of tt spin correlation l l direction correlations. How to make this QCD test most incisive? Get spin correlations into generators. • Top EW measurements: Single top production via W exchange are sensitive to Vtb , GTOT . Can one ‘discover’ the single top production and then refine the selection of single top to enhance the precision of these EW parameters? • FCNC and anomalous form factors: what sensitivity for t → Zc / g c to limit anomalous top couplings? • Tau decays: t BRs are sensitive to admixture of t → H b with H → tn . How much improvement on H mass limits? 12

13. W boson mass Three (correlated) variables are sensitive to the W mass: Electron pT , Missing ET (neutrino),Transverse mass = mT mT 2pT(e) pT(n) [ 1 – cos(f(e) - f(n)) ] mTis insensitive to the W production dynamics (corrections O(pTW/MW)2 ) but requires the inferred neutrino pT, hence is sensitive to detector response. pT(e)andpT(n) Jacobian edges depend on pT(W). pT(e)depends only on well measured electron kinematics; pT(n) also depends on hadronic response mTand pT(e) distributions as generated and pT(W) = 0 (solid line); correct pT(W) (red points) and after detector resolution effects (yellow shading) Method: Fast MC to include W production, decay and full detector modelling. Make templates of mT , pT(e),pT(n), for set of MW values and find best fit. MW (DØ) =80.483 0.084 GeV 10 Run 1 measurements (electron channel) 13

14. Detector response modelling The detector response functions for electrons, recoil energy, radiative photons, etc. are mostly determined from data distributions. • Electron response: Emeas = aEtrue +d taken from Z→ee and precision LEP Z mass • Electron resolution: s/E = c + s/ E + n/E taken from fit to Z lineshape • Electron directions: chamber and calorimeter position calibration from muons and Z→ee • Hadronic response: require pT balance of e+e- from Z and the hadronic recoil • Hadronic resolution: shape of pT(X) distributions along/perpendicular to Z→ee • Trigger efficiencies measured with special data sets • Energy corrections to pT(e) and UT for hadronic energy falling into electron window • Correct selection bias for UT close to pe (loss of events due to energy isolation cut) • Radiative decays (W→ eng) taken from theory and modelled in MC • Effect of extra minimum bias events underlying the W production taken from special inclusive triggers; overlay these events at the same luminosity as for signal events • Backgrounds (mainly from QCD jets misidentified as electrons at 10-4 level) taken from special data sets by selecting ‘bad’ electrons. W→tn→ ennn is included in the decay MC 14

15. The MC, with parameters determined from data, can be confronted with data to show the validity of the model. Some examples: Sample MC fits Z→ee distributions for central/end and end/end e’s showing validity of electron response, resolution and background determinations ratio of datah distribution to that of MC (an important constraint on the PDF) recoil energy along electron direction recoil transverse energy 15

16. Mass fits • The W mass is obtained by comparing MC templates with various assumed MW to the data, and performing a likelihood fit. This example shows the mT distribution fit for end electrons. • (similar fits for pT(e) and pT(n) distributions ) • A variety of cross checks are performed: • consistency of mT, pTe, pTn fits • vary fit region in both mass and h • bin results as a function of time, thus L • vary the recoil pT cut • fit for the Z mass using transverse mass • compare result from two end calorimeters • compare for different electron impact position • compare for different EM energy fractions mT distribution c2 distribution 16

17. Combined DØ W mass fits Systematic errors arising from uncertainty in detector or theory parameters are computed; the parameter errors are themselves correlated in some cases, and when the same data sets are employed, are correlated because of the data set. The simultaneous measurement of MW for central and end electrons is important in reducing the theoretical error due to uncertainty in the PDF. New measurement uses electrons aimed near edge of central calorimeter modules (14% gain in statistics for W).This measurement helps primarily by constraining response parameter for non-edge electrons. The full correlation matrix is determined, yielding these W mass values: Run Ia (central e) mT 80.35 0.25 GeV Run Ib (central e) mT 80.44 0.12 Run Ib (central e) pTe80.48 0.14 Run Ib (central e) pTn80.37 0.18 Run Ib (end e) mT 80.76 0.23 Run Ib (end e) pTe80.55 0.24 Run Ib (end e) pTn80.74 0.35 Run Ib (central e-edge) mT 80.60 0.44 Run Ib (central e-edge) pTe80.73 0.53 Run Ib (central e-edge) pTn80.51 0.61 Overall DØ average 80.483 0.084 GeV 17

18. Combined World results Combining with the CDF result, Tevatron MW = 80.454 0.060 GeV . LEP experiments precision (per experiment) about the same as Tevatron. LEP MW has increased over the past two years, so now good agreement between LEP and Tevatron LEP MW average 80.450 0.039 World Avg: MW = 80.451 0.033 GeV Mt, MW give strong constraint on the Higgs boson mass in the framework of the SM (green ellipse) Indirect prediction (red ellipse) from the precision LEP/SLC/nN measurements in reasonable agreement (< than 2s), but with the new higher MW, there is a weak hint of the effect of new physics. Supersymmetry would provide new particles whose virtual effects would predict higher MW. The indirect MW indication from Z, n, top measurements is 80.373 0. 023 GeV, nearly 2sfrom the measured value. 18

19. W boson mass errors Dominant combined end & central electron errors ~ Z stats ~ special run stats ~ W stats • Notes: • most errors are stats limited • use mT, pT(e), pT(n) for consistency check (3% error reduction over mT alone) • pT(e) least affected by hadronic corrections • overlaid min bias affects recoil resolution; will become worse • need both end and central e’s to control pdf uncertainty • PDF error will be further constrained in Run 2 by W/Z asymmetries • Measurement in mchannel not as accurate, but good cross check (note CDF problem in Run 1) W statistics 61 Z statistics 59 Calorimeter linearity 25 electron resolution 19 electron angle calib. 10 recoil response 25 recoil resolution 25 E in electron window 12 Backgrounds 9 pT(W) modelling 15 GW 10 radiative corrections 12 PDF uncertainty 7 Simple scaling of 84 MeV Run 1 error by 1/ N would give dMW = 20 MeV for Run 2; however, most of the errors will have some irreducible systematic component. The most problematic of these will be the detailed electron response function (non-linearity, offset), effect of min. bias overlay, pT(W) modelling. 19

20. The very first Run 2 W transverse mass plot ! Questions for Run 2 W mass • Minimum bias overlay: Can one improve with algorithm that seeks to measure underlying energy from other vertices in the same/neighboring events for each event? (recall that the DØ calorimeter samples several crossings. Run 2b may have digital filter to tag energy per cell from adjacent crossings. Use modification of energy flow algorithm to tag collisions at other z in same event?) • Which distribution?: In presence of extra min. bias evnts, is pT(e) the distribution of choice? • The W muon decay is less useful than electron; (dp)m ~2.5 GeV; (dE)e ~ 1 GeV at W peak, so expect (dMW)m ~ 2 x (dMW)e . Nevertheless, the W→ mn channel should be used… • Muons: How will one best cross-calibrate the muon momentum and electron energy scales? What subsidiary measurements are needed to understand the effects of dead material, radiative effects, etc. • Muonic Z’s: Can Z → mmevents be used for establishing hadronic recoil parameters (even if Z → mmresolution not so good)? (Double Z statistics) 20

21. Questions for Run 2 W mass • W pT: Is there a (different) optimum cut on pT(W) that will minimize the combination of statistical and W production model error? • Radiation: With a solenoid, radiated photons no longer overlap with the electron so well; what errors for the radiative corrections and how best to establish them? • New methods: Internal Run 1 analysis used ratio of W and Z transversemass and scale to LEP Z mass (thus is limited by Z statistics). This cancels many effects due to electron, underlying event response/ resolution. Remaining systematic errors from small differences in W/Z production distributions. How far can this measurement be taken? • Combined channels: At present, detector parameters (e.g. had. response) are determined in subsidiary data sets and used to generate separate mT, pT(e), pT(n) distributions. Can the fact that the underlying MW is the same for a given event in each of the distributions, can one add a constraint in the parameter determinations? (Like the constraint that the unknown t and t masses are equal.) 21

22. Higgs search • The canon: • (a) SM Higgs now constrained to < 200 GeV; • (b) maybe LEP sighted it at 115 GeV; • (c) Tevatron constraints from top/W will tighten indirect indication by x2-3. • (d) Tevatron can discover/see evidence up to 180 GeV before LHC. • At masses below 135 GeV, use W/Z + (H)production.ln (bb),l+l– (bb),nn(bb),qq (bb) , and ln (tt) (??), qq (tt) (??) channels all can contribute. expected run 2 precision • Above 135 GeV, H → W*W dominates; can use gluon fusion production. 22

23. General Higgs search questions • For some channels (Z(nn)H(bb),Z(tt)H(bb),Z(qq)H(tt) and Z→bb), triggering is an issue, even with STT detached vertex trigger. The Run 2a trigger should have t trigger capability using isolated high pT track triggers. The Run 2b trigger upgrade envisions correlating CFT and CAL information to further aid in t triggering. The Z→nn + H→bb dijet opening angle and missing ET correlations differ from QCD dijet events. Run 2b trigger improvements to CAL trigger to allow topological analysis of energy towers, and finer CFT/CAL correlation could improve t and ET triggers at L1. dijet opening angle (in trk sectors) • Triggering : Study trigger rejections possible with CFT/CAL correlations, and topological triggers using CAL. Refine the triggers for Z→ nn / tt +H→bb, and Z→ qq + H→ tt. opening angle – missing ET correlation 23

24. p p H b P b p p General Higgs search questions • The H→W*W analysis simulation is at present based on series of simple cuts on kinematic quantities and is not optimized. There is no mass peak left after cuts, so the analysis is a counting experiment. • H→W*W :Pursue a multivariate analysis for the H→W*W channel to improve its sensitivity. Seek variables that survive after cuts that carry mass information. • There may be a substantial diffractive production of Higgs, leading to two diffractive protons and a gap in rapidity to the di-b jets. Trigger on leading protons and rapidity gaps. Can one discover Higgs this way? • Diffractive Higgs :Sort out the theory of diffractive Higgs production; simulations needed to see if this is a useful channel and to find trigger efficiency. 24

25. Issues for Higgs search Higgs will not be a precision business in Run 2 ! The Run 2 Higgs Working Group study has examined many of the critical issues forrefining the search sensitivity. The two main keys for the Higgs search are: dijet mass resolution, andb-tag efficiency and purity. NN algorithm Eflow algorithm • 1. Dijet mass resolution issues: • Jet energy resolution is key (angular error is small) • Separate optimization of b and q/g jet resolutions • Getting a good sample of Z→bb will be crucial for studying b-jet optimization. • Energy flow: (Use charged tracks + neutrals in CAL). Optimize this algorithm (using data). Recent studies show perhaps 25% improvement over cone alg., (15% over NN alg.) largely due to ICR region, may be possible. Effect of corrections to b jet on Higgs mass resolution • b-jet resolution: Devise multivariate algorithm to correct b-jet resolution – use the multiplicity, leading track momenta, jet mass, topology etc. in each event to optimize dE/E • Z→bb : Improve the trigger rejection at L1. STT is essential at L2; what else? (only 2 jets? equal ET jets? 25

26. Issues for mass resolution, cont’d • Effect of initial state radiation (should ignore) and final state radiation (should combine) ISR & FSR ISR only FSR only • Handling extra jets: Can one devise a way to guess which are ISR and FSR jets? (pT, mass, angular … weighting) Can JADE-like algorithms forcing event to right # jets help? • Choice of jet algorithm (Higgs WG found little help from kT algorithm) • Jet algorithm: What is the optimum jet algorithm. Can kT be better than cone? (Recent studies suggest it does not!) • Event pileup: Higgs WG: 25% deterioration from overlaid min bias events • Event pileup: Can one learn to recognize energy due to pileup and subtract? Run 2b CAL trigger with digital filter could help tag events from other crossings. 26

27. b-tagging for Higgs Yes, the low mass Higgs search is all about b-tagging! The full simulation MC b -tag efficiency & mistag rate are improved from the Higgs WG (parametrized MC). old – Higgs Wkshp parameterized MC 27

28. b-tagging for Higgs High tanb Susy Higgs can emphasize multi-b events; for example bbA production; this may indicate different b-tagging needs (looser?) • b tag algorithms: Using data, work to improve the b-tag efficiency and decrease the mistag rates. (A Profound Statement !!) Run 2 reach in MA vs tanb • bb event tag: Is it possible to improve upon a simple ‘tight’/’loose’ single b-tag, to make a bb-pair tag based on a single combined goodness variable? (and by extension a 4b variable for selecting Susy Higgs events. 28

29. Run 2 has discovery reach beyond LEP in ~ 25 different channels. Leptons and ET are the key ingredients. DØ low ET lepton triggering in Run 2 is important addition. Tevatron has good potential for sighting SUSY in Run 2. Supersymmetry ~ ~ Trilepton final states probe chargino pair production (Run III Run 2b = 15 fb-1). GMSB: gg + ET search (c10 → G g ) • Trigger questions: Develop more powerful lepton triggers. Take the lepton thresholds lower using CFT/CAL correlations. Design restrictive t triggers. There is room for new ideas and simulations. • Pointing photons : GMSB has g decays from NLSP to LSP gravitino. Develop algorithms for photons pointing to vertex. 29

30. Stop searches in several channels Supersymmetry • squark, gluino decays place a premium on missing ET resolution, control of calorimeter noise. • Missing ET: How well can missing ET be incorporated in the trigger. Include ICR detectors in L1 trigger. Modify thresholds for summing CAL tower energy into ET to optimize resolution at L1. • Kinks: Develop the algorithms needed to detect charged particle kinks associated with c1+→ c10 p decays (slow p ) characteristic of AMSB. • And: • Framework: Tevatron in Run 1 lacked a solid phenomenological framework (defined benchmarks) for interpreting SUSY limits (as LEP had). These need to be defined for the several types of SUSY breaking. Also should develop the methodology for combining DØ and CDF results for Tevatron averages. 30

31. Summary It’s not all over when the detector is commissioned ! New clever ideas are needed to gain more sensitivity for Run 2 physics studies and searches Much work remaining to develop generators and better control of QCD processes Great opportunities to develop triggers that increase sensitivity to t, ET, special topologies Develop better algorithms – dijet mass, b-tagging, min bias event tags, etc.

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33. Combined World results Combining with the CDF result, Tevatron MW = 80.454 0.060 GeV . LEP experiments precision (per experiment) about the same as Tevatron. LEP MW has increased over the past two years, so now good agreement between LEP and Tevatron LEP MW average 80.450 0.039 World Avg: MW = 80.451 0.033 GeV The indirect MW indication from Z, n, top measurements is 80.373 0. 023 GeV, nearly 2sfrom the measured value. Mt, MW give strong constraint on the Higgs boson mass in the framework of the SM (green ellipse) Indirect prediction (red ellipse) from the precision LEP/SLC/nN measurements in reasonable agreement (< than 2s), but with the new higher MW, there is a weak hint of the effect of new physics. Supersymmetry would provide new particles whose virtual effects would predict higher MW. 18

34. p p H b P b p p