Plots for approval- jet shapes as a function of NPV

Lily Asquith (ANL) on behalf of ATLASBoost 2012, Valencia

jet shapes0OutlineWhat are jet shapes, and why are we measuring them?

Experimental challenges.

The measurements. arxiv:1206.5369

Whats new?

1What are jet shapes?All of these observables are constructed using the angular separation and energy of the jet constituents. e.g. mass:A jet.A constituent.

Traditionally jet shapes are differential and integrated. arxiv:1101.0070, arxiv:1204.3170These shapes are different measures of energy flow: mass, width, planar flow, eccentricity and angularity.

2Core-heavy jet: width0

Width3WidthBroad jet: width1

4Quark/ gluon?Quark/gluon jets: width (or girth); gluon jets are broader than quark jets, with more tracks.

arXiv:1106.3076v25Planar flowTwo-body jet: Linear energy deposition: Planar flow0

6Planar flowThree-body jet: Planar energy deposition: Planar flow1

7EccentricityIsotropic energy deposition: eccentricity0

8EccentricityElongated energy deposition: eccentricity1

9Two- and higher-body decaysPlanar flow can distinguish between three-body (top) jets and two-body (light quark/ gluon) jets.

arXiv:0807.023410Angularity -2Asymmetric energy deposition: -2maximum

11Angularity -2Symmetric energy deposition: -20

12Different two-body decaysAngularities can distinguish between two-body (W/Z/H) jets with different polarisation and two-body (light quark/gluon) jets.

arXiv:0807.0234

Longitudinal Z/ QCDTransverse Z/ QCDz=m/pT Longitudinal Z jetsQCD (light quark, gluon) jets13Correlations between observables

High pT, central, Pythia6 dijets.

Mass and width are strongly correlated.

Planar flow and eccentricity are strongly anti-correlated.14Correlations between observables

At high mass, the correlations change. These are for QCD.Mass > 100 GeVNo mass cut15The experimental challenges:aka Pileup

16Why pileup is such a problem for jet shapes and substructure

1: These jets are big. These sorts of observables generally change under pileup like R2 or more17Why pileup is such a problem for jet shapes and substructure2: We want to be able to distinguish A from BAB18Why pileup is such a problem for jet shapes and substructure2: We want to be able to distinguish A from BAB in these conditions.19Pileup

2010: ~2 (28% of events NPV=1) special datasetThe Number of reconstructed Primary Vertices - NPV can tell us how much additional radiation we are dealing with.

2011: ~ 10 20122012*: ~ 25+. 2020Controlling pileup

Complementary cone technique (CDF) looks in region transverse (in azimuth) to the jet.

Energy deposits in this region are attributed to pileup and underlying event (UE): soft radiation that is always present.arxiv:1101.3002, 1106.5952v2

21Controlling pileupSingle vertex events contain only the UE contribution characterise pileup by comparing events with single and multiple vertices.

expectedmeasured

arxiv:1206.5369 Can then find the scaling of e.g. M with R obtain subtractions for R=1 jets.

22Controlling pileupComplementary cone technique restores distributions to shape seen in single vertex events.

23The measurements24DetailsEvents are selected based on run conditions, data quality and detector conditions.The anti-kT algorithm is used with locally calibrated topological clusters as input.The highest pT jet in each event is measured, must have pT>300 GeV.ObservableRMass rangePileup correctionMass M0.6,1.0AllWidth W0.6,1.0AllPlanar flow P1.0130-210NPV=1Eccentricity 0.6,1.0>100Angularity -20.6100-130Not needed25Jet massPYTHIA8, PYTHIA6HERWIG++ 2.4.2, 2.5.1POWHEG, PYTHIA6R=0.6R=1.0

26Jet mass

Herwig++ 2.5.1 jet mass prediction is greatly improved w.r.t 2.4.227Jet mass

Eikonal approx of QCD for gluons and quarks is compatible with our expectation that the data is a mixture of quark and gluon initiated jets.28Jet mass

Dominant contributions to the systematic uncertainty are the cluster energy scale and Monte Carlo predictions.These show C on the y-axis: C is the correction factor in bin i when going from detector-level to particle-level jets in the baseline Pythia6 (AMBT1) MC sample.C is the difference when we vary the sample w.r.t this baseline.Shading is statistical uncertainty. 29Jet widthWidth is well-modeled by all MCs beyond the first bin.

30DetailsObservableRMass rangePileup correctionMass M0.6,1.0AllWidth W0.6,1.0AllPlanar flow P1.0130-210NPV=1Eccentricity 0.6,1.0>100Angularity -20.6100-130Not neededPlanar flow is measured for jets with mass in a window around the top mass.Not many R=0.6 jets have such a high mass:Only measure P for R=1.0 jets.Only measure P in pileup-free (NPV=1) events.31Planar flow

Again we see Herwig++ 2.5.1 providing a superior description of the energy flow wrt 2.4.2.Note: this is not the same mass range as the eccentricity measurements.32DetailsEccentricity is measured in the general region of interest for boosted particle searches: M>100 GeV.

ObservableRMass rangePileup correctionMass M0.6,1.0AllWidth W0.6,1.0AllPlanar flow P1.0130-210NPV=1Eccentricity 0.6,1.0>100Angularity -20.6100-130Not needed33Eccentricity

Eccentricity is a magnifying glass for differences in the distributions of constituents on the local angular scale:

34Eccentricity

Eccentricity is a magnifying glass for differences in the distributions of constituents on the local angular scale:

This piece varies significantly between MCs, but (mostly) washes away with energy weight (soft particles).Highly anti-correlated with planar flow (-90% for jets in same high mass range)35DetailsQCD small-angle approximation gives a prediction for the peak and maximum values of the -2 distribution:Valid for fixed high mass and pT (we choose 1000.3, then we chuck it. Then we rebuild the jet from remaining clusters.Trimmed: The jet constituents are reclustered with a small distance parameter R=0.3 into subjets. Any subjet with pT