Tau Reconstruction at CMS. Evan Friis

Transcription

1 Tau Reconstruction at CMS Evan Friis

2 Outline Taus at hadron colliders Tau ID algorithms at CMS Tau ID measurements in 2010 Z ττ standard candle SVfit: τ pair mass reconstruction MSSM H ττ

3 Tau ID at hadron colliders proton - (anti)proton cross sections tot Exciting new physics signals could appear in tau channels QCD Jets can fake taus QCD background is very large! Dominant background in many analyses is fake taus (nb) jet (E T jet > s/20) jet (E T jet > 100 GeV) WJS2009 b W Z t jet (E T jet > s/4) Higgs (M H =120 GeV) 200 GeV 500 GeV Tevatron LHC s (TeV) events / sec for L = cm -2 s -1

4 Particle Flow Algorithm taus in CMS are built using Particle Flow objects Clusters and links signals from all subdetectors Produces a list of particle candidates h h 0 e μ γ To the user looks just like Monte Carlo,*-*9-#$ 5/64 /"+7-*$7 0/64 /"+7-*$7 ;&$-%9"*<="#> 8$&9:7 F. Beaudette

5 Particle Flow Performance Jet Transverse Energy Resolution # Particle Flow Particle Flow Jets CMS Preliminary SIM Particle Flow resolves overlaps in subdectors GeV Et tau Calo Tower Jets Improves resolution Et Tau ET resolution

6 Traditional CMS Tau ID geometrically defined isolation define geometric region around tau candidate and require low detector activity relies on the fact that taus are more collimated than QCD CMS Physics Technical Design Report (PTDR) results use these algorithms see CMS PAS PFT

7 Decay Mode CMS Tau ID Particle Flow algorithm allows examination of meson content two new algorithms: Hadrons Plus Strips (HPS) algorithm Tau Neural Classifier (TaNC) algorithm GOAL: optimize tau identification for individual tau decay modes

8 Hadrons Plus Strips Algorithm build signal components combinatorially cluster gammas into π 0 candidates using η-φ strips build all possible taus that have a ʻtau-likeʼ multiplicity from the seed jet φ π 0 γ γ γ π 0 π + π + π π + π + π - γ 0.05 η tau that is ʻmost isolatedʼ with compatible mvis is the final tau candidate associated to the seed jet

9 Tau Neural Classifier a neural network for each decay mode cluster gammas into π 0 candidates by combinatoric pairs compatible with mπ0 φ signal objects are defined using shrinking cone depending on decay mode π 0 π + π 0 γ γ γ π + π 0 π + π 0 π 0 π + π + π - γ π + π + π - π 0 a different neural network η is applied!

10 Tau Performance measuring the fake rate is easy (no lack of background at the LHC) fake rate is different for W+jets, multi-jet, heavy flavor independently measuring signal efficiency is hard in practice efficiency extracted in situ in Z and Higgs analyses

11 Fake Rate measurement TAU open points = simulation red is W+jets closed points = data purple is heavy flavor CMS Preliminary 2010, -1 s=7 TeV, 36 pb CMS Preliminary 2010, -1 s=7 TeV, 36 pb fake rate from jets 10-2 W#µ" Data TANC TaNC loose! fake rate from jets 10-2 HPS HPS loose W#µ" Data W#µ" Simulation QCDj Data QCDj Simulation QCDµ Data QCDµ Simulation! W#µ" Simulation QCDj Data QCDj Simulation QCDµ Data QCDµ Simulation Data-Sim. Simulation jet p T (GeV/c) Data-Sim. Simulation jet p T (GeV/c)

12 sured in data are represented by solid symbols and compared to MC prediction y open symbols. TAU Tau ID Performance CMS Preliminary 2010, -1 s=7 TeV, 36 pb fake rate from jets 10-2 PTDR, W+jet PTDR, QCDµ TaNC, W+jet TaNC, QCDµ HPS, W+jet HPS, QCDµ purple info box 3X improvement since PTDR measured! expected! efficiency measured fake rate as a function of MC estimated efficiency for all working

13 Tag & Probe efficiency TAU Preselect Z τ μτhad using loose isolation + Z analysis cuts Fit ττ M vis passing/failing spectra composition Method robust against Higgs contamination in Z peak CMS Preliminary 2010, -1 s=7 TeV, 36 pb CMS Preliminary 2010, -1 s=7 TeV, 36 pb number of events Data * Z/# "! + QCD W + jets * Z/# " µ + tt + jets HPS loose -! - µ PASSED number of events Data * Z/# "! + QCD W + jets * Z/# " µ + tt + jets HPS loose -! - µ FAILED µ! jet visible mass (GeV/c 2 ) µ! jet visible mass (GeV/c 2 ) Figure 2: The visible invariant mass of the µτ jet system for preselected events which passed (left) and failed (right) the HPS loose tau identification requirements compared to predictions of the MC simulation. result: DATA/MC 1.0 ± 25%

14 Zττ cross section EWK ! Analysis goal: understand taus at CMS Four channels: μ-had, e-had, e-μ, μ-μ ~25% τ-id uncertainty limits utility as test of Standard model Instead: believe in lepton universality and use Z peak to measure τ-id Combined fit of all channels

15 Z ττ cross section final Zττ events selected EWK Events / (10 GeV) pb CMS preliminary at s = 7 TeV Z "!! " µ! had data Z "!! EWK+tt QCD Events / (10 GeV) pb CMS preliminary at s = 7 TeV Z "!! " e! had data Z "!! EWK+tt QCD Events / (10 GeV) yields from fit Visible Mass [GeV] pb CMS preliminary s = 7 TeV data Z "!! EWK+tt QCD yields from fit at Z "!! " eµ e-µ Invariant Mass [GeV] Events / (10 GeV) yields from fit Visible Mass [GeV] pb CMS preliminary s = 7 TeV data Z "!! Z/#* " µµ QCD yields from fit at Z "!! " µµ µ-µ Invariant Mass [GeV] Figure 2: Visible mass distributions of the τ µ τ had (top left), τ e τ had (top right), τ e τ µ (bottom left), and τ µ τ µ (bottom right) final states. non-tau backgrounds measured from data

16 Combined Zττ Fit simultaneously fit all channels for σz AND ετid e-μ and μ-μ channels drive σzττ central value EWK Combined: σ (pp ZX) B Z τ + τ = 1.00 ± 0.05 (stat.) ± 0.08 (syst.) ± 0.04 (lumi.) nb, fitted ετid MC/DATA = 0.93±0.09 assume σzττ = σzee/μμ ετid MC/DATA = 0.96±0.07 Taus are well understood objects at CMS!

17 searches with taus

18 Tau pair mass reconstruction Searches for new resonances to taus Tau pair invariant mass is the most natural observable Tau decays have invisible component Recovery methods: Collinear approximation SVfit algorithm Missing Mass algorithm (see Alexeiʼs talk)

19 The Collinear Approximation Assume neutrinos collinear with visible products Approximates true ττ mass MET x = P ν 1 sin θ 1 cos φ 1 + P ν 2 sin θ 2 cos φ 2 τ vis 1 MET y = P ν 1 sin θ 1 sin φ 1 + P ν 2 sin θ 2 sin φ 2 Very sensitive to MET MET angular resolution! τ vis 2 ~45% of events thrown away due to unphysical negative energies

20 SVfit mass reconstruction parameterize the physics of tau decays maximize a likelihood function w.r.t. the tau decay parameters likelihood terms: decay phase-space reconstructed neutrinos and measured ME T p T-balance regularization compatibility with tracker information (optional)

21 Decay Parameterization a τ decay can be completely described by: θ φ minvis R Rest frame angle between boost and visible decay productions Azimuthal angle of visible decay products about boost direction Mass of invisible decay product system (minvis = 0 for τhad) Flight distance in lab frame

22 Decay Parameterization reconstructing the tau energy rest frame visible energy: E vis = m2 τ +m2 vis m2 νν 2m τ Lorentz invariant component of visible momentum sin θ LAB = p vis sin θ p LAB vis Solve Lorentz transformation along boost for γ p LAB vis cos θ LAB = γβe vis + γp vis cos θ E LAB τ = γm τ

23 Decay Parameterization reconstructing the tau direction sin θ LAB = p vis sin θ p LAB vis constrains τ direction to lie on cone with angle θ LAB about visible momentum uvis azimuthal fit parameter φ φ determines direction R flight path R determines θ L location of decay vertex (optional) PV

24 Phase Space Likelihood Two or three-body decay Hadronic decays trivial Leptonic decays depend on m νν dγ M 2 ((m2 τ (m νν + m vis ) 2 )(m 2 τ (m νν m vis ) 2 )) 1/2 2m τ m νν dm νν sin θdθ present implementation of the SVfit algorithm, the matrix element is assume Decays are assumed to be isotropic: M 2 = 1 Investigating extending term to account for polarization correlations between taus Possible handle to separate Higgses from Zs!

25 likelihood MET Compare SV-fitted neutrinos to measured missing transverse energy Resolution of ME T parameterized by ΣET of the event Resolution measured in Z μμ events Zμμ events

26 PT - balance likelihood to reduce background one must apply kinematic thresholds on visible decay products for Z/H μ-had channel: pt μ > 15 GeV, pt had > 20 GeV significantly biases the kinematic distributions pt balance term: probability for decay pt from mass M 0.1 τ μνν before P T cut after P T cut τ τhν before P T cut after P T cut 0.08 H(130) 0.08 H(130) Visible energy fraction Visible energy fraction

27 PT - balance likelihood term which represents the probability P(pT Mττ) first assume isotropic decay of resonance M at rest each decay product has P(pT) P iso (p T ) p T 1 (2pT /M ) 2 smear with Gaussian and add Gamma to account for resolution and non-zero boost P total (p T ) P iso (p T ) exp( p2 T 2s 2 )+aγ(p T,k,θ) smear, Gamma fraction and shape are fitted as first order functions of Mττ

28 Tracking constraint Taus have non-negligible lifetime: cτ = 87µm uvis Use tracker information Constrain fitted SV SV φ to lie on track with error R Constrain flight time R Not currently used. θ L Working to understand alignment issues. track

29 SVfit Performance SV fit has better resolution than collinear approximation (left) SV fit has twice the acceptance as the collinear solution (right) a.u CMS Preliminary SV fit Z "!! Simulation s = 7 TeV Collinear approx Events CMS Preliminary $(120)#!! s = 7 TeV tan"=30 SV fit Collinear approx [GeV/c ] M!! normalized to unity [GeV/c ] M!! normalized to luminosity

30 SVfit Performance SVfit peaks at di-tau mass better relative resolution that visible mass a.u CMS Preliminary %(160)$## s = 7 TeV tan"=30 SV fit Visible mass Visible mass! mass [GeV/c ]

31 Extensions to SVfit currently under development Implement tracking likelihood Improve p T-balance parameterization Use polarization information Integration instead of maximization (similar to DLM, MMC) Extend code to fit N leptons Application to W τν, H ++, etc

32 MSSM H ττ Search Taus one of the best handles for MSSM μ + τ had e + τ had μ + e Benefit from tanβ enhancement σ and BR Search performed with three channels: Tau ID correction factor floats in final fit, constrained by Z peak & 25% tag-probe All backgrounds measured from data

33 MSSM H ττ Search HIG results final Mττ distribution of all channels no bumps!"#$%&'()*+,#-'! ).!"#$%&'()*+,#-'! ). 1** 0** )** /** * ) /* /* purple info box =CD+E6#F575$26G 0H+49 I/ +++J+K#- 89&#6"#: 7 A +B+)**+,#-'! ) ; ;!!,!@ <=>?+%% / * /** )** 0** 1** % &&+(,#-'! ).

34 MSSM Expected Limits HIG Visible mass Expected Bayesian 95% CL limits on σh BR(H ττ) SVfit BR(h"!!) Expected limit on $ # CMS Preliminary, s -1 = 7 TeV, L = 35 pb!! " µ! had!! " e! had!! " e µ Combined m(a) [GeV/c 2 ] BR(h"!!) Expected limit on $ # CMS Preliminary, s -1 = 7 TeV, L = 35 pb!! " µ! had!! " e! had!! " e µ Combined m(a) [GeV/c 2 ] SVfit improves limit by 10%

35 MSSM Observed Limit HIG observed limit on σh BR(H ττ) 900 >=?9 =++90"= ,AB+C%$DE7E2F%G 6H+0" I3 +++J+K$; ()*+,-.-+/00$%+"1/2'#!"#$%&$' A$'EF2+$L0$MN$' 3 +$L0$MN$'+%F2O$ 5 +$L0$MN$'+%F2O$ 544 ) :$;<! 5 = re 2: The expected one- and two-standard-deviation ranges (blue bands) an

36 ure 3: Region in the parameter space of tan versus m excluded at 95% C.L. Interpretation in tanβ HIG /7!"#$%&'()*)+,&-$$$./$01 23 $$$4$5'6 :,+ ; *,H "##"$* < $$$$=>'+,&)?@$" #A#B $C$3$5'6 D;E$!FGF$'H>(IJ'J$&'K)?+= 377 3; ;7.77 * L $$$MN'6O! 8 P $!"#$'H>(IJ'J $Q3 $:<'?&- $!"#$'H0'>:'J GS%$'H>(IJ'J 5'R,:&?+$'H>(IJ'J

37 Summary Large improvements in τ-id since PTDR Tau fake rates & efficiency measured in real data Z ττ cross section measured with high precision Taus well understood at CMS SVfit method improves M ττ resolution CMS sets new limits on MSSM using taus

38 backup

39 Particle Flow Algorithm CMS Preliminary HCAL Entrance ECAL Entrance ECAL Entrance HCAL Entrance cluster linked to track unlinked cluster tracker hit see CMS PAS PFT

40 Particle Flow Performance Jet Transverse Energy Resolution # 450 CMS Preliminary invariant mass of PF photon pairs Particle Flow Particle Flow Jets 50 GeV Et tau SIM Number of photon pairs fit 2 m! 0 = ± 0.1 MeV/ c 2 " m! = 13.2 ± 0.1 MeV/ c TeV Data, 0.1 nb CMS Preliminary Calo Tower Jets Et TeV Data, 0.1 nb Mass (GeV/c ) Tau ET resolution Mass of photon pair [GeV/c 2 ] Figure 1: Photon-pair invariant-mass distribution the simulation (b).

41 Shrinking Cone Algorithm reduce QCD by applying isolation requirement require a leading candidate with pt > 5 within ΔR < 0.1 of jet axis signal objects are those with ΔR < ΔRsig of the lead candidate R sig =5.0/E jet T isolation objects are those in the region ΔRsig < ΔR < 0.5 about the lead candidate R = φ 2 + η 2

42 Zττ selections Trigger Events triggered by single Electron/Muon Triggers P T thresholds 9-15 GeV, depending on instantaneous Luminosity Lepton Selection Electrons Muons had.! Decays P T > 15 GeV P T > 15 GeV P T > 20 GeV! < 2.4! < 2.1! < 2.4 isolated isolated loose Tau id. Veto against e/µ Opposite Charge Lepton Pair Event Selection For µ +! had, e +! had and e + µ Channels, µ + µ Channel different (Backup) Transverse Mass e +! had, µ +! had : M T (l + MET) < 40 GeV e + µ: M T (e + MET ) < 50 GeV && M T (µ + MET) < 50 GeV Veto Events with additional isolated Leptons Christian Veelken Higgs and Z!! +! - in CMS 5

43 Zττ yields Event Yields CMS Data, 36 pb 7 TeV Background Estimates quoted in Table obtained from Data-driven Methods > 600 Z!! +! - Signal Events selected in CMS Data Christian Veelken Higgs and Z!! +! - in CMS 7

44 Z recoil correction MET resolution better in Monte Carlo than data before correction after correction Zμμ events Zμμ events Project MET in directions parallel and perpendicular to Z and parametrize as function of Z pt

45 sub title Observed vs. expected Limits by Channel visible Mass full! +! - Mass 34

46 Higgs Search control plots Lepton P T and!: µ +! had Channel Christian Veelken Higgs and Z!! +! - in CMS 26

47 Higgs Search control plots Lepton P T and!: e +! had Channel Christian Veelken Higgs and Z!! +! - in CMS 27

48 Z!! +! - Systematic Uncertainties Largest Uncertainty: hadronic Tau Identification Efficiency!!" had Identification Efficiency constrained by Ratio of Event Yields in semi-leptonic/leptonic Channels!! Determine Z " " + " - Cross-section by simultaneous Fit of all four Channels Christian Veelken Higgs and Z " " + " - in CMS 25

49 Christian Veelken Higgs and Z!! +! - in CMS 28

50 Christian Veelken Higgs and Z!! +! - in CMS 29

51 Christian Veelken Higgs and Z!! +! - in CMS 30