Measurements of jet rates with the anti-k T and SISCone algorithms at LEP with the OPAL detector

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1 Measurements of jet rates with the anti-k and SISCone algorithms at LEP with the OPAL detector Andrii Verbytskyi Rencontres de Moriond, QCD and High Energy Interactions, La huile, Italy 9-26 March 26 / 34

2 he LEP Accelerator OPAL he world most famous e + e collider running (LEP-I), 996-2(LEP-II). Now tunnel hosts LHC. Energy ranges 9 GeV(LEP-I) and 9 28 GeV(LEP-II). Host of four big experiments: OPAL, ALEPH, DELPHI, L3. 2 / 34

3 he OPAL Collaboration and Detector Electromagnetic calorimeters Hadron calorimeters and return yoke y θ ϕ Solenoid and z x pressure vessel Presampler Forward ime of flight detector detector Silicon tungsten luminometer Muon detectors Jet chamber Vertex chamber Microvertex detector Z chambers Omni-Purpose Apparatus at LEP Advanced multipurpose detector with almost 4π solid angle coverage. Collaboration of more than 3 people. Data available for re-analysis. 3 / 34

4 Jets at OPAL: motivation e + e γ /Z hadrons is perfect for studying QCD. New algorithms, never used before at LEP, can produce valuable results: SISCone ; anti-k 2. Compare new algorithms for e + e, validate them and their implementation. Expect to produce an input for α s determination with reduced uncertainties. Study hadronisation corrections. G. P. Salam and G. Soyez, A Practical Seedless Infrared-Safe Cone jet algorithm, JHEP 75 (27) 86 2 M. Cacciari et al., he Anti-k(t) jet clustering algorithm, JHEP 84 (28) 63 4 / 34

5 Similar studies elsewhere Jet rates: OPAL Coll., Determination of α s using jet rates at LEP with the OPAL detector, EPJC 45 (26) 547 dσ/de jet,b (pb/gev) k (x ) anti-k (x ) SIScone ZEUS 82 pb - NLO hadr Z Jet OPAL (9 GeV) Durham 2-jet 3-jet 4-jet 5-jet PYHIA HERWIG y cut adronisation correction -..9 Q 2 > 25 GeV 2-2 < η B jet <.5 cos γ h <.65 jet energy scale uncertainty k (+.5) anti-k SIScone hadronisation uncertainty Comparison of algorithms: ZEUS Coll., Inclusive-jet cross sections in NC DIS at HERA and a comparison of the k, anti-k and SISCone jet algorithms, PLB 69 (2) 27 5 / 34

6 Data and MC samples Full LEP data sample with 2 energies: s = GeV. MC samples with simulated detector level: e + e γ /Z hadrons KK2f 3 signal samples hadronised with Pythia6 and Herwig6. e + e leptons + hadrons grc4f 4 and KoralW 5 background samples hadronised with JESE7.4. For some plots the samples are merged: 9 9 GeV GeV GeV GeV 3 S. Jadach et al., he precision Monte Carlo event generator KK for two fermion final states in e + e collisions, CPC 3 (2) 26, also PRD 88 (23), J. Fujimoto et al., Grc4f v.: a four fermion event generator for e + e collisions, CPC (997) M. Skrzypek et al., Monte Carlo program KORALW-.2 for W pair production at LEP-2/NLC energies with Yennie-Frautschi-Suura exponentiation, CPC 94 (996) / 34

7 Event selection High energy multihadron event: 5+7 good tracks+clusters; significant energy deposit in the central region of calorimeter. Low e + e W + W background probability. Events 5 5 e) Selected Likelihood Output Selection of W + W qqqq events as in OPAL Coll., Measurement of the e + e W + W cross section and W decay branching fractions at LEP, EPJC 52 (27) / 34

8 Event reconstruction Low energy or poorly reconstructed tracks and calorimeter clusters removed; Calorimeter clusters and tracks combined with energy flow algorithm to prevent double counting; Running jet algorithms on the resulted list of objects. SiScone in spherical coordinates with ɛ =.75 and E tilde merging scheme, R =.3,.4,.5,.7,.9,.. e + e version of anti-k, R =.3,.4,.5,.7,.9,.. PxCone (ee) and Durham for comparison. 8 / 34

9 Check of the MC samples OPAL DP(prel.) ee-anti-k R=.7, s=9gev OPAL DP(prel.) ee-anti-k R=., s=6gev OPAL DP(prel.) SISCone R=.7, s=27gev.6 N jets =2.6 N jets =2.6 N jets = KK2f MC with Pythia6 hadronisation Good description of the data for various jet algorithms. 9 / 34

10 Check of the reconstruction Comparison to previous analyses with Durham and PxCone. OPAL DP(prel.) Durham, s=9gev OPAL DP(prel.) SISCone R=.7, s=9gev.6, Durham.5.4, Durham, OPAL.6.5.4, SISCone, PxCone, PxCone, M.A.D y Data from: JADE and OPAL Colls., QCD analyses and determinations of α s in e + e annihilation at energies between 35 GeVand 89 GeV, EPJC 7 (2) 9 cut E cut,gev Data from: "Determination of α s using jet rates at LEP", M.A. Donkers, PhD thesis. / 34

11 Anti-k with R =.7 OPAL DP(prel.) ee-anti-k R=.7, s=9gev OPAL DP(prel.) ee-anti-k R=.7, s=33gev OPAL DP(prel.) ee-anti-k R=.7, s=77gev.6 N jets =2.6 N jets =2.6 N jets = OPAL DP(prel.) ee-anti-k R=.7, s=97gev N jets =2 KK2f +Pythia6 describes the data well. KK2f +Herwig6(not shown) describes the data well. Both tuned by OPAL he uncertainties are statistical only. Full uncertainties are in the backup. / 34

12 SISCone with R =.7 OPAL DP(prel.) SISCone R=.7, s=9gev OPAL DP(prel.) SISCone R=.7, s=33gev OPAL DP(prel.) SISCone R=.7, s=77gev.6 N jets =2.6 N jets =2.6 N jets = OPAL DP(prel.) SISCone R=.7, s=97gev N jets =2 KK2f +Pythia6 describes the data well. KK2f +Herwig6(not shown) describes the data well. Both tuned by OPAL he uncertainties are statistical only. Full uncertainties are in the backup. 2 / 34

13 Scaling of the jet rates with the visible energy, R =.7 OPAL DP(prel.) Scaling with E, N =2 vis jets OPAL DP(prel.) Scaling with E, N =3 vis jets OPAL DP(prel.) Scaling with E, N =4 vis jets 9GeV anti-k R=.7 33GeV anti-k R=.7 77GeV anti-k R=.7 9GeV anti-k R=.7 33GeV anti-k R=.7 77GeV anti-k R=.7 9GeV anti-k R=.7 33GeV anti-k R=.7 77GeV anti-k R= GeV anti-k R= GeV anti-k R= GeV anti-k R= OPAL DP(prel.) Scaling with E, N =2 vis jets OPAL DP(prel.) Scaling with E, N =3 vis jets OPAL DP(prel.) Scaling with E, N =4 vis jets 9GeV SISC. R=.7 33GeV SISC. R=.7 77GeV SISC. R=.7 9GeV SISC. R=.7 33GeV SISC. R=.7 77GeV SISC. R=.7 9GeV SISC. R=.7 33GeV SISC. R=.7 77GeV SISC. R= GeV SISC. R= GeV SISC. R= GeV SISC. R= E vis is a sum of energies of all objects in the event. 3 / 34

14 Scaling of the jet rates with the visible energy, R =.3 OPAL DP(prel.) Scaling with E, N =2 vis jets OPAL DP(prel.) Scaling with E, N =3 vis jets OPAL DP(prel.) Scaling with E, N =4 vis jets 9GeV anti-k R=.3 33GeV anti-k R=.3 77GeV anti-k R=.3 9GeV anti-k R=.3 33GeV anti-k R=.3 77GeV anti-k R=.3 9GeV anti-k R=.3 33GeV anti-k R=.3 77GeV anti-k R= GeV anti-k R= GeV anti-k R= GeV anti-k R= OPAL DP(prel.) Scaling with E, N =2 vis jets OPAL DP(prel.) Scaling with E, N =3 vis jets OPAL DP(prel.) Scaling with E, N =4 vis jets 9GeV SISC. R=.3 33GeV SISC. R=.3 77GeV SISC. R=.3 9GeV SISC. R=.3 33GeV SISC. R=.3 77GeV SISC. R=.3 9GeV SISC. R=.3 33GeV SISC. R=.3 77GeV SISC. R= GeV SISC. R= GeV SISC. R= GeV SISC. R= E vis is a sum of energies of all objects in the event. 4 / 34

15 SISCone jet rates with different R parameter OPAL DP(prel.) Running of SiSCone alg. with R, s=9gev OPAL DP(prel.) Running of SiSCone alg. with R, s=9gev OPAL DP(prel.) Running of SiSCone alg. with R, s=27gev N jets =2 PxCone R=.7 N jets =2 SIScone R=.3 N jets =2 SIScone R=.5 N jets =2 SIScone R=.7 PxCone R=.7 SIScone R=.3 SIScone R=.5 SIScone R=.7 N jets =2 PxCone R=.7 N jets =2 SIScone R=.3 N jets =2 SIScone R=.5 N jets =2 SIScone R=.7 N jets =2 SIScone R=.9 SIScone R=.9 N jets =2 SIScone R=.9.6 N jets =2 SIScone R=..6 SIScone R=..6 N jets =2 SIScone R= OPAL DP(prel.) Running of SiSCone alg. with R, s=27gev PxCone R=.7 SIScone R=.3 SIScone R=.5 SIScone R=.7 SIScone R=.9 SIScone R=. Stable results for 2- and 3- jet rates. SISCone results close to PxCone / 34

16 Anti-k jet rates with different R parameter OPAL DP(prel.) Running of ee-anti-k alg. with R, s=9gev OPAL DP(prel.) Running of ee-anti-k alg. with R, s=27gev OPAL DP(prel.) Running of ee-anti-k alg. with R, s=9gev N jets =2 anti-k R=.3 N jets =2 anti-k N jets =2 anti-k N jets =2 anti-k R=.5 R=.7 R=.9 N jets =2 anti-k R=.3 N jets =2 anti-k N jets =2 anti-k N jets =2 anti-k R=.5 R=.7 R=.9 anti-k R=.3 anti-k anti-k anti-k R=.5 R=.7 R=.9.6 N jets =2 anti-k R=..6 N jets =2 anti-k R=..6 anti-k R= OPAL DP(prel.) Running of ee-anti-k alg. with R, s=27gev.6.4 N jets =2 anti-k R=.3 N jets =2 anti-k N jets =2 anti-k N jets =2 anti-k N jets =2 anti-k R=.5 R=.7 R=.9 R=. Similar patterns to SiSCone / 34

17 SISCone jet rates dependence on R with E cut = 6 GeV OPAL DP(prel.) N-jet events E>6GeV with SiSCone alg., s=9gev OPAL DP(prel.) N-jet events E>6GeV with SiSCone alg., s=33gev OPAL DP(prel.) N-jet events E>6GeV with SiSCone alg., s=77gev.4 N jets =2 E>6.GeV.2 E>6.GeV.4 N jets =2 E>6.GeV.2 E>6.GeV.4 N jets =2 E>6.GeV.2 E>6.GeV E>6.GeV E>6.GeV E>6.GeV R OPAL DP(prel.) N-jet events E>6GeV with SiSCone alg., s=97gev R R.4 N jets =2 E>6.GeV E>6.GeV E>6.GeV Monotonic dependence on R. he choice can be done in a wide range R 7 / 34

18 Anti-k jet rates dependence on R with E cut = 6 GeV OPAL DP(prel.) N-jet events E>6GeV with ee-anti-k alg., s=9gev OPAL DP(prel.) N-jet events E>6GeV with ee-anti-k alg., s=33gev OPAL DP(prel.) N-jet events E>6GeV with ee-anti-k alg., s=77gev.4 N jets =2 E>6.GeV.2 E>6.GeV.4 N jets =2 E>6.GeV.2 E>6.GeV.4 N jets =2 E>6.GeV.2 E>6.GeV E>6.GeV E>6.GeV E>6.GeV R R R OPAL DP(prel.) N-jet events E>6GeV with ee-anti-k alg., s=97gev.4 N jets =2 E>6.GeV E>6.GeV E>6.GeV Monotonic dependence on R. he choice can be done in a wide range R 8 / 34

19 Predictions with Pythia8, Herwig++2.7 and Sherpa2.2, SISCone with R =.7 Many generators were tuned to LEP data. How do these describe the data? We consider: Pythia8 with LEP-I tuning; Default Herwig++2.7; Default SHERPA2.2 (AHADIC++). 9 / 34

20 Predictions with Pythia8, Herwig++2.7 and Sherpa2.2, SISCone with R =.7 OPAL DP(prel.) SISCone R=.7, s=9gev OPAL DP(prel.) SISCone R=.7, s=33gev OPAL DP(prel.) SISCone R=.7, s=77gev N =2 jets N jets =2 herwig++ N =2 jets N jets =2 herwig++ N =2 jets N jets =2 herwig++ herwig++ herwig++ herwig++.6 herwig++ N jets =2 pythia8.6 herwig++ N jets =2 pythia8.6 herwig++ N jets =2 pythia8 pythia8 pythia8 pythia8.4 pythia8.4 pythia8.4 pythia8 N jets =2 sherpa N jets =2 sherpa N jets =2 sherpa.2 sherpa sherpa.2 sherpa sherpa.2 sherpa sherpa OPAL DP(prel.) SISCone R=.7, s=97gev N =2 jets N jets =2 herwig++ herwig++ herwig++ N jets =2 pythia8 pythia8 Good description of data. he best one is for s = 9 GeV..4.2 pythia8 N jets =2 sherpa sherpa sherpa he solid lines are data, the dashed and doted are MC. he uncertainties are statistical only. Full uncertainties are in the backup / 34

21 Predictions with Pythia8, Herwig++2.7 and Sherpa2.2, anti-k with R =.7 OPAL DP(prel.) ee-anti-k R=.7, s=9gev OPAL DP(prel.) ee-anti-k R=.7, s=33gev OPAL DP(prel.) ee-anti-k R=.7, s=77gev N =2 jets N jets =2 herwig++ N =2 jets N jets =2 herwig++ N =2 jets N jets =2 herwig++ herwig++ herwig++ herwig++.6 herwig++ N jets =2 pythia8.6 herwig++ N jets =2 pythia8.6 herwig++ N jets =2 pythia8 pythia8 pythia8 pythia8.4 pythia8.4 pythia8.4 pythia8 N jets =2 sherpa N jets =2 sherpa N jets =2 sherpa.2 sherpa sherpa.2 sherpa sherpa.2 sherpa sherpa OPAL DP(prel.) ee-anti-k R=.7, s=97gev N =2 jets N jets =2 herwig++ herwig++ herwig++ N jets =2 pythia8 pythia8 Good description of data. he best one is for s = 9 GeV..4.2 pythia8 N jets =2 sherpa sherpa sherpa he solid lines are data, the dashed and doted are MC. he uncertainties are statistical only. Full uncertainties are in the backup / 34

22 Hadronization corrections with Pythia8, Herwig++2.7 and Sherpa2.2 How large and stable are the hadronisation corrections? We consider: Pythia8 with LEP-I tuning; Default Herwig++2.7; Default SHERPA2.2 (AHADIC++). 22 / 34

23 Hadronisation correction, anti-k with R =.7 OPAL DP(prel.) ee-anti-k R=.7, s=9gev OPAL DP(prel.) ee-anti-k R=.7, s=33gev OPAL DP(prel.) ee-anti-k R=.7, s=77gev Hadr. correction N jets =2 herwig++ herwig++ herwig++ Hadr. correction N jets =2 herwig++ herwig++ herwig++ Hadr. correction N jets =2 herwig++ herwig++ herwig++ N jets =2 pythia8 N jets =2 pythia8 N jets =2 pythia8.4 pythia8.4 pythia8.4 pythia8 pythia8 pythia8 pythia8.2 N jets =2 sherpa sherpa.2 N jets =2 sherpa sherpa.2 N jets =2 sherpa sherpa sherpa sherpa sherpa Hadr. correction OPAL DP(prel.) ee-anti-k R=.7, s=97gev N jets =2 herwig++ herwig++ herwig++ N jets =2 pythia8 pythia8 pythia8 N jets =2 sherpa sherpa Corrections: Larger for 3 and 4-jet events. Larger for lower energies. Smaller for tuned MC. sherpa he solid lines are old MC, the dashed and doted are new MC. 23 / 34

24 Hadronisation correction, SISCone with R =.7 OPAL DP(prel.) SISCone R=.7, s=9gev OPAL DP(prel.) SISCone R=.7, s=33gev OPAL DP(prel.) SISCone R=.7, s=77gev Hadr. correction N jets =2 herwig++ herwig++ herwig++ Hadr. correction N jets =2 herwig++ herwig++ herwig++ Hadr. correction N jets =2 herwig++ herwig++ herwig++ N jets =2 pythia8 N jets =2 pythia8 N jets =2 pythia8.4 pythia8.4 pythia8.4 pythia8 pythia8 pythia8 pythia8.2 N jets =2 sherpa.2 N jets =2 sherpa.2 N jets =2 sherpa sherpa sherpa sherpa sherpa sherpa sherpa Hadr. correction OPAL DP(prel.) SISCone R=.7, s=97gev N jets =2 herwig++ herwig++ herwig++ N jets =2 pythia8 pythia8 pythia8 N jets =2 sherpa sherpa sherpa Corrections: Larger for 3 and 4-jet events. Larger for lower energies. Smaller for tuned MC. Smaller than for anti-k he solid lines are old MC, the dashed and doted are new MC. 24 / 34

25 Conclusions Presented measurements of distributions of jet rate fractions with anti-k and SISCone algorithms at LEP. he old and new (Pythia8, SHERPA2.2, Herwig++2.7) Monte Carlo describes the data well. Studied hadronisation corrections to the presented quantities with different hadronisation models. he mesurements can be used for the precise α s determination. 25 / 34

26 Backup slides 26 / 34

27 Access policy he OPAL data is analysed in Data Preservation mode. It implies some specific features: Absence of regular collaboration structure: groups, spokesperson, administration. Absence of dedicated manpower, support and infrastructure. Still, if the data is available it can be used! 27 / 34

28 Systematics he systematic uncertainties are estimated with the strategy used in the previous analyses. In brief the following sources were considered: s reconstruction; Selection procedure; Hadronisation model; Background modelling. 28 / 34

29 Jet energy scale.5.4 (a) OPAL.3 Jet energy scale cosθ data/mc data/mc (c) Jet energy scale linearity data/mc cosθ Z 2-jet Z 3-jet (b) Jet energy resolution Z/γ high energy Corrected Corrected Corrected OPAL Coll., Measurement of the mass and width of the W boson, EPJC 45 (26) / 34

30 Generators reminder KK2f : Ultimate precision for e + e ff ; Used version 4.3, CPC 3 (2) 26; Last version 4.22, PRD 88 (23) no., 422. grc4f : Background from e + e 4fermions; akes into account all contributions. KoralW : Monte Carlo for e + e ff ; See also AUOLA, PHOOS and KoralZ. 3 / 34

31 Numerical results for some energies First uncertainty is statistic the second is systematic 3 / 34

32 Results for s = 9 GeV, anti-k first, SISCone second; R =.7 E cut, GeV N jets = 2 N jets = 3 N jets = E cut, GeV N jets = 2 N jets = 3 N jets = / 34

33 Results for s = 96 GeV, anti-k first, SISCone second; R =.7 E cut, GeV N jets = 2 N jets = 3 N jets = E cut, GeV N jets = 2 N jets = 3 N jets = / 34

34 Results for s = 27 GeV, anti-k first, SISCone second; R =.7 E cut, GeV N jets = 2 N jets = 3 N jets = E cut, GeV N jets = 2 N jets = 3 N jets = / 34

arxiv: v1 [hep-ex] 21 Aug 2011

arxiv: v1 [hep-ex] 21 Aug 2011 arxiv:18.155v1 [hep-ex] 1 Aug 011 Early Searches with Jets with the ATLAS Detector at the LHC University of Chicago, Enrico Fermi Institute E-mail: georgios.choudalakis@cern.ch We summarize the analysis