CMS Performance Note

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1 Available on CMS information server CMS DP -0/00 CMS Performance Note 0 February 0 (v, 4 February 0) Results on b-tagging identification in 8 ev pp collisions Wolfgang Adam, Jérémy Andrea, Camille Beluffi, Daniel Bloch, Kenneth Bloom, Adrien Caudron, Harry Cheung, Caroline Collard, homas Danielson, Alexis Descroix, ristan du Pree, Juan Pablo Fernandez Ramos, Cristina Ferro, Alex Garabedian, Pablo Goldenzweig, Juan Pablo Gomez Cardona, Rebekka Höing, Ketino Kaadze, James Keaveney, Dan Knowlton, Patricia Lobelle Pardo, Michael Maes, Sudhir Malik, Ivan Marchesini, Ernesto Migliore, Niklas Mohr, Marco Musich, Meenakshi Narain, Andrea Rizzi, Alexander Schmidt, Luca Scodellaro, Michael Segala, Pedro Silva, homas Speer, Alberto raverso, Pierre Van Hove, Petra Van Mulders, Gerrit Van Onsem, Caterina Vernieri, Jesus Vizan, Roberval Walsh, Jinzhong Zhang Abstract At the Large Hadron Collider, the identification of jets originating from s is important for searches for new physics and for measurements of standard model processes. A variety of algorithms has been developed by CMS to select b-quark jets based on variables such as the impact parameters of the charged-particle tracks, the properties of reconstructed decay vertices, and the presence or absence of a lepton, or combinations thereof. he performance of these algorithms has been measured using data from proton-proton collisions at the LHC and compared with expectations based on simulation. he data used in this study were recorded in 0 at 8 ev for a total integrated luminosity of up to 7 fb-. he efficiency for tagging b-quark jets has been measured in events from multijet and t-quark pair production.

2 Results on b-tagging identification in 8 ev pp collisions At the Large Hadron Collider, the identification of jets originating from s is important for searches for new physics and for measurements of standard model processes. A variety of algorithms has been developed by CMS to select b-quark jets based on variables such as the impact parameters of the charged-particle tracks, the properties of reconstructed decay vertices, and the presence or absence of a lepton, or combinations thereof. he performance of these algorithms has been measured using data from proton-proton collisions at the LHC and compared with expectations based on simulation. he data used in this study were recorded in 0 at p for a total integrated luminosity of up to 7 fb. he efficiency for tagging b-quark jets has been measured in events from multijet and t-quark pair production. For more details, see as a reference the analogous results in p s = 7 ev collisions: Identification of b-quark jets with the CMS experiment, CMS Collab., CERN-PH-EP-0-6, arxiv:.446 A brief glossary of the used acronyms is given below: bsample Method to measure the b-tagging efficiency in tt events from a b-enriched lepton+jets sample CSV Combined Secondary Vertex algorithm, based on secondary vertex and track-based lifetime informations CSVL, CSVM, CSV CSV algorithm at the loose, medium, tight operating points FC Flavour ag Consistency method for the measurement of the b-tagging efficiency in tt events with lepton+jets FM Flavour ag Matching method for the measurement of the b-tagging efficiency in tt events with dileptons IPD Method for the measurement of the b-tagging efficiency in multijet events based on the D impact parameters of muons JP Jet Probability algorithm, based on the likelihood of tracks to come from the primary vertex (using the impact parameter significance values) JPL, JPM, JP Jet Probability algorithm at the loose, medium, tight operating points L Lifetime agging method for the measurement of the b-tagging efficiency in multijet events, based on template fits to the JP or CSV distributions PtRel Method for the measurement of the b-tagging efficiency in multijet events based on the transverse momenta of muons w.r.t. the jet axis System8 Method for the measurement of the b-tagging efficiency in multijet events with a muon, solving a system of equations CHP rack Counting High Purity algorithm, based on the impact parameter significance of the third track, ordered in decreasing values. CHP rack Counting High Purity algorithm at the tight operating point

3 Results on b-tagging identification in 8 ev pp collisions racks CMS 0 preliminary, /MC Nb. of pixel hits racks / 0 µm 6 4 CMS 0 preliminary, /MC Distance to jet axis [cm] Figure : rack properties after basic selection (except for the variable plotted): (top) number of hits in the pixel system and (bottom) distance to the jet axis. he distributions from simulation have been normalized to match the counts in data. he stacked, coloured histograms indicate the contributions of different components from simulated multijet ( QCD ) samples. Simulated events involving gluon splitting to s ( ) are indicated separately from the other b production processes ( ). In each histogram, the rightmost bin includes all events from the overflow. he sample corresponds to a trigger selection with jet p > 40 GeV/c. Jets with p > 60 GeV/c are selected.

4 racks / 0 µm CMS 0 preliminary, 6 4 /MC D IP [cm] racks / CMS 0 preliminary, /MC D IP significance Figure : Distributions of (top) the D impact parameter and (bottom) the significance of the D impact parameter for all selected tracks. Selection and symbols are the same as in Fig.. Underflow and overflow are added to the first and last bins, respectively.

5 4 Results on b-tagging identification in 8 ev pp collisions Jets / 0. CMS 0 preliminary, 6 4 /MC CHP discriminator Jets / 0.0 CMS 0 preliminary, 6 4 /MC JP discriminator Figure : Discriminator values for (top) the CHP and (bottom) the JP algorithms. Selection and symbols are the same as in Fig.. he small discontinuities in the JP distributions are due to the single track probabilities which are required to be greater than 0.%. he operating point value for the CHP tagging criterion is set to.4. he operating point values for the JPL, JPM, JP tagging criteria are set to 0.7, 0.4, 0.790, respectively.

6 SV / 4 CMS 0 preliminary, /MC D SV flight distance significance SV / 0.08 GeV/c CMS 0 preliminary, /MC SV mass [GeV/c ] Figure 4: Properties of reconstructed decay vertices: (top) the significance of the D secondary vertex (D SV) flight distance and (bottom) the mass associated with the secondary vertex. Selection and symbols are the same as in Fig..

7 6 Results on b-tagging identification in 8 ev pp collisions Jets /MC CMS 0 preliminary, Nb. of secondary vertices Jets / CMS 0 preliminary, /MC CSV discriminator Figure : Distributions of (top) the secondary vertex multiplicity and (bottom) the CSV discriminator. Selection and symbols are the same as in Fig.. he operating point values for the CSVL, CSVM, CSV tagging criteria are set to 0.44, 0.679, 98, respectively.

8 7 - CMS 0 prelim., 7 fb at Jets / 0. GeV/c JPL tagged b jets light-parton + c jets Jets / 0. GeV/c [GeV/c] - CMS 0 prelim., 7 fb at rel p JPL untagged b jets light-parton + c jets [GeV/c] Figure 6: Fits of the summed b and non-b templates, for simulated muon jets, to the muon p rel distributions from data. (top) and (bottom) show the results for muon jets that pass (tagged) or fail (untagged) the b-jet tagging criteria of the JPL method, respectively. he muon jet p is between 80 and 0 GeV/c. rel p

9 8 Results on b-tagging identification in 8 ev pp collisions Jets / CMS 0 prelim., 7 fb at CSVM tagged b jets c jets light-parton jets ln( IP [cm]) Jets / CMS 0 prelim., 7 fb at CSVM untagged b jets c jets light-parton jets ln( IP [cm]) Figure 7: Same as Fig. 6 using the ln( IP [cm]) distributions and the CSVM tagging criterion. he muon jet p is between 60 and 0 GeV/c.

10 9 Jets/0. - CMS prelim., 7 fb at fit b jets c jets udsg jets Jets/0. - CMS prelim., 7 fb at fit b jets c jets udsg jets JP discriminator JP discriminator Figure 8: Fits of the summed b, c and light-parton templates, for simulated jets, to the JPdiscriminant distributions from data in muon-jet events. Jets with p > 600 GeV/c are selected. (left) and (right) show the results for muon jets before and after identification with the CSVM tagger, respectively. he black line is the sum of the contributions from the templates. Overflows are displayed in the rightmost bins. Jets / CMS preliminary, 7 fb at 0000 all 8000 c jets 6000 b jets udsg jets 4000 Jets / CMS preliminary, 7 fb at tagged c jets b jets udsg jets JP discriminator JP discriminator Figure 9: Fits of the summed b, c and light-parton templates, for simulated jets, to the JPdiscriminant distributions from data in tt events into dilepton (ee, µµ, eµ) final state. (left) and (right) show the results for jets before and after identification with the CSVM tagger, respectively. he black line is the sum of the contributions from the templates. Overflows are displayed in the rightmost bins.

11 Results on b-tagging identification in 8 ev pp collisions CMS Preliminary. fb at - Events tt Single-op W lν + - Z/γ* l l Uncertainty /MC χ =.44 KS est = Number of agged Jets CMS Preliminary. fb at - Events tt Single-op W lν + - Z/γ* l l Uncertainty /MC χ = KS est = Number of agged Jets Figure : Number of tagged jets per event in the lepton+jet channel with the FC method with the CSVM operating point, in the data (filled circles) and the simulation (solid histograms), (top) before and (bottom) after the fit. he simulated distribution is normalized to the integrated luminosity. he hatched area corresponds to the combined statistical and systematic uncertainty.

12 CMS Preliminary. fb at - b-tag Efficiency Monte Carlo ruth 0. Measured Value SF b CSV Discriminator Value Figure : Measured b-jet tagging efficiency as a function of the flavour discriminator threshold for the CSV algorithm, measured with the FC method. he absolute b-jet tagging efficiency measured from data and predicted from simulation is shown in the upper panel. he scale factors SF b is shown in the lower panel, where the blue dashed lines represent the combined statistical and systematic uncertainty. he arrows indicate the standard operating points.

13 Results on b-tagging identification in 8 ev pp collisions Events / 0 GeV CMS Preliminary 6.4 fb at - tt signal tt other Single-op W lν + - Z/γ* l l Luminosity /MC M µb (GeV) Figure : Distribution of the jet-muon mass in the data (filled circles) and the simulation (solid histograms), as used in the bsample method. he simulated distribution is normalized to the integrated luminosity. he component tt signal stands for the lepton+jet events. he component tt other contains the events in all other decay channels. he hatched area corresponds to the combined statistical and systematic uncertainty. Overflow entries are added to the last bin.

14 CMS preliminary (stat+syst) - 7 fb at s=8 ev bsample L ttbar multijet FC FM combined CHP JP JPM JPL CSV CSVM CSVL SF b Figure : Summary of the measurements of the ratio of the b-jet tagging efficiencies of the data to that in simulation in tt events: lepton+jets ( FC and bsample methods) and dilepton ( FM and L ttbar methods) final states. he combined tt results (grey area) is compared to the overall multijet results ( multijet ) for b-jets in the p range of tt events.

15 4 Results on b-tagging identification in 8 ev pp collisions /Sim. b-tag SF CMS prelim., 7 fb at JPL PtRel System8 IPD L Jet p [GeV/c] /Sim. b-tag SF CMS prelim., 7 fb at JPL weighted average fit fit ± (stat syst) SFb Jet p [GeV/c] Figure 4: Individual and combined measurements of the ratio of the b-jet tagging efficiencies of the data to that in simulation for the JPL tagger. he (top) and (bottom) figures show the individual measurements from the muon p rel ( PtRel ), System8 ( System8 ), muon IP ( IPD ) and lifetime tagger method on muon-jet events ( L ) or tt events into dilepton (ee, µµ, eµ) final state ( ttbar for the CSV tagger only). he inner and outer error bars indicate the statistical and the combined uncertainties, respectively. he grey hatched areas represent the combined measurements at p. In the lower panels the combined measurements have been parameterized by functions of the form SF b (p )=a( + bp )/( + gp ). he error bars attached to the function have the same size as the uncertainties from the combined measurement in each bin. he yellow areas represents the similar results obtained at p s = 7 ev.

16 /Sim. b-tag SF CMS prelim., 7 fb at CSVM PtRel System8 IPD L ttbar Jet p [GeV/c] /Sim. b-tag SF CMS prelim., 7 fb at CSVM weighted average fit fit ± (stat syst) SFb Jet p [GeV/c] Figure : Same as Fig. 4 for the CSVM tagger.

17 6 Results on b-tagging identification in 8 ev pp collisions Jets / CMS preliminary, MC b MC c MC udsg Jets / 0. 4 CMS preliminary, 6 MC b MC c MC udsg /MC JP discriminator CHP discriminator Jets / /MC CMS preliminary, JP discriminator /MC.4. MC b MC c MC udsg CSV discriminator CSV discriminator Figure 6: Signed b-jet tagging discriminators in data (dots) and simulation for light-parton jets (blue histogram, with a lighter colour for the negative discriminators), c jets (green histogram), and b jets (red histogram) for the (top left) CHP, (top right) JP, (bottom) CSV algorithms. A jet-trigger p threshold of 40 GeV/c is required for both data and simulation. he simulation is normalized to the number of entries in the data. Underflow and overflow entries are added to the first and last bins, respectively.

18 7 Misidentification probability CMS prelim., 7 fb at JPL p [GeV/c] MC / MC misid. SF CMS prelim., 7 fb at JPL / MC fit to data stat syst p [GeV/c] Figure 7: For the JPL tagger: (top) misidentification probability in data (red squares) and simulation (blue dots); (bottom) scale factor for the misidentification probability. he last p bin in each plot includes all jets with p > 800 GeV/c. he solid curve is the result of a polynomial fit to the data points. he dashed curves represent the overall statistical and systematic uncertainties on the measurements. Misidentification probability CMS prelim., 7 fb at CSVM p [GeV/c] MC / MC misid. SF CMS prelim., 7 fb at CSVM / MC fit to data stat syst p [GeV/c] Figure 8: Same as Fig. 7 for the CSVM tagger.