W/Z+Jets production studies in ATLAS Ellie Dobson (University of Oxford) On behalf of ATLAS and the W/Z+Jets CSC note group DIS 2008 Why study W/Z+jet events? How do we see such events in ATLAS? Summary of current MC studies Ellie Dobson

Why study W/Z+jets? Meff Events Detector 10 fb1 Detector Tests lepton reconstruction & MEt in multi jet environment Precision tests of jet reconstruction algorithms and techniques Standard model physics Testing ground of pQCD Testing LO/NLO predictions Tests of BFKL logarithms PDF studies Beyond the standard model physics Background to many BSM searches Events must be well understood before we start looking for new physics! Ellie Dobson

W/Z+jets production in ATLAS Hard jets Zooming in….. g PDF1 u Hard Scatter Underlying event (low pt hadronic recoil) d W PDF2 Example of W+1jet production W/Z LHC will be a ‘W and Z factory’ Early running will produce ~1fb-1 of data: ~20 million Ws, ~2 million Zs that can be seen (electron decay) ~1/3 of these produced in association with jets…. Lepton MET/second lepton Health warning! Back of the envelope calculation Ellie Dobson

W/Z+jets reconstruction in ATLAS Muon trigger used to write Z→μμ and W→μν events to disk Jets reconstructed in the calorimeters. Jets are built from calorimeter towers which are ‘H1 style’ calibrated to hadron level) Muons reconstructed as a combination of a track in the inner detector and the muon spectrometer Met and SumPt determined by summing over calorimeter cells. More atlas specific Electrons reconstructed as a combination of a track in the inner detector and the energy deposit in the EM calorimeter Electron trigger system used to write Z→ee and W→eν events to disk Ellie Dobson

Current activities CSC (Computer Systems Commissioning) activity currently underway in ATLAS to produce public notes on performance and analysis This talk summarises the activities of the W/Z+jets CSC note The work in the W/Z inclusive CSC note is also relevant Electronic and muonic decay channels have been studied The focus at the moment is on understanding the detector: current activities include: Put picture of first page of note here Leptons (ID, efficiency, background) Methods of background subtraction Jets (reconstruction, algorithms, bjets) Unfolding corrections Evaluating uncertainties Ellie Dobson

MC simulation and event selection W/Z+jets sample (used for main analysis) Matched Alpgen/Herwig samples (using LO PDF set CTEQ6LL), with generator level filter requiring 1 truth cone04 jet and 1(2) electrons/muons within fiducial requirements Offline procedure (default) Z EVENTS Mass cuts 2 leptons W EVENTS 1xMet 1 lepton BG and comparison samples MC@NLO, Pythia and Alpgen W, Z, dijet and other background samples Renormalisation scale of Mz2+Ptz2 used Reference cross sections calculated at NLO (where possible) using MCFM (generated using CTEQ6.1 PDFs) LEPTON Pt > 25/20/15GeV Fiducial η cuts Track matching Inner detector track Isolation cut from jets Deposit of appropriate shape in calorimeter (electrons) Hits in muon spectrometer (muons) JET Pt>20 or 40 GeV Fiducial rapidity cuts Isolation from leptons Seeded cone 04 algorithm used MET Met>25GeV (W events) Ellie Dobson

Correcting from parton-hadron level Data measurements compared to theory predictions at hadron level → need to correct theory with respect to fragmentation and underlying event Determine corrections by comparing Pythia hadron level results with non perturbative effects switched on/off Underlying event and fragmentation have the opposite effect Precise behaviour depends on the jet algorithm used Can check underlying event in data using minimum bias events Pythia gives a better description of the underlying event at the Tevatron In general the underlying event wins Effects get smaller at higher energy because underlying event is essentially constant but Pt jet increases Fragmentation effect becomes smaller because jet becomes more collimated Fragmentation corrections for cone07 smaller than for cone04 whereas underlying event corrections are larger Performance of kt06 comparable to cone04 Underlying event adds energy to the hadron level jet Fragmentation reduces the amount of energy in the jet cone Negligible effect for higher energy jets Ellie Dobson

Trigger and reco efficiencies (Z→ee) Single electron trigger (e25i) used to select Z → ee and W → eν events e25i efficiency determined using a ‘tag and probe’ data driven method (although results shown are obviously ‘pseudo data’ for the time being….) The numbers may be used to determine Z → ee or W → eν cross section Sufficient in inclusive study to consider the efficiency as a function of η and pt only In these more ‘jetty’ events is important to study the efficiency as a function of jet variables (distance to closest jet, hadronic activity, jet multiplicity….) Global trigger efficiency ~1.5% lower than in the Pythia inclusive sample Trigger efficiency Reconstruction efficiency Fall with higher hadronic activity due to the implicit isolation cut in the level 1 trigger Ellie Dobson

Unfolding of detector effects (Z→ee) Need to unfold data (jet and electron resolutions and reconstruction efficiencies) from detector level to hadron level Will eventually determine jet resolution and efficiency from real data Bias in reconstruction at low jet pt For jet resolution used a global average correction. Effect is worse in tevatron experiments The idea is to set up the machinery for making cross sections with data- test for perturbative QCD Jet resolution and efficiency from real data possible- dijet matching in different planes Make graphs by truth-reco matching in pt and dR (0.2 and 0.5-1.5) At higher Pt deviations could suggest quark compositeness BFKL logarithms can show up in these plots Can probe these jets up to the multi TeV range No global behaviour seen Within errors, the Pt distributions of truth and corrected reconstructed jets agree Ellie Dobson

BG estimation and subtraction (Z) Z-ττ, ttbar and W → lν are, for now, estimated and subtracted using MC estimates Weighting factors used for QCD due to the enormous cross section of this process Fits may be used to estimate QCD backgrounds in real data Can also derive this background by inverting selected electron ID cuts Muons coming from background (particularly bbar) can be rejected using isolation requirements QCD background dominates at a 1 jet signal. At higher jet multiplicity ttbar dominates. Mass cuts imposed to reduce background I use a JF17 sample (3Mio evts) where all W,Z,TTbar are already discarded in order to avoid double-counting. In the signal and background plots I do the complete electron ID for all samples except for JF17 where I only require two AOD electron candidates. The events are then weighted by the additional rejection from the isEM medium and the trigger conditions. This additional rejection is derived using JF17 events with single AOD-electron-candidates, which fulfil all kinematic requirements. I derive a rejection separately for AOD-electron-candidates which don't match with a truth electron (actually the majority) and for AOD-electron candidates which match with a truth electron (probably mostly from B-decays). > Do you have any plans to use data driven estimates for the other processes? Yes, in particular for the TTbar. The most difficult part is to separate the Ttbar from the QCD because we expect a different PT distribution for TTbar and for QCD. A few ideas: Loosening the electron ID would increase the QCD but not the TTbar, requiring low Etmiss will decrease the TTbar but the QCD will stay the same, whereas requiring a minimum ETmiss will decrease the QCD but the Ttbar will stay the same. Ellie Dobson

BG estimation and subtraction (W) QCD Zee Weν QCD largest background ttbar dominates at high Njets W→τν and Z →ee estimated using MC Pythia underestimates QCD QCD can be estimated from data using photon trigger and normalising to electron spectrum in sideband QCD also can be estimated using fake rates ttbar W→τν Ellie Dobson

Jet energy scale (JES) uncertainties Dominant experimental systematic for W/Z+jets at the LHC Miscalibration of ±1, 3, 5% assumed on the jet energy and effect on jet pt calculated Main effect on the cross section results from the selection cut on the jet pt Within early running (1fb-1) we hope to be within 3% JES uncertainty → systematic on the cross section of up to 10% JES uncertainty of 1% (ultimate ATLAS goal) yields systematic of 0.5% W events Uncertainties increase with jet multiplicity Ellie Dobson

PDF uncertainty studies Must get these right or SM physics could be misinterpreted as new physics! PDF uncertainties often the dominant theoretical uncertainty PDF forms determined from combination of theoretical calculations and data Free parameters of fit are given in a PDF set with their upper and lower errors Overall PDF uncertainties calculated with PDF reweighting on NLO CTEQ6M set PDF uncertainty ≤ JES uncertainty Uncertainties always remain <10% Hessian method used PDF reweighting used to avoid generating two MC samples for each free parameter in the global fit. Apply an event to the hard process- probability of picking up the same partons with the same momentum fractions Shown results for W→eν. Similar results seen in the muons and Z analysis PDF errors increase at central η and at low electron Pt (no y dependence seen) Ellie Dobson

Cross section results (Z→ee) MCFM predictions corrected (for underlying event and fragmentation) to hadron level Data unfolded to hadron level PDF and JES uncertainties are included in the error determination Cross sections quoted wrt inclusive to factor out luminosity uncertainty in early data Can scale the MC samples globally with (inclusive cross section predicted with the MC sample - inclusive cross section measured in data) - only interested if the XS fraction of the subsamples with >=N jets is reproduced correctly for detector validation Pythia predicts a larger inclusive cross section for >=1jet Results normalised to NLO inclusive (DrellYann) MCFM cross section Pythia predicts a softer pt spectrum Pythia discrepancies due to tuning of leading soft radiation in parton shower Ellie Dobson

XS (Z →μμ) Data unfolded to hadron level as before Choice of isolation cone size must be optimised so to balance muon reconstruction efficiency and background rejection Cross sections normalised to NLO MCFM predictions corrected and compared to unfolded reconstructed events Unfolded distribution - Count more jets in Pythia if you do soft cuts on the jet PT. - For Cone 20- isolation there is +- no efficiency loss. Pytha predicts more low pt jets Pythia parton shower predicts softer jet pt distribution Alpgen predicts more high pt jets Ellie Dobson

Z→μμ+bjets A cross section measurement in this channel will provide an important test of pQCD Will reduce the current uncertainty on the partonic heavy flavour content This channel will be a lot easier at the LHC than at the Tevatron (higher production cross section, smaller background from Z+cjet) btagging: cutting on the weight parameter (secondary vertex and impact parameter) Z+cjet background depends on the sea quark distributions. gluon distributions dominate at the LHC (gb→Zb will dominate over qqbar → Zbbar) Thus the sea quark contributions are relatively suppressed. At the Tevatron, the sea quark contributions can contribute more strongly Contamination from light jets of the order 30% Ellie Dobson

Conclusions W/Z+jets used as a standard candle to understand the detector Understanding necessary in SM and BSM sectors Specific findings: Efficiencies ~1% lower than the inclusive due to hadronic isolation Cuts developed so that signals are larger than background sum Tools for estimating the dominant backgrounds from data developed Two main non perturbative effects neglible above a jet Pt of 40GeV Comparisons made between theory (corrected to the hadron level) and data (unfolded from detector level) are in agreement JES dominant systematic. Will be reduced to ~3% after 2 years This is larger than dominant theoretical uncertainty (PDF uncertainties) Ellie Dobson