jet calibration in cms experience lot of questions and few answers a work in progress n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Jet Calibration in CMS: experience… lot of questions… and few answers… …a work in progress… PowerPoint Presentation
Download Presentation
Jet Calibration in CMS: experience… lot of questions… and few answers… …a work in progress…

Loading in 2 Seconds...

play fullscreen
1 / 35

Jet Calibration in CMS: experience… lot of questions… and few answers… …a work in progress… - PowerPoint PPT Presentation


  • 112 Views
  • Uploaded on

Jet Calibration in CMS: experience… lot of questions… and few answers… …a work in progress…. Attilio Santocchia INFN Perugia Frascati – 2nd Workshop sui Monte Carlo, la Fisica e le Simulazioni a LHC 22.05.2006. Motivations.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

Jet Calibration in CMS: experience… lot of questions… and few answers… …a work in progress…


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
    Presentation Transcript
    1. Jet Calibration in CMS: experience… lot of questions… and few answers……a work in progress… Attilio Santocchia INFN Perugia Frascati – 2nd Workshop sui Monte Carlo, la Fisica e le Simulazioni a LHC 22.05.2006

    2. Motivations • ttH channel very challenging: we have to optimize all the tools we need to use… • Which is the best Jet Algorithm to use for such a complex multi-jet final state rich with b-jets? • I used to study the fully hadronic decay  8 jets (4 light + 4 b jets) • Honestly? It’s a mess! And jets are the most important object I had to understand… Attilio Santocchia

    3. Chosen Algorithm & Data Sample • 5 Different Iterative Cone Algorithm +3 KT inclusive • ICA DeltaR=0.30, 0.35, 0.40, 0.45 and 0.50 • KT  r=0.35, 0.40 and 0.45 • COMPHEP+PYTHIA 6.215+CTEQ4L • ttH120 (200K) • ttjj (1000K) 1.6M events • ttbb (400K) • ALPGEN2+PYTHIA 6.325+CTEQ5L • tt1j exclusive (1000K) • tt2j exclusive (560K) • tt3j exclusive (68K) • tt4j inclusive (97K) • 1.725M events Attilio Santocchia

    4. Calibration • To do physics we need to go back to parton energy • 2 different aspect to be considered: • Detector Effects  PARTICLElevel correction • Physics Model Effects  PARTONlevel correction • I tried to factorize the 2 effects: • 2 different set of Calibration functions are calculate for correction to JetMC Energy and to Parton Energy • These functions are then applied to the raw jet energy in cascade to recover the initial Parton Energy ET(raw)  ET(MCjet)  ET(parton) Attilio Santocchia

    5. Raw Jet • Standard Jets from CMS simul+reco software • No Calibration • Calorimeter Noise Cut are: ET > 0.5 GeV and E > 0.8 GeV • Raw Jet ET > 5 GeV • All Jets are considered massless Attilio Santocchia

    6. MC Jets • Built from stable generator particles and ET > 0.5 (1) GeV • Muons and Neutrinos are included in the calculation • Muons and Neutrinos are excluded in the calculation • If you keep all particles  Jet is the same (difference in ET below 5%) but CPU time needed for ICA increases of a factor 2-3 • Jet is kept if ET(jet) > 10 (20) GeV • We need to b-tag MC jets to build flavored dependant calibration: • Each particle belonging to a jet is classified as daughter of a b-flavored unstable particle or not • Define b-ratio as sum of energy from particles from b divided jet energy • If b-ratio > 0.20 then jet is tagged as a MC b-jet Attilio Santocchia

    7. Jet Costituents • After ICA application, I can list all the particles used to form the Jet (Jet Components) • Each Particle in the Jet can be associated either to the partons from the hard scattering or nothing • Most of the time 100% of the particles within a jet comes from the same original parton… • But sometimes there is a mixing… Attilio Santocchia

    8. Particles  String  Partons Attilio Santocchia

    9. Jet Classification - Example JET= 4 jet= 4 EtJ=33.731 EtaJ=-1.211 PhiJ=-0.899 EJ=61.810 n= 0 Npar=192 Strg=191 Part= 4 EtP= 6.883 EtaP=-1.234 PhiP=-0.864 EP=12.832 dR= 0.042 n= 1 Npar=193 Strg=191 Part= 4 EtP=13.563 EtaP=-1.249 PhiP=-0.921 EP=25.595 dR= 0.044 n= 2 Npar=371 Strg=191 Part= 4 EtP= 1.528 EtaP=-1.243 PhiP=-0.918 EP= 2.873 dR= 0.038 n= 3 Npar=373 Strg=191 Part= 4 EtP= 1.604 EtaP=-0.925 PhiP=-0.825 EP= 2.391 dR= 0.295 n= 4 Npar=375 Strg=191 Part= 4 EtP= 4.728 EtaP=-1.204 PhiP=-0.892 EP= 8.606 dR= 0.009 n= 5 Npar=376 Strg=191 Part= 4 EtP= 1.334 EtaP=-1.417 PhiP=-1.046 EP= 2.916 dR= 0.254 n= 6 Npar=507 Strg=191 Part= 4 EtP= 2.061 EtaP=-1.067 PhiP=-0.838 EP= 3.351 dR= 0.155 n= 7 Npar=508 Strg=191 Part= 4 EtP= 2.061 EtaP=-1.027 PhiP=-0.890 EP= 3.246 dR= 0.184 JET= 5 jet= 5 EtJ=25.726 EtaJ= 1.639 PhiJ= 2.254 ThetaJ= 0.384 EJ=68.962 n= 0 Npar=238 Strg= 91 Part= 0 EtP= 3.739 EtaP= 1.902 PhiP= 2.357 EP=12.810 dR= 0.283 n= 1 Npar=258 Strg=110 Part= 3 EtP= 3.686 EtaP= 1.487 PhiP= 2.340 EP= 8.585 dR= 0.174 n= 2 Npar=261 Strg=110 Part= 3 EtP= 5.652 EtaP= 1.518 PhiP= 2.170 EP=13.564 dR= 0.147 n= 3 Npar=262 Strg=110 Part= 3 EtP= 1.627 EtaP= 1.466 PhiP= 2.034 EP= 3.716 dR= 0.279 n= 4 Npar=422 Strg= 91 Part= 0 EtP= 1.370 EtaP= 1.977 PhiP= 2.286 EP= 5.042 dR= 0.340 n= 5 Npar=438 Strg=110 Part= 3 EtP= 3.864 EtaP= 1.560 PhiP= 2.246 EP= 9.615 dR= 0.079 n= 6 Npar=439 Strg=110 Part= 3 EtP= 4.426 EtaP= 1.622 PhiP= 2.279 EP=11.641 dR= 0.031 n= 7 Npar=440 Strg=110 Part= 3 EtP= 1.457 EtaP= 1.665 PhiP= 2.249 EP= 3.990 dR= 0.027 • First Jet is PURE: all the particles comes from the same string ; the associated parton code is 4 (a W+) • Second Jet is a mixing of t_bar (code 3) and something else (code 0) • How can I treat this kind of situation? Attilio Santocchia

    10. Jet Classification – An Event • ttH fully hadronic  CompHEP • Iterative Cone Algo (Cone Size 0.4) • ET(particles isthep=1)>1GeV Index 0 Jet 3 Et=164.511 Eta=-2.067 Phi=-2.742 RatioE=0.800 Quark Higgs Index 1 Jet 0 Et=147.849 Eta=-2.614 Phi= 0.030 RatioE=1.000 Quark top Index 2 Jet 2 Et=105.950 Eta=-2.131 Phi=-0.131 RatioE=0.742 Quark W+ Index 3 Jet 1 Et=102.842 Eta=-0.176 Phi= 2.456 RatioE=0.981 Quark top_bar Index 4 Jet 4 Et= 33.731 Eta=-1.211 Phi=-0.899 RatioE=1.000 Quark W+ Index 5 Jet 5 Et= 25.726 Eta= 1.639 Phi= 2.254 RatioE=0.741 Quark top_bar Index 6 Jet 7 Et= 11.329 Eta=-1.117 Phi= 1.326 RatioE=1.000 Quark Higgs Index 7 Jet 8 Et= 8.020 Eta=-2.585 Phi=-2.695 RatioE=1.000 Quark Higgs Index 8 Jet 9 Et= 6.469 Eta= 0.227 Phi= 2.937 RatioE=1.000 Quark W- Index 9 Jet 10 Et= 4.530 Eta=-0.108 Phi=-3.023 RatioE=1.000 Quark W- Index 10 Jet 6 Et= 4.008 Eta=-2.951 Phi= 0.251 RatioE=1.000 Quark top Index 11 Jet 12 Et= 3.490 Eta=-1.442 Phi= 0.667 RatioE=1.000 Quark Higgs Index 12 Jet 11 Et= 2.566 Eta= 0.574 Phi=-2.994 RatioE=1.000 Quark W- Index 13 Jet 13 Et= 1.797 Eta=-2.101 Phi= 3.061 RatioE=1.000 Quark Higgs Index 14 Jet 14 Et= 1.566 Eta=-3.743 Phi=-0.466 RatioE=1.000 Quark top Index 15 Jet 15 Et= 1.548 Eta=-2.106 Phi=-2.194 RatioE=1.000 Quark Higgs Index 16 Jet 16 Et= 1.494 Eta=-0.598 Phi= 1.332 RatioE=1.000 Quark Higgs Index 17 Jet 17 Et= 1.325 Eta=-1.567 Phi=-0.483 RatioE=1.000 Quark W+ Index 18 Jet 18 Et= 1.320 Eta= 1.166 Phi= 2.320 RatioE=1.000 Quark top_bar Index 19 Jet 19 Et= 1.297 Eta= 2.246 Phi= 2.674 RatioE=1.000 Quark no part Index 20 Jet 20 Et= 1.263 Eta=-2.534 Phi=-0.745 RatioE=1.000 Quark top Index 21 Jet 21 Et= 1.003 Eta=-0.934 Phi=-2.936 RatioE=1.000 Quark no part • In real life, low ET Jets are objects difficult to detect • Only jets with ET>10(20)GeV will be used in the next slides Attilio Santocchia

    11. How many MC jets? tt1j – All Particles – ET>10GeV • <Njet> distribution for different jet algo • Black is ICA • Red is KT • In the table <Njet>: • red is maximum <Njet> • 1st number is AllParticle – 2nd is noMuNu Iterative Cone • If <Njet> increase when DR increase  I get more jets because of ET(jet)>10GeV • If <Njet> decrease when DR increase  overlapping KT • If <Njet> increase when r increase  Again depends on ET(jet)>10GeV • If <Njet> decrease when r increase  ??? Attilio Santocchia

    12. Jet Formation  Overlapping tt1j – All Particles – ET>10GeV Black is ICA – Red is KT Fractio of jets with jetRatio > 0.80 Fractio of jets with jetRatio > 0.90 97.3% ÷ 97.9% Attilio Santocchia

    13. bJets and cJets Classification • Look for each particle belonging to the jet… • Define b-Ratio and c-Ratio • ratioParticle = E(particle)/E(jet) • If(decayFromBquark) ratioForBjet+=ratioParticle • elseIf(decayFromCquark) ratioForCjet+=ratioParticle • A jet is a bJet if: • (ratioForBjet>ratioForCjet) && (ratioForBjet>CutBjetRatio) • A jet is a cJet if: • (ratioForCjet>ratioForBjet) && (ratioForCjet>CutCjetRatio) • What are CutBjetRatio And CutBjetRatio? • See next slides… Attilio Santocchia

    14. b-ratio Distribution b-ratio>0.2 b-ratio>0.2 tt1j Sample tt2j: ICA 0.300.50 – KT r=0.350.45 ICA 0.40: sample tt1j… tt4j Percentuale di bJet taggabili! Sono meno di quelli che mi aspetto… (in percentuale!) I bJet troppo soffici li perdo… E il gluon splitting è trascurabile Attilio Santocchia

    15. c-ratio Distribution c-ratio>0.2 c-ratio>0.2 • Same criteria  a jet is classified as a cJet when more than 20% of its energy comes from c haddrons (and there are no b in the decay chain…) • tt1j ~ 11.2% are cJets • tt2j ~ 10.4% are cJets • tt3j ~ 9.8% are cJets • tt4j ~ 8.8% are cJets Attilio Santocchia

    16. Minimum Distance (b and c partons) Fractio of jets nearer than 0.2 from a b(c) parton in the hard scattering Jet Algo is ICA and DR=0.4 Attilio Santocchia

    17. b Minimum Distance VS bRatio • Example for tt2j and ICA cone 0.4 • Here we can evaluate the gluon splitting • bJets with bRatio>0.5 and minDistB>0.5 are not coming from a b parton in the hard scattering  6.2% • bJets with bRatio>0.2 and minDistB>0.8 are not coming from a b parton in the hard scattering  4.0% Attilio Santocchia

    18. Calibration Raw Jet MC Jet • Build jets from Full Reco (FR) • Build jets from Generator (MC) particles list • Match FR-MC jets minimizing SDRFR-MC; keep jets where DRFR-MC< 0.3 • Fill 50h x 200ET histos with ET(FR)/ET(MC) for b-jets and not-b-jets in the rangeabs(eta)<5 and ET<600 GeV • Gaussian Fit if Nent>30 • For each Eta Value, fit the ET Ratio as a function of ET(raw) using the function Attilio Santocchia

    19. Calibration MC Jet Parton • Build jets from Generator (MC) particles list • Match jets-Parton minimizing SDRMC-Parton; keep jets where DRMC-Parton< 0.15 • Fill 50h x 200ET histos with ET(MC)/ET(Parton) for b-jets and not-b-jets in the rangeabs(eta)<5 and ET<600 GeV • Gaussian Fit if Nent>30 • For each Eta Value, fit the ET Ratio as a function of ET(MC) using the function Attilio Santocchia

    20. Single ET Ratio Distribution • Example for 1 of the 10000 bins in which the eta-ET plane has been divided • Red is b-jets - Black is not-b-jets • Fit done in 2 steps: • First in the whole histo range [0,2]  Get Mean and Sigma • Second in the range [mean-2.5*sigma,mean+2.5*sigma] Raw-MC jet Ratio Distribution MC jet-Parton Ratio Distribution Attilio Santocchia

    21. Ratio vs ET Distribution MC jet-Parton Ratio Distribution Raw-MC jet Ratio Distribution • Eta Ring 0.5<h<0.6 • Red is b-jets - Black is not-b-jets • No needs to distinguish b-jets for MC-Parton • Error Bar are defined as s/sqrt(N) where s is the width of the second fit and N is number of Entry (see slide #11) ET(GeV) ET(GeV) Attilio Santocchia

    22. Fitted Parameter Raw Jet MC Jet Parameter a Parameter b Parameter c • Fitted parameters as a function of eta • Red is b-jets - Black is not-b-jets h h h Here is the tracker Barrel-EndCaps Border! Attilio Santocchia

    23. Fitted Parameter MC Jet Parton (DR=0.5) Parameter a Parameter b Parameter c h h h • Fitted parameters as a function of eta • b-jets and not-b-jets are together • Each parameter fitted with a streight line Attilio Santocchia

    24. Parton Calibration - Fitted Para – Different Cone – All Particles Light Jets ● ICA 0.30 ● ICA 0.35 ● ICA 0.40 ● ICA 0.45 ● ICA 0.50 h h h bJets h h h Attilio Santocchia

    25. Ratio vs ET DistributionInput Particles is NoMuNu Eta=0.5-0.6 ET=51-54GeV Attilio Santocchia

    26. Ratio vs Eta Distribution (ET=45-48 GeV)Input Particles is NoMuNu and All Particles h h • Here AllParticles and NoMuNu show differences (for low eta) • But this is not a homogeneous functions… • Matching 0.15 is not enough? See also the Single distributions and the left tail… Attilio Santocchia

    27. MCJet to ttH Comparison (cone 0.5) • 3 different eta bin  No major difference above 40 GeV for not-b-jets and 60 GeV for b-jets • Difference due to different Calibration: • MCJet is only particle level • ttH is particle level and parton level • Parton level correction important for low ET jets Attilio Santocchia

    28. MC Jet Definition… what I learned… • Option Jet input list: • All Particles • NoMuNu • No major differences  the difference in bJets/lightJets is minor (negligible?) • Particle Calibration keeps the high difference btw bJets/lightJets… • Depends on the fragmentation used… • bJets charged spectrum different from lightJets • To recover correctly the jet energy is mandatory to tag the jets and use 2 different corrections for bJets and lightJets • Parton Calibration could be the same for all experiments (ATLAS/CMS)… • Providing the definition is the same for both od us… • All Particles keeps simple the definition for parton calibration Attilio Santocchia

    29. Invariant Masses ttH fully Hadronic • To cross-check the quality of the calibration functions, invariant masses for the W,t and Higgs particles are used • The 8 most energetic jets in the tracker are paired to the 8 partons in the final state using DR. • All the events where alle the 8 jets are paired with DR<0.3 have been selected • Invariant mass are built using the calibrated jets for each algorithm-calibration Attilio Santocchia

    30. Invariant Masses ttH fully Hadronic from MC Jets • 1000 events used for this exercise… • No DeltaR matching  Look for configuration 3+3+2 and correct JetRatio associations (see slide #9-#10) • Cone 0.5 is the more ermetic… OK but how many events survive the request 3+3+2? • Cone 0.4 is better… less ermetic but sigma is better, and Nevents is a lot better! Attilio Santocchia

    31. Invariant Masses ttH fully Hadronic • Invariant Masses for (from left to right) W,t and Higgs • Upper row is Standard CMS MC-Jet calibration and DeltaR=0.5 • Lower row is ttH-calibration and DeltaR=0.5 Minv(GeV) Minv(GeV) Minv(GeV) Minv(GeV) Minv(GeV) Minv(GeV) Attilio Santocchia

    32. Invariant Masses full Results • Resolution is defined as s/M • Numer of selected events and Resolution give a hint on the best algorithm to use • ICA DR=0.4 and inclusive KT seems good choice Attilio Santocchia

    33. Analysis from the CMS P-TDR ttH fully Hadronic • Analysys based on c2mass for jet pairing • 8 most energetic jets in |h|<2.7 • Centrality Cuts (All and Higgs) • The c2mass for 2W and 2tops within 3 sigma from expected values • Different cut for Btag and ET jets • Significance S/sqrt(N) and S/N used as benchMark Attilio Santocchia

    34. Same Analisys  Different Parton Calibration Attilio Santocchia

    35. ConclusionsNon ci sono ancora! ma… • La parton calibration è necessaria per noi sperimentali • La definizione di MCjet potrebbe essere uguale per tutti (ATLAS/CMS)… • In questo modo si potrebbe chiedere ai teorici/sperimentali di definire un unico oggetto che può essere usato da noi sperimentali per la particle calibration… • E dai teorici per la parton calibration… che è uguale per tutti… • In ogni caso la particle calibration non può essere unica per tutti i jets… • Ma una distinzione tra bJets e lightJets è necessaria… • Non ho ancora guardato il KT… mea culpa… Attilio Santocchia