Muon fake rates: a systematical approach

04-05-2009 CMSSWPD meeting - Luca Perrozzi 1

Muon fake rates:Muon fake rates:a systematicala systematical

approachapproach


Framework and data sampleFramework and data sample• CMSSW_2_2_3 using PATtuples• B decays yielding muons (including DIF)

– /QCD_BCtoMu_PT30to50/Summer08_IDEAL_v11_redigi_v1/GEN-SIM-RECO

– 30GeV < Pt(hat) < 50GeV– = 91.77 b– Filter efficiency = 0.0061– Generated Muons (Pt>5GeV, ||<2.5) ≥ 1– No trigger requirements– 600k events used so far (L= 1027 nb-1)

• PAT (or TMLastStationOptimizedLowPtTight) muons


Checking fake rates on dataChecking fake rates on data

Pi tracks fromK0

s Signal

Reco K0s

Pi tracks fromK0

s Background

Reco Mu

Mu associated toPi track fromK0s Signal

Mu associated toPi track from

K0s Background

R<0.01Pt<0.01

R<0.01Pt<0.01

Sig - Bkg

Sig - Bkg

Pi Rate

Mu Rate

Mu/Pi

Pi (from K0s)

fake rate (as function of

Pt, Eta, Phi,dxy,decay length)

K0s→+-

case


Reco Reco (from Ks)(from Ks) association cutsassociation cuts

Pt/Pt<0.01

R|<0.01

Pt/Pt vs |R|

2 2R


KK00ss case case

V0 moduleoutput


Phi distributions forPhi distributions for and and - - Stage IStage I

Black: Signal regionViolet: Bkg region

Muons associated to Pions

Log scale!

Pions


• Select Pi tracks from K0

s mass signal and background region, then look for associated


Pi from KPi from K00ss fake rate vs. Phi - Stage fake rate vs. Phi - Stage

IIII

Log scale!

phi distribution after Sig-Bkg

Black: PionsRed: Muons

• Subtract sidebands (Sig-Bkg) for and , then obtain fake rate as ratio /

Fake rate as a function of phi


KK00ss fake rate summary fake rate summary

NB: large muon fraction in sidebands requires larger Bkg sidebands to reduce statistical errors !!!

Pions in K0s mass signal

region 97347

Pions in K0s mass bkg

region 9695

Signal – Bkg for Pions 87652

Muons associated to pions in K0

s mass signal region 865


s mass bkg region 415

Signal – Bkg for Muons 450

Muons/Pions ratio(5.1±0.4)∙

10-3

K0s mass mean (MK):

0.498079 GeVK0

s mass sigma (K):

0.006585 GeV

Signal region:|M-MK|<1.4 K

Background region:2.8 K <|M-MK|< 4.2 K


00pp case case

V0 moduleoutput


00pp fake rate summary fake rate summary (p(ponly)only)

Protons in mass signal region 10170

Protons in mass bkg region 2586

Signal – Bkg for Protons 7584

Muons associated to protons in mass signal

region253

Muons associated to protons in mass bkg

region129


Muons/Protons ratio(1.6±0.25)∙

10-2

0s mass mean (M):

1.115850 GeV0

s mass sigma ():

0.002550 GeV

Signal region:|M-M|<1.4

Background region:2.8 <|M-M|< 4.2



KK++KK case case

Made“by hand”


KK++KK fake rate summary fake rate summaryPions in K0


Pions in K0s mass bkg

region 354756

Signal – Bkg for Pions 94240




s mass bkg region 7354


Muons/Pions ratio(3.7±0.1)∙1

0-2

0s mass mean (M):

1.115850 GeV0

s mass sigma ():

0.002550 GeV

Signal region:|M-M|<1.4

Background region:2.8 <|M-M|< 4.2



UpdatesUpdates

• TMLastStationOptimizedLowPtTight muons used

• Background sidebands expanded• Nuclear interactions examples with

GenPKs– 1,2,3 prong vertexes

• New resonances added in V0Producer

• New tracking algorithm example


Muon selectors efficiencies & Muon selectors efficiencies & puritypurity


PAT vs LastStation muons (I)PAT vs LastStation muons (I)



• Select Pi tracks from K0s mass signal and background region, then look for associated



PAT muons Last station muons

Pt distribution after Sig-Bkg


PAT muons

Pt distribution after Sig-Bkg


Last station muons


PAT vs LastStation muons PAT vs LastStation muons (II)(II)

Fake rate as a function of Pt


Fake rate as a function of Pt

Using LastStation muons statistics decreases dramatically! (factor ~5)






impact parameter distribution doesn’t change significantly


PAT vs LastStation muons PAT vs LastStation muons (III)(III)

Fake rate as a function of phi Fake rate as a function of phi

Using LastStation muonsfake rate decreases a factor ~5 !!!

PRELIMINARY


KK00ss case case

• Sum of 2 gaussian fits perfectly mass distribution shape

•Need to redefine

New FIT!

Old FIT!


SignificanceSignificance

F = Ns + Nb – kNc

If NC = kNB

2 2 2 2

S B CF N N NS B C

S B C

F F F

N N N

N N N

S+B

C

(1 )S

F S B

NF

N N k


Background sidebands Background sidebands extensionextension

• If we try to plot mass distributions for all Ks (black) and only for those with at least one pi-mu association (red) we obtain top plot.

• If we divide histograms (red/black) we see that oustide peak region ratio rises linearly so we can extend our background sidebands.

• Fitting top red histogram no clear changes in mass peak’s mean and sigma are noticed (also fixing one of the two parameters) with respect to black histo


Background sidebands Background sidebands extensionextension

Bkg/Sig = 5

Bkg/Sig = 1


Nuclear InteracionsNuclear Interacions• p,±,K± production points

xy view zR view

R distribution d0 distribution

NO B field propagation!


Nuclear Interacions (at least 2 Nuclear Interacions (at least 2 prong)prong)

• (at least) 2-prong p,±,K± vertexes selectedxy view zR view




Nuclear Interacions (at least 3 Nuclear Interacions (at least 3 prong)prong)

• (at least) 3-prong p,±,K± vertexes selectedxy view zR view




Tracker layers’ radiiTracker layers’ radii


D0 from V0ProducerD0 from V0Producer


Phi from V0ProducerPhi from V0Producer


J/Psi from V0ProducerJ/Psi from V0Producer


Last CMS WEEK Last CMS WEEK announcementannouncement

• Available (but non standard) in 2_2_X

• NOT available in 2_2_X


Old/new tracking Old/new tracking comparisoncomparison

• Test on 500 events with V0Producer (K0s

reconstruction)– The difference in production radius distribution is

impressive!– Needs to be run on RAW

• 3-4 SECONDS PER EVENT…Red – old tracking algorithmBlack - new tracking algorithm


BACKUPBACKUPSLIDESSLIDES


• Pt/Pt distribution with/without R cut

Reco Reco pp(from (from )) association association cutscuts

Black: without cutRed: with cut

or protons


CDF analysis highlightsCDF analysis highlights• Motivations

– Large compared to NLO QCD expectation when measured with muons PRD 69, 072004 (2004)

– Time-integrated mixing probability larger than e+e- resultPRD 69, 012002 (2004)

– Low-mass dilepton spectrum inconsistent with QCD expectations from heavy flavorPRD 72, 072002 (2005)

• Results– There is an unexpected

sample of muons which do not give hits in the first two silicon layers (r<2.5 cm) and which have a very large impact parameter (IP); hereafter called “ghost” muons (fanciful term).

– The size of the ghost sample is about the same as the bb sample.

– Around ghost muons, additional ones are found with similar characteristics

• Known sources• Ghost excess

bb


Analysis Plan (I)Analysis Plan (I)• Check track reconstruction efficiency for

tracks with large Impact Parameter (IP)– MC study of track reconstruction efficiency vs IP,

vs radius of production point– Validation on data using tracks from Ks decay– Choose most suitable tracking algorithm

• Check resolution in IP determination– Measure in data with dimuon resonances

• Check IP, Pt distribution from most relevant sources of reconstructed muons of choice (GM?)– Punch through (PT)– Decays in flight– Semileptonic B,D decays

} Data control

samples

K0s→+-

→K+K-

pD0 →+K-


Analysis Plan (II)Analysis Plan (II)• Study secondary tracks from nuclear

interactions and their contributions to IP tails• Compute expected background rate in well-

defined IP/Pt region

• Jump on data!

• Technical points:– there is no impact parameter for genPs

• We used linear extrapolation back to primary vertex

– GenPs are reconstructed before GEANT detector simulation• We used K. Ulmer private code to recover DIF and nuclear

interactions

Muon fake rates: a systematical approach

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