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Amnon Harel aharel@fnal University of Rochester

International Workshop on Top Quark Physics La Biodola, Isola d’Elba, Italy 18-24 May, 2008. MC for top background at the Tevatron. Amnon Harel aharel@fnal.gov University of Rochester.

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Amnon Harel aharel@fnal University of Rochester

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  1. International Workshop on Top Quark PhysicsLa Biodola, Isola d’Elba, Italy18-24 May, 2008 MC for top backgroundat the Tevatron Amnon Harelaharel@fnal.gov University of Rochester Thanks to: Kirsten Tollefson, Lisa Shabalina, Christopher Neu, Tom Junk, Ann Heinson, Jason Nielsen, Michael Begel, Ulrich Husemann, Kevin Lanon, Gustavo Garzon, Gerald Grenier, and apologies to those whose names I accidentally left out

  2. Outline Backgrounds Measurements Matched MC Reweighting the MC The cost of matching • BTWs: • multijets • Detector simulation Amnon Harel

  3. The backgrounds – top pair Hard to simulate misreconstructions  Data driven estimation Dilepton channel Small  A rough simulation suffices A.k.a.: Z+jets Lepton+jets channel Haven’t discovered that one yet Amnon Harel

  4. V+jets – top pair Dilepton channel • Z(ee/μμ)+jets - main background in ee and μμ channels, Z()+jets in eμ • Very important at the early stages of event selection • After final selection Z+jets contribution is small • Most measurements do not use b tagging • Flavor composition usually not important Lepton+jets channel • This channel provides the most precise measurements • W+jets - main background • Very important at all stages of selection • Most of measurements use b-tagging • Knowledge of flavor composition is a limiting factor for precision measurements Amnon Harel

  5. The backgrounds – single top H.F. fractions of W+jets crucial W+light Multijet • BTW: WH Higgs search is also sensitive to W+jets H.F. fractions CDF Amnon Harel

  6. V+jets cross sections Amnon Harel

  7. W+bb measurements What have we measured? Though conclusions from W+HF measurements not yet applied to top analyses CDF preliminary from Monday(1.9fb-1): Harsh b-tagging and MET (>25GeV) selections Jet definitions: Jet selection: Result: Alpgen prediction: 0.78pb , & , & DØ preliminary from 2005(382pb-1): , , & Amnon Harel

  8. W+c measurements CDF Data: MCFM: DØ Data: Alpgen+Pythia: Phys. Rev. Lett. 100, 091803 (2008) arXiv: 0803.2259v1[hep-ex] Recent MCFM calculations (John Campbell) for DØ cuts yield R(LO)=3.7, R(NLO)=3.4 Amnon Harel

  9. W+jets measurement Dedicated W+jets measurement. SMPR = CKKW matched Madgraph + Pythia MLM = MLM matched Alpgen + Herwig MCFM = NLO predictions will be a recurring theme Amnon Harel

  10. Matched MC For top physics, we usually simulate W+jets (also Z+jets) using MLM matched Alpgen. Implementations differ: • light partons jets are MLM matched • with pT>8GeV • MLM stable to the chosen pT • Discard events with additional heavy quarks from the PS MC • done in post processing • Generate 14 samples: • W+bb+Nlp, with N=0,1,2, or ≥3 • W+cc+Nlp, with N=0,1,2, or ≥3 • W+Nlp, with N=0,1,2,3,4, or ≥5 (includes W+c+jets  massless c quarks) • MLM matched (pT>15GeV) within each class of events • cc / bb pairs within the same parton jet are taken only from the PS MC; those in different jets taken only from the ME MC • Generate 15 samples: • W+bb+Nlp, with N=0,1, or ≥2 • W+cc+Nlp, with N=0,1, or ≥2 • W+c+Nlp, with N=0,1,2, or ≥3 • W+Nlp, with N=0,1,2,3, or ≥4 Amnon Harel

  11. Alpgen qfac=ktfac=0.5,could be a JES issue Z+jets Simulation • Z+jets appears at a lower rate (~×10), but has much less background  a good process for tuning the simulations. • NormalizationUsually it suffices to normalize according to cross sections predicted from MCFM or NNLO calculations. • Dependency on kinematic cuts! • Some analyses require normalization from data, e.g., CDF’s top FCNC search in Z+jets • KinematicsCan be tuned using data • Example: ResBos described DØ’s Z pT data well. DØ is starting to use it as a surrogate to the data and to re-weight ALPGEN+PYTHIA to match the same spectrum. The same re-weighting is carried over to W+jets. Alpgen qfac=ktfac=1 arXiv:/0712.0803 Amnon Harel

  12. Z+jets Shape: Pythia & Sherpa - I Sherpa uses CKKW matching T Normalized to data without parametrizing in Njet Pythia is a parton shower generator  not enough radiation JES uncertainties dominate systematics (and are a bit conservative) Amnon Harel

  13. Z+jets Shape: Pythia & Sherpa - II Again Pythia spectrum is too soft Amnon Harel

  14. Z+jets Shape: Pythia & Sherpa - III Again Pythia spectrum is too soft Amnon Harel

  15. Z+jets Shape: Pythia & Sherpa - IV We’ll return to the simulation of dijet angles… Amnon Harel

  16. Z+jets vs. NLO Dedicated Z+jets measurement. Phys. Rev. Lett. 100, 102001 (2008) MCFM hiding behind data points Amnon Harel

  17. Normalizing W+jets W+jets and W+HF are normalized to data, after other backgrounds (multijets, dibosons, etc.) are subtracted. • multijets estimated from data samples with leptons that pass only a looser selection (mostly looser isolation) • “loose-tight” • several approaches, typically: • W+jets normalized to data before b tagging • or fitted in signal samples • W+HF fractions normalized to data after b tagging • multijets estimated from data samples with leptons that pass only a looser selection • “anti-electrons”, ”non-isolated” • Studies with dijet & multijet events • “Method 2” inherited from Run I: • W+jets normalized to data before b tagging • W+HF fraction fitted to data after b tagging Assumptions: Kbb=Kcc, and Kc=1 (consistent with studies) Amnon Harel

  18. W+jets Normalization @ CDF • Three parameter fit to Bottom-Charm-Light templates of jet-flavor separating distributions (NN output, SecVtx mass) in W+2 jet data • yields KHF=1.4±0.4 • relative to Alpgen H.F. fraction • Light flavor yield with prediction from • per jet fake b tag rates (estimated from inclusive multijet data) • either W LF MC or data, pre b tag yields Amnon Harel

  19. W+jets Normalization @ DØ PRL 98, 181802 (2007) • For W+jets: • Normalize to pretag data • Channel dependence? • single-top vs. top-pair analysis • same in e+jets & μ+jets within uncertainties • Njet dependence? • For W+HF: • Normalize to data after b-tagging • in 0 b tag bin  negligible signal • Defined relative to Alpgen H.F. fraction First data driven normalization: single-top evidence analysis Amnon Harel

  20. Sensitive to extra backgrounds included Sensitive to selection cuts on jets single top ||<3.4; ttbar ||<2.5 Consistent between e/μ channels Studied several cuts on b tag output Measured HF scale factor (uncertainty from all deviations observed in the studies): KHF = 1.170.18 Used for summer results W+jets Normalization @ DØ - II Procedure refined for later ttl+jets measurements • tighter selection cuts • normalize MC to match the fraction of 0 tag events in 1 and 2 jet bins Studies of systematic uncertainties • Separated Wc for W+lp and varied by 20% (not enough?) • Dependence on the multijet background contribution • Tried to extract corrections to Wcc and Wbb separately Results • Switched from Alpgen 2.05 to 2.12 • Several bug fixes including one in Wcc / Wbb generation • Compared shapes: the only noticeable difference is R(j,j) • Cross sections differ by a factor of 2! • New KHF factor ~1.9 Amnon Harel

  21. W+jets Normalization for BYSM Normalizing W+jets to data with the same jet multiplicity as signal is not trivial for BYSM searches, or even for cross section measurements. Examples • searches for resonant top pair production • Iterative procedure in CDF’s • Analytical work around in D0’s • Charged Higgs search Amnon Harel

  22. W+jets: Other Reweightings Some discrepancies between Alpgen and data are showing up with the increasing statistics. Corrected for / treated as systematic uncertainties in recent measurements. E.g. possible missimulation of the angular distributions of the jet with the 2nd highest pT Plot from latest single top analysis Amnon Harel

  23. DØ experience with matching At the time, Alpgen was the only matched MC that CDF & DØ could: run, integrated with their software, mass produce. It allows us to produce physics results! Large scale use + cutting edge technology = pain Outlining the DØ experience to identify lessons. • Must add together the parton-jet bins with the correct weights. Unfortunately, weights are sample dependent • Must freeze samples • Post processing in DØ due to overlaid zero bias data & HF removal • Book keeping nightmare (ttbar, Z+jets in HF & MZ* bins, systematic variations) • Error prone • Large relative weights • necessary for multiple (additional) jets • but complicates statistics (some physics required) Amnon Harel

  24. DØ experience with matching • Using matched Alpgen extensively for the last couple of years: • We’ve made several mistakes, e.g., • Random seeds outside legal range • Imperfect HF removal • Study Interplay with MC tunes • Some bugs found along the way, had to find workarounds • Best case: need to look at the right plot in the right channel • Recent case: “why does that matching weight look odd?” • Slow turn around times • Alpgen release  DØ release  Production (large 0lp samples, slow 5lp samples)  Postproduction  Analyses • 6-12 months • Limits our ability to generate sufficient samples to study systematics Amnon Harel

  25. Work in progress – Example of failed model BTW1: MC in multijet modeling • Though multijet modeling is data driven, it is (mostly) based on samples with 3 jets which are reconstructed as lepton + 2 jets. • Can check the methodology using simulated multijets • Lepton ID cuts • Lepton ID efficiencies and their parametrization • MET (“triangle”) cuts • Sample composition Example of bad agreement from recent DØ studies: Amnon Harel

  26. BTW2: Detector simulation • An ubiquitous problem, often taken for granted.Data based modeling for: • misreconstructed leptons, i.e., multijet background • b tagging rates • relative jet energy scale • This talk focused on the generator parts of simulation rather than on detector simulation. • Modeling of multijet background is covered in analysis presentations • the last two items will be covered in two talks about “tools for top” later today (CDF @ 15:30, D0 @ 16:00). Amnon Harel

  27. Conclusions • Simulation of W+jets and Z+jets • is not trivial • can be analysis dependent: • One size can almost fit all • Don’t always need the most sophisticated treatment • Several approaches to estimating the heavy flavor contribution • Can fit and/or normalize W+jets • New physics can complicate matters • Using matched Alpgen extensively for the last couple of years • Able to meet all our physics needs! • Higgs / Top pairs / single top / W+HF / Z+HF • Lepton+jets+MET / di-lepton final states (Z+jets important) • possible inaccuracies (e.g. Z pT, 2nd jet ΔR) • difficulties adapting to this technology • Technical lesson: avoid any post processing that can break the matching • Other generators seem promising • but have received much less scrutiny Amnon Harel

  28. Back up slides Amnon Harel

  29. 29 Other weights To estimate PDF uncertainties we reweight our MC after the fact, rather than regenerate it. Is this compatible with MLM matching? Yes [private communications with Mangano] We simulate additional collisions by overlaying “zero-bias” data (i.e. free of trigger biases) onto simulated collisions. Since instantaneous luminosities are still rising, we “update” the simulation by giving more weight to simulated events whose overlaid data event had a high inst. lumi. Amnon Harel

  30. 30 Matching @ CDF Amnon Harel

  31. Calibrating the Simulation • We verify each aspect the simulation, mostly on appropriate data samples, and correct the simulation as needed. • Jets • Relative energy scale • Energy resolution (ET smearing) • Reco. & ID Efficiencies • b-tagging rates • Corrections for gluon splitting • Instantaneous Luminosity • Primary Vertex Z-coordinate • Electrons • Resolutions (ET smearing) • Reco. & ID efficiencies • Muons • Resolutions (pT smearing) • Reco., ID and isolation efficiencies Amnon Harel

  32. Normalizing to Data @ DØ In several double-top l+jets “property” analyses • W+HF normalized to data as in previous slides • W+jets fit to data • topological likelihood separates top pair from W+jets Example from PRL 100, 062004 (2008) Backgrounds (mostly W+jets) Top Pair Amnon Harel

  33. Normalizing W+jets @ DØ HZ Another example: Higgs search in HZbbX channel • Heavy Flavor in (W/Z)+jet Alpgen+Pythia predictions were multiplied by K-factors (NLO/LO) calculated with MCFM • (W/Z)+jets normalized to data before b-tagging After b-tagging Before b-tagging Amnon Harel

  34. Terminology • DØ is trying to converge on terminology for normalization factors: • K-factor: normalizes LO to match (N)NLO • K’-factor: normalizes MC to match (N)NLO • S-factor: normalizes MC to match “pretag” data • SHF: normalized heavy-flavor MC to match b-tagged data • At DØ: • For Z+lp and Z+HF: • Using K’-factors, normalize to theory • Some analyses (e.g. ) override with S-factors • For W+lp: Using S factors • For W+HF: Using S & SHF factors Amnon Harel

  35. Know-how I • Generate 14 samples: • W+bb+Nlp, with N=0,1,2 or ≥3 • W+cc+Nlp, with N=0,1,2 or ≥3 • W+Nlp, with N=0,1,2,3,4 or ≥5 (includes W+c+jets) • Individual samples can not be used any more! Add all parton-jet bins together with weights Fi Amnon Harel

  36. Know-how II • Sample has to be frozen • Large relative weights • Complicates statistics • Post processing: • Data quality selection due to zero bias overlay • Discard events with additional heavy quarks created by Pythia • Generate 14 samples: • W+bb+Nlp, with N=0,1,2 or ≥3 • W+cc+Nlp, with N=0,1,2 or ≥3 • W+Nlp, with N=0,1,2,3,4 or ≥5 No skimming Book keeping is a nightmare! Amnon Harel

  37. Generate multi-parton MEs with Alpgen Add showering and hadronization from Pythia b-fragmentation model underlying event model Run full D0 detector simulation and reconstruction Add zero bias events to match luminosity profile in data Apply to simulated events: JES Jet removal Smear jets, electrons and muon Propagate to missing ET Correction factors: Trigger efficiency Electron and muon ID efficiency For b-tagging: Taggability RF Tag rate function Reweightings: lumi, z vertex, etc From generated MC to data Amnon Harel

  38. Alpgen qfac=ktfac=1 Z+jets @ CDF - I FCNC analysis used this for a systematic uncertainty. negligible – doesn’t appear in the tables Alpgen qfac=ktfac=2.0 Alpgen qfac=ktfac=0.5 Amnon Harel

  39. MCFM Z+jet @ DØ An example: Results for 60-75 GEV Amnon Harel

  40. MCFM W+jets @ DØ Method • All calculations come from the MCFM author (John Campbell) • K-factor = sigma(NLO)/sigma(LO) • Parameters: • PDF: CTEQ6L1(LO), CTEQ6M (NLO) • Factorization scale = Renormalization scale = MW Conclusions • MCFM calculations show that K-factor for W+light is stable • K-factors for Wc, Wcc, Wbb decrease as jet pT increases • MCFM does not support any additional HF scale factor in addition to W+light k-factor • The last conclusion contradicts our observation from data Amnon Harel

  41. DØ Z+jets Normalizations • When estimating the W+jets background in Lepton+jets+MET channels, we predict Z+jets from the simulation + studies on di-lepton channels. • For Z+lp and Z+HF: • Typically weigh Alpgen+Pythia to MCFM / NNLO • NNLO from Hamberg et.al., Nucl.Phys.B359 + Martin et.al. hep-ph/0308087 • Agree to within 10% • Recently calculate the K-factors with MCFM (is shaping needed?) • K-factors in the theoretical sense: NLO/LO • Cuts crucial in W+2HF (e.g. ) • Evaluate effect of quark masses at LO: 10-40% Amnon Harel

  42. 2nd jet angles @ 1 fb-1 Clearly there’s nothing to be excited about in this plot. Very preliminary analysis of later data shows similar trends. Amnon Harel

  43. DØ Z+jets Shape Corrections arXiv:/0712.0803 • Starting to use ResBos as a surrogate to our data • Reweighting Alpgen+Pythia MC to fit the ResBos spectrum • Applying the lesson from Z+jets to W+jets… • Other approaches • Scale directly to data as a function of Njet • Consider other event source • Measure & reweight as a function of: • ZpT (reconstruction vs. particle level) • jet observables Amnon Harel

  44. 1 4 + ( ) ( ) ( ) l b i 9 8 2 8 0 6 t t t § : § 1 4 + s a s y s u m p ( ( ) ( % ) ) % b P D F 1 4 7 1 1 4 0 0 1 3 7 § § 1 6 ¡ . : : : : : : p : 3 0 ¡ : : : : : : W+c measurements CDF Data: MCFM: DØ Data: Alpgen+Pythia: Phys. Rev. Lett. 100, 091803 (2008) arXiv: 0803.2259v1[hep-ex] Recent MCFM calculations (John Campbell) for DØ cuts yield R(LO)=3.7, R(NLO)=3.4 Amnon Harel

  45. Title • Text Amnon Harel

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