Calibration for jets Reminder on the D detector

- Calibration for jets · Reminder on the DØ detector · Jet Identification and Reconstruction · Jet Energy Scale: · results from Run 1 · b-jet calibration 11/26/2020 1

Run II Detector 11/26/2020 2

- Calorimeter · Fine segmentation: · semi-projective towers in 0. 1 x 0. 1 · 4 em layers: 2, 2, 7, 10 X 0 · shower-max (EM 3): 0. 05 x 0. 05 · 4/5 hadronic (FH + CH) · hermetic with full coverage u | | < 4. 2 ( 2 o) u int > 7. 2 (total) · Uranium absorber (Cu (CC) or Steel (EC) for coarse hadronic) u compensating e/ 1 to be studied with shorter shaping Beam Tests of the D 0 Uranium Liquid Argon Calorimeter. NIM A 324, 53 (1993) NIM A 338 185 (1994) 11/26/2020 from test beam data e: E/E = 15% / E + 0. 3% : E/E = 45% / E + 4% 3

SCA non-linearity · functional form of SCA non-linearity correction function · correction important at low energies â electronic noise translates into higher energy â jet become more narrow 0. 25 ADC count/Me. V 0 ~Energy/Ge. V 11/26/2020 250 Me. V for energies > 200 Me. V non -linearity introduces an offset of ~250 Me. V for the gain 8 4 measurements 1 Ge. V Gain 8 Gain 1 0 10 20 30 40 50 Ge. V 4

Central Jet Triggers · L 2 jet Efficiency vs jet p. T CJT(1, 3) CJT(1, 5) CJT(1, 7) CJT(1, 10) Cluster 3 x 3 or 5 x 5 trigger towers around L 1 seed towers u · L 3 jet Simple cone or tower NN algo’s 0. 1 x 0. 1 towers u 3 single jet (tower) triggers: u JT_LO L 1: 5 Ge. V, L 3: 10 Ge. V u JT_HI L 1: 10 Ge. V, L 3: 15 Ge. V u CJT 40: L 1: 40 Ge. V u Efficiency u standard jet selection, offline p. T > 8 Ge. V u very sharp turn on u L 1 Trigger efficiency CJT(1, x) · L 1 single jet efficiencies L 1 Trigger efficiency CJT(2, x) ask for one or two hadronic trigger towers (0. 2 x 0. 2) above threshold u use -trigger as unbiased reference to measure turn-on u ask for one and only one reconstructed jet in | |<0. 7 u L 1 hadronic response about 40% low for current data set u 11/26/2020 5

NADA: noise reduction · NADA = New Anomalous Deposit Algorithm · identify isolated energy deposits in the calorimeter = “Hot Cells” u Source: electronics, Ur noise, beam splash, cosmics etc Improve object resolution and ETmiss · Run 1: AIDA Only examine neighbors in the same tower for Ecell > 10 Ge. V u 99% efficient, BUT 5 -10% misidentification rate u examine all cells with > 1 Ge. V remove cells < -1 Ge. V & > 500 Ge. V u ET < 5 Ge. V removed if no neighbor with E > 100 Me. V u ET < 500 Ge. V removed if no neighbor with E > 2% Ecell high efficiency (90%) and low misidentification u ET > 1 Ge. V : ~0. 5% u ET > 10 Ge. V : ~0% on average about 0. 8 cells / event u 11/26/2020 ETthresold ETneighbour> 100 Me. V or 0. 02 Ecell 6

Jet Finding · Calorimeter jet (cone) jet is a collection of energy deposits with a given cone R: u cone direction maximizes the total ET of the jet u various clustering algorithms u ¢correct for finite energy resolution ¢subtract underlying event ¢add out of cone energy · Particle jet a spread of particles running roughly in the same direction as the parton after hadronization u 11/26/2020 7

Jet Algorithms: Cone · Run 1 Legacy Cone draw a cone of fixed size around a seed u compute jet axis from ET-weighted mean and jet ET from ET’s u draw a new cone around the new jet axis and recalculate axis and new ET u iterate until stable ¢algorithm is sensitive to soft radiation (split & merge) u · Improved Run 2 cone use 4 -vectors instead of ET u additional midpoint seeds between pairs of close jets u split/merge after stable proto-jets found ¢algorithm is infrared safe u 11/26/2020 8

Jet Algorithms: k. T For each object and pair of objects: order all dii and dij: If dmin=dij Collinear merge particles (if R<<1 ) Soft Resolution parameter (D=1) · theoretically favored, no split-merge · to reduce computation time, start with 0. 2 x 0. 2 pre-clusters x-section measurement differ from cone-jet If dmin=dii jet (JETRAD) DØ Subjet multiplicity of gluon and quark jets reconstructed using the k. T algorithm in pbarp collisions Phys. Rev. D 65 052008 (2002) hep-ex/0108054 The inclusive jet cross section in pbarp collisions at sqrt(s)=1. 8 Te. V using the k. T algorithm Phys. Lett. B {525}, 211 (2002) hep-ex/0109041 11/26/2020 9

Hadronization effects? • particle jets are more (less) energetic than parton jets with k. T (cone) ® k. T collects more energy ® cone looses energy ® k. T jets are 7 (3)% more energetic at 60 (200) Ge. V than cone jets: • consistent with HERWIG at high p. T, at 2 at low p. T applying correction to cone-jets improves agreement between the 2 algorithms 11/26/2020 10

Jet Algorithms: Cell. NN & Flow · Cell Nearest Neighbor u layer-by-layer clustering starting with EM 3 u each local maximum starts a layer-cluster then add in neighbors u energy sharing according to transverse shape parameterization u angular matching of floor clusters search for minima in longitudinal energy distribution to separate EM and hadronic showers u · Energy Flow algorithm use tracking information to better characterize the contributions from charged particles u u in development 11/26/2020 11

Jet Selection DØ Run 2 Preliminary · central jets (Run 2 cone, R=0. 7) · event quality cuts number of jets 1 u Etotal in the calorimeter 2 Te. V u missing ET 70% of leading jet p. T u Zvtx < 50 cm u EM F CHF · leading Jet Cuts Jet p. T > 8 Ge. V (offline cut) u 0. 05 EMF 0. 95 u CHF 0. 4 (0. 25 tight) u Hot. F 10 (5 tight) (Hot. F = ET 1 st cell / ET 2 nd cell ) u n 90 > 1 (number of towers that contain 90% of jet ET) u · efficiencies from MC loose: ~100% u ~Flat in u tight: ~ 98% 11/26/2020 Hot F n 90 Da — MC ta · Non-linearity of SCA included in MC 12

Jet Energy Scale jet · correct Jet Energy to the particle level · Eoffset energy offset from underlying event, pile-up, noise determined from Min. Bias Events · Rcalorimeter response using -jet events: Missing ET Projection Fraction Method · Rshower energy contained in jet corrections from MC - energy in cones around the jet axis depending on jet algorithm! Determination of the Absolute Jet Energy Scale in the D 0 Calorimeters. NIM A 424, 352 (1999), hep-ex/9805009 11/26/2020 13

Run I: Offset corrections · subtract contributions not associated to the high pt interaction: · Ur noise, pile-up, multiple interaction, underlying even · measured as ET densities D, to be multiplied by the area of a jet in E EOFF= EUE + NZB EUE +Enoise+Epile-up · measurement of the ET density D in zero bias event · measurement of DUE from minimum bias events DUE=DMB-DZBno HC 11/26/2020 14

Run I: Offset corrections Ur noise, pile-up, multiple events underlying event contribution ICR · measured for different luminosities · depends on s and process · dominant error from occupancy dependence · associated to a single event independent of luminosity 11/26/2020 15

Run I: response correction · using -jet events · ideal calorimeter : · jet response (with calibrated ): · Ejetmeas: dependent on energy response and resolution, threshold effects and smearing · better: E = ET cosh jet 11/26/2020 16

Run I: jet response · comparison of jet response in different cryostat regions - CC | |<0. 7 - ICR 0. 7<| |<1. 8 - EC 1. 8 <| |<2. 5 ® effect of finite jet resolution at E = 10 Ge. V ® lowest response in ICR: int < 6 11/26/2020 17

Run I: EC/CC correction · independent of E as EC/CC similar in construction · derived from overlap region of CC and EC response at 60<E <180 Ge. V · Fncry/Fscry=0. 997 0. 003 · EC response 2% below CC · compared to the ratio of a fit to the 2 response functions 11/26/2020 18

Run I: ICR correction · inhomogeneous detector material: correction as function of and ET high ET: jet-jet events low ET: -jet events · or leading jet required to be central (| |< 0. 5) · fit of response as Rjet = + b ln ET+ b ln (cosh ) · correction derived from difference between measurement and the expectation for an ideal detector, extrapolated from fit at | |<0. 5 and 2 < | |<2. 5 11/26/2020 19

Run I: low ET bias · Etjet > 8 Ge. V · jet resolution ~50% migration of low ET jets fluctuating below Etmin are not reconstructed bias of the response towards higher values • as response determined from Etmiss and , bias correction determined from: 11/26/2020 20

Run I: Response function · fit of the measured response function Rjet(E)=a+b ln E+c (ln E)2 logarithmic terms justified by non compensation at low E fit of CC and EC measurement for ET>30 Ge. V at highest energy prediction from MC after tuning response on data in measured region error band derived taking into account correlations 11/26/2020 21

Run I: Showering correction · corrects for out-of- 1% cone energy belonging to the jet · scales reconstructed jet to particle level: S=Ejet/(Ejet+Esho. MC) 4% 10% · parameterizations for different cone sizes · errors at low energy: offset subtraction; at high energy: stat 2. 5% 5% 10% 11/26/2020 · shower correction depend on jet profiles, but not on s 22

Run II: +jet / Z+jet /Z+jet QCD (udsg) signal: 152 M evts bkgd: 47. 1 M evts signal: 64. 8 k evts bkgd: 650 evts QCD (cbt) W+jet, Z+X, • +jet: Run I method – jet calibration possible up to 250 Ge. V • Z+jet: lower statistics, but clean sample, useful at low energies, x-check! 11/26/2020 23

b-jet calibration · naïve reconstruction of Z-mass shows a lower mass for selected b-jets than light quark jets. peak: 82. 6 energy losses from semi-leptonic b decays ( , ) wider b-jets (due to the large b-mass) 11/26/2020 peak: 86. 8 24

Z bb vs + b-jet : Z bb: · high statistics, allows for a tight b-jet selection (btagging). · expected number of tagged events: 1. 2 M but: sensitive fractional imbalance I= (p. T( ) - ET(jet))/ p. T( ) · systematics closer to physics processes (H or Top) at high p. T · resonance mass independent of multiple interactions. · but: signal/noise~10 -3 requires special trigger (Silicon Track Trigger – operational end 2002) 11/26/2020 25

CDF Run 1: Z bb selection · about 120 000 Z bb events produced in Run 1 · expected to be observed ~ 50 -100 · Trigger: central muon (p. T> 7. 5 Ge. V) 5. 5 M evts · Offline: request 2 tagged (0. 7 cone) jets 5479 evts · QCD background rejection based on event topology: > Z is produced by a time-like q-qbar anihilation, > QCD produced color flow between initial and final partons > Z is expected to have soft radiation between the jets > background will also have strong radiation between IS and FS partons. http: //www-cdf. fnal. gov/physics/ewk/zbb_new. html 11/26/2020 26

CDF Run 1: 3 ET and 12 Use 2 kinematic variables to discriminate: · 3 ET : sum of ET of the clusters outside the 2 leading jets · 12 : azimuthal angle difference between the 2 jets cuts derived: 3 ET < 10 Ge. V, 12>3 rad 11/26/2020 27

CDF Run 1: Z bb Signal · after cuts: S/N=1/6 at the Z mass peak · select/antiselect w. r. t. the 2 variables to determine the tagging probability · 3. 2 exces 11/26/2020 28

CDF Run 1: Likelihood fit Results: MZ=90. 0 2. 4 Ge. V Z = 9. 4 3. 5 Ge. V NZ=91 30(stat) 19(sys. ) Pythia: expect 124 14 11/26/2020 29

First Run 2 QCD Physics Inclusive jet p. T spectrum at 1. 96 Te. V Dijet mass spectrum at 1. 96 Te. V Ldt = 1. 9 ± 0. 2 pb-1 Only statistical errors · not fully corrected distributions: Highest 3 -jet event ETjet 1 : 310 Ge. V Etjet 2 : 240 Ge. V ETjet 3 : 110 Ge. V Etmiss : 8 Ge. V preliminary correction for jet energy scale (but no unsmearing or resolution effects) u u 30 -50% systematic error in cross-section u no trigger selection efficiency corrections 11/26/2020 30