Light Jet reconstruction and calibration in B.Andrieu (LPNHE, Paris)

Introduction: Cone Jet algorithm basics Cone Jet algorithms Associate “particles” inside a cone, where particles can be partons (analytical calculations or parton showers MC) “hadrons” = final state particles (MC particles or charged particles in trackers) towers (or cells or preclusters or any localized energy deposit) Calculate jet 4-momentum from “particles” 4-momenta  Defined by Clustering procedure, Distance and Recombination scheme Cone (proto-) jets are chosen as “stable” cones, i.e. cones whose geometrical position (axis) coincides with jet direction (3-momentum)  How to find all stable cones in minimum CPU time? Quark and gluon jets (identified to partons) can be compared to detector jets, if jet algorithms respect collinear and infrared safety (Sterman&Weinberg, 1977) QCD  { Infrared unsafety Collinear unsafety Figures from hep-ex/0005012 Problems of “naive” Cone Jet Algorithms using seeds Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

Introduction: the Ideal Jet Algorithm for Tevatron Compare jets at the parton, hadron and detector level  Jet algorithms should ensure infrared and collinear safety invariance under longitudinal boosts fully specified and straightforward to implement same algorithm at the parton, hadron and detector level boundary stability (kinematic limit of inclusive jet cross section at ET = s/2) factorisation (universal parton densities) independence of detector detailed geometry and granularity minimal sensitivity to non-perturbative processes and pile-up events at high luminosity minimization of resolution smearing/angle bias reliable calibration maximal reconstruction efficiency (find all jets) vs minimal CPU time replicate RunI cross sections while avoiding theoretical problems General Theory Experiment Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

Introduction: RunII Cone Algorithm (hep-ex/0005012)  2 new Cone Algorithms proposed for RunII (G.C. Blazey et al., “RunII Jet Physics”, hep-ex/0005012)  Seedless Cone Algorithm  Almost ideal, but very computationally intensive  RunII (= Improved Legacy or Midpoint) Cone Algorithm = approximation of the seedless algorithm QCD calculation at fixed order N  only 2N –1 possible positions for stable cones (pi , pi+pj , pi+pj+pk ,…) Data: consider seeds used in RunI Cone algorithms as partons  in addition to seeds, use ‘midpoints’ i.e. pi+pj , pi+pj+pk ,… only need to consider seeds all within a distance DR < 2Rcone only use midpoints between proto-jets (reduce computing time) otherwise algorithm similar to RunI Other specifications of the suggested RunII cone Algorithm E -scheme recombination = 4-momenta addition use true rapidity Y instead of pseudo-rapidity h in DR use all towers as seeds (pT > 1 GeV) splitting/merging: pT ordered, f = 50 % Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

DØ calorimeter reconstruction U/LAr calorimeter Pseudo-projective geometry ~ 45 000 cells, ~ 5000 towers Granularity 0.1 x 0.1 in (h,f) From cells to towers Cells Electronics calibration and baseline subtraction Noise removal: 0-suppression (2.5 s), remove isolated cells (2.5/4 s) (h,f) intercalibration using jets EM cal calibrated using Z e+e-  To each cell is associated a massless 4-vector (primary vertexcell center) Towers Combine (4-vector addition) all cells with non-0 signal in the same geometrical tower (pointing to detector center) Towers may be massive  Towers are basic objects used for jet reconstruction Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

DØ Run II Cone algorithm (I) Algorithm defined in “RunII Jet Physics” (hep- ex/0005012) parameters in green, changes w.r.t. definition in red Reduce the number of seeds for clustering  Preclustering seeds = pT ordered list of particles with pT >0.5 GeV (1 GeV in RunI) reduce effect of noise in CH and ECMG  special treatment for towers if highest energy cell of a tower is in CH or ECMG, its energy is removed from the tower before applying the above minimum cut for seed selection precluster = all particles in a cone of r = 0.3 around seed (for Cone Jets with Rcone  0.5) precluster 4-momentum calculated using the E – scheme Search for stable cones starting from preclusters  Clustering seeds = pT ordered list of preclusters with pT > 1 GeV except those close to already found proto-jets: DR (precluster, proto-jet)< 0.5 Rcone form proto-jet cluster all towers within Rcone of the precluster axis in (Y ,f) space recalculate proto-jet 4-momentum (E - scheme) iterate proto-jet formation (cone drifting) until cone is stable (cone axis coincides with proto-jet direction) OR pT < 0.5 pTmin OR # iterations = 50 (to avoid  cycles) remove duplicates Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

DØ Run II Cone algorithm (II) Ensure infrared and collinear safety  Clustering from midpoints repeat same clustering using midpoints (between previously found proto-jets) as seeds except no condition on close proto-jet no removal of duplicates  proto-jets (with possible overlaps) Treat overlapping proto-jets  Merging/Splitting use pT ordered list of proto-jets (from seeds and midpoints) a pT cut at 8 GeV was used in RunI and suggested for RunII, but is not applied now note that pTmin / 2 cut on proto-jets candidates implies a pT cut at 3 GeV (at least) attribute shared energy exclusively according to shared energy fraction ET,12 > f . Min(ET,1, ET,2)  Merge jets ET,12 < f . Min(ET,1, ET,2)  Split jets = assign each particle to its closest jet f = 50 % at each merging/splitting step recalculate 4-momenta of merged/splitted jets re-order list of merged/splitted jets treat all proto-jets until no shared energy is left  final list of proto-jets (without overlap) Calculation of jet variables and final pT cut E-scheme recombination (4-momenta addition) pT ordering final pT cut: pTjet > pTmin (pTmin = 6 GeV)  final list of jets Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

Jet Reconstruction and Identification efficiency (I) Fake jets due to bad noise conditions (especially at the beginning of RunII)  Jet-ID cuts identify “good” jets and reject “fake” jets as efficiently as possible based on: - either topological variables (EMF, CHF, n90,…) - or signal in independent electronic readout (L1 confirmation) The “true” jet efficiency relates particle jets to detector jets: for particle jets at a given pT and h, it is the fraction of matching detector jets reconstructed and passing ID cuts Can only be measured in MC Neglects ambiguous matching between detector and particle level (1->2 or 2->1..) 3 sources of inefficiency: ID cuts Algorithmic Detector (fixed pT cut + energy response) In mathematical terms: Main dependence is on pT_particle (dependence on eta is expected to be less important) But dependency on pT_min is also important Due to improper calorimeter response (and trigger) simulation, these 3 sources of inefficiency give 3 possible sources of difference between data and MC Efficiency Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

Jet Reconstruction and Identification efficiency (II) Relative importance of 3 sources of inefficiency ID cuts  limited effect (few %) in some specific regions, mostly pT independent  most important at high pT Algorithmic  totally negligible at high pT and O(1-2) % at lowest pT Energy resolution (+fixed pT cut)  unavoidable!  main pT-dependent effect at low pT (up to 20-25 GeV) and affects reco efficiency  same pT cut must be applied consistently after JES for proper data/MC comparison Efficiency measurement through Tag & Probe method (assuming reco and ID efficiency factorize) Tag = Z, g, good jet (+ track jet opposite to Tag to provide Probe h) Probe = jet (close to track jet) whose efficiency is to be measured Is there a jet?  reconstruction (reco) efficiency Is it a good jet (= does it pass ID cuts)?  identification (ID) efficiency Comparison data/MC Correct MC to adjust efficiency in MC to that in data Caveat: Efficiency measured in data is NOT true jet efficiency (pT_Tag ≠ pT_true) At low pT only the effect of pT cut is visible (residual inefficiencies too small) Issue: Efficiency correction by pT-dependent removal leads to biased distributions  for pT-dependent (reconstruction) inefficiency at low pT (energy resolution + pT cut) corrections applied through energy scale and resolution corrections  for pT-independent (identification) inefficiency at high pT corrections applied through removal of a small fraction of jets in MC Measurement Correction Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

B.Andrieu Light Jet reconstruction and calibration in D∅ - Jet Reconstruction efficiency in Z+jet Z+jet sample: A reconstructed Z (Tag) and at least 1 track jet Exactly 1 trackjet with ΔΦ(Z,trackjet) > 2.5 or ≥ 2 trackjets with ΔΦ(Z,leading pT trackjet) > 2.5 or else, ≥ 2 trackjets with ΔR(leading,next) < 0.7 and ΔΦ(Z,combined trackjet) > 2.6 ΔR(leading trackjet or each from the combined, e from Z) > 0.5 Veto jet activity outside the Tag and Probe region (DeltaR> 0.5) Veto on photon (no EM cluster without an associated track) and on a 3rd electron Measure efficiency of finding a good jet matched to the probe track jet (DR<0.5) as a function of pT for different |h_det(track-jet)| regions CC ICR pT>15 pT>15 Good agreement after Energy Scale and Resolution corrections Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

Jet Identification efficiency in g+jet and dijet ID efficiency Scale factor data/MC ID efficiency Plateau values data/MC Agreement between different methods MC jet removal according to measured scale factors as a function of h_jet Systematics function of pT (ID efficiency lower in MC than in data?  not corrected, in systematics) Detailed systematic studies (bin size, fit procedure,…) Closure test Systematics down to 0.5-1% level (except in some specific regions: up to 4% at low pT & ηdet 0-0.4 or 0.8-0.9) Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

Issue with RunII Cone algorithm: “Dark” jets Jets might be missed by RunII Cone Algorithm (S.D. Ellis et al., hep-ph/0111434)  low pT jets too close to high pT jet to form a stable cone (cone will drift towards high pT jet) too far away from high pT jet to be part of the high pT jet stable cone proposed solution  Smaller Search Cone Algorithm remove stability requirement of cone run cone algorithm with smaller cone radius to limit cone drifting (Rsearch = Rcone /  2) form cone jets of radius Rcone around proto-jets found with radius Rsearch Remarks Problem of lost jets first seen by CDF, finally observed by DØ with 2nd-pass algorithm (re-run cone jet algorithm on unclustered energy) For DØ, maximum effect on inclusive jet cross-section ~ 1% (below 20 GeV) and O(10-5) above 50 GeV  totally negligible Effect unknown in multi-jet environment? Proposed solution unsatisfactory w.r.t. cone jet definition anyway  D preferred using RunII Cone without Smaller Search Cone  CDF decided recently to abandon this option too Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

Jet Energy Scale: overview Jet energy corrected to the particle level: Offset (O ): energy not associated with the hard scattering (noise, pileup from previous BC and other interactions in the same BC) measured from zero bias and minimum bias events. Response (Rjet=RCC x F (h)): calorimeter response to a jet Jet absolute energy scale for central calorimeter RCC measured from ET balance in g +jet events h dependence F (h) relative to CC determined by combining g +jet and dijet events for higher statistics and greater energy High energy extrapolation with modified cell-response MC Showering (S ): correction for net energy flux through jet cone boundary, measured from energy density around jet Various k’ s: bias corrections to offset and response estimators. Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

Jet Energy Scale: Offset correction Correct for multiple interactions (MI), noise and pileup (NP) + energy associated with high pT collision that becomes visible as a combined result of Offset Energy addition in each calorimeter cell AND Zero Suppression (≠ in MB events and in jet area  ZS bias) Compute energy per i ring (integrated over i) from ZB (noise and pile-up) and MB (multiple interactions) data Measure separately NP and MI contributions, as a function of , nPV and L O(L, nPV)=OZB(L)+OMB(L,nPV)-OMB(L,nPV=1) Zero-Suppression bias estimated using g+jet MC w/o and w/ ZB overlay, suppressed and unsuppressed (note: similar bias affects the response measurement, corrected independently. Both corrections cancel almost perfectly.) Correction determined from average energy per ring within jet area assuming jet is a circle in (h,f)  individual jet shape not taken into account ZB (LM and PV veto) MB (L~1.6x1032 cm-2s-1) Total Offset Energy 1.2x1032 cm-2s-1 0.5x1032 cm-2s-1 0.1x1032 cm-2s-1 Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

Jet Energy Scale: Absolute Response correction True response of a particle jet in CC derived using g+jet events using the MPF (Missing ET Projection Fraction) method. Rrecoil/Rg= 1 + MET/pTg (projected onto g direction) Typically fit: R(E’) = p0+p1log(E’/100)+p2log2(E’/100) E’ = pTg cosh(jet) biases to be corrected (each at the % level): Photon energy scale and dijet background contamination Impact of zero-suppression (similar in size to bias in offset) Topology bias (difference between response of recoil and response of the jet) Total error at the % level Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

Jet Energy Scale: Relative Response correction determine response of a jet at  relative to CC (-dependent corrections) derived in the whole range (||<3.6) in very fine  binning (~0.1). Also E dependent. use MPF method in g+jet (low ET region) and dijets (higher ET region) events, to extend the kinematic range. Tag object (g or jet) in CC, probe jet anywhere in  Issues Discrepancy between g+jet and dijets (up to 10%) Background contamination in g+jet g energy bias different flavor composition (due to difference between quark - and gluon-jet responses) Resolution bias (effect of resolution + steeply falling pT spectrum) to be corrected for dijet Zero-suppression bias and topological bias Uncertainty Results Correction Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

Jet Energy Scale: Showering correction Compensate for net energy flow through jet cone boundary Use same g+jet sample as for absolute response except jet not restricted to CC True showering correction can be derived using MC without ZB overlay Alternative method (for both data and MC as a cross-check) - Templates for jet energy profiles (energy in DR annuli) determined in MC Spatial matching between calorimeter jet and particle jet One template for “particle-jet” energy profile (1) , one for “not particle-jet” profile (2) One template for offset energy density - Fit a (1) + b (2) + offset to measured jet energy profiles Results show good agreement data/MC  common energy dependence Rcone=0.5 Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

Jet Energy Scale: Results Correction Uncertainty E E Correction Results certified for |h|<3.6, pT >25 GeV 1-2% uncertainty in wide kinematic range for g+jet sample (potential few % change expected for other exclusive samples) h Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -

B.Andrieu Light Jet reconstruction and calibration in D∅ - Summary Cone Jet algorithm used by D0 in RunII improvement compared to RunI but a few problems or questions still open (not exhaustive list): CDF and D0 use a (slightly, but still...) different Cone Jet algorithm differences of D implementation w.r.t. RunII Cone recommendations usefulness of a pT cut on proto-jets before merging/splitting at high luminosity? even the RunII Cone algorithm is ICS up to NNLO only (G.P. Salam & G. Soyez, hep-ph/0704.0292)  Use SISCone (or even better: use kT!) Reconstruction and identification efficiency now much better under control Energy response is the main cause for jet (reconstruction) inefficiency and its improper simulation is the main cause for observed differences in jet efficiency between data and MC Consistent correction of reconstruction efficiency data/MC differences through JES and JER Much better understanding and correction of identification efficiency differences  systematics to the 0.5%-1% level (except in some specific regions) Jet Energy Scale correction for RunIIa completed Many detailed studies of small effects (often O(1%)) unprecedented level of precision O(1-2%) over a very large kinematic range (|h|<3.6, pT >25 GeV) However, the absence of a Monte Carlo reproducing data at a fundamental level prevents from extending easily all the knowledge gained on one particular sample to all data: cross checks have to be performed for each analysis using a sample different from the one used for JES derivation.  A good MC simulation helps!  If possible, apply energy calibration of objects before entering jet algorithm Workshop on Top Physics: From the TeVatron to the LHC , 18 October 2007 B.Andrieu Light Jet reconstruction and calibration in D∅ -