muon fake rates: a systematical approach
Post on 03-Jan-2016
32 Views
Preview:
DESCRIPTION
TRANSCRIPT
04-05-2009 CMSSWPD meeting - Luca Perrozzi 1
Muon fake rates:Muon fake rates:a systematicala systematical
approachapproach
04-05-2009 CMSSWPD meeting - Luca Perrozzi 2
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
04-05-2009 CMSSWPD meeting - Luca Perrozzi 3
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
04-05-2009 CMSSWPD meeting - Luca Perrozzi 4
Reco Reco (from Ks)(from Ks) association cutsassociation cuts
Pt/Pt<0.01
R|<0.01
Pt/Pt vs |R|
2 2R
04-05-2009 CMSSWPD meeting - Luca Perrozzi 5
KK00ss case case
V0 moduleoutput
04-05-2009 CMSSWPD meeting - Luca Perrozzi 6
Phi distributions forPhi distributions for and and - - Stage IStage I
Black: Signal regionViolet: Bkg region
Muons associated to Pions
Log scale!
Pions
Black: Signal regionViolet: Bkg region
• Select Pi tracks from K0
s mass signal and background region, then look for associated
04-05-2009 CMSSWPD meeting - Luca Perrozzi 7
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
04-05-2009 CMSSWPD meeting - Luca Perrozzi 8
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
Muons associated to pions in K0
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
04-05-2009 CMSSWPD meeting - Luca Perrozzi 9
00pp case case
V0 moduleoutput
04-05-2009 CMSSWPD meeting - Luca Perrozzi 10
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
Signal – Bkg for Muons 124
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
NB: large muon fraction in sidebands requires larger Bkg sidebands to reduce statistical errors !!!
04-05-2009 CMSSWPD meeting - Luca Perrozzi 11
KK++KK case case
Made“by hand”
04-05-2009 CMSSWPD meeting - Luca Perrozzi 12
KK++KK fake rate summary fake rate summaryPions in K0
s mass signal region 448996
Pions in K0s mass bkg
region 354756
Signal – Bkg for Pions 94240
Muons associated to pions in K0
s mass signal region 10809
Muons associated to pions in K0
s mass bkg region 7354
Signal – Bkg for Muons 3455
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
NB: large muon fraction in sidebands requires larger Bkg sidebands to reduce statistical errors !!!
04-05-2009 CMSSWPD meeting - Luca Perrozzi 13
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
04-05-2009 CMSSWPD meeting - Luca Perrozzi 14
Muon selectors efficiencies & Muon selectors efficiencies & puritypurity
04-05-2009 CMSSWPD meeting - Luca Perrozzi 15
PAT vs LastStation muons (I)PAT vs LastStation muons (I)
Black: Signal regionViolet: Bkg region
Muons associated to Pions
• Select Pi tracks from K0s mass signal and background region, then look for associated
Black: Signal regionViolet: Bkg region
Muons associated to Pions
PAT muons Last station muons
Pt distribution after Sig-Bkg
Black: PionsRed: Muons
PAT muons
Pt distribution after Sig-Bkg
Black: PionsRed: Muons
Last station muons
04-05-2009 CMSSWPD meeting - Luca Perrozzi 16
PAT vs LastStation muons PAT vs LastStation muons (II)(II)
Fake rate as a function of Pt
PAT muons Last station muons
Fake rate as a function of Pt
Using LastStation muons statistics decreases dramatically! (factor ~5)
Black: Signal regionViolet: Bkg region
Muons associated to Pions
Black: Signal regionViolet: Bkg region
Muons associated to Pions
PAT muons Last station muons
impact parameter distribution doesn’t change significantly
04-05-2009 CMSSWPD meeting - Luca Perrozzi 17
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
04-05-2009 CMSSWPD meeting - Luca Perrozzi 18
KK00ss case case
• Sum of 2 gaussian fits perfectly mass distribution shape
•Need to redefine
New FIT!
Old FIT!
04-05-2009 CMSSWPD meeting - Luca Perrozzi 19
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
04-05-2009 CMSSWPD meeting - Luca Perrozzi 20
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
04-05-2009 CMSSWPD meeting - Luca Perrozzi 21
Background sidebands Background sidebands extensionextension
Bkg/Sig = 5
Bkg/Sig = 1
04-05-2009 CMSSWPD meeting - Luca Perrozzi 22
Nuclear InteracionsNuclear Interacions• p,±,K± production points
xy view zR view
R distribution d0 distribution
NO B field propagation!
04-05-2009 CMSSWPD meeting - Luca Perrozzi 23
Nuclear Interacions (at least 2 Nuclear Interacions (at least 2 prong)prong)
• (at least) 2-prong p,±,K± vertexes selectedxy view zR view
R distribution d0 distribution
NO B field propagation!
04-05-2009 CMSSWPD meeting - Luca Perrozzi 24
Nuclear Interacions (at least 3 Nuclear Interacions (at least 3 prong)prong)
• (at least) 3-prong p,±,K± vertexes selectedxy view zR view
R distribution d0 distribution
NO B field propagation!
04-05-2009 CMSSWPD meeting - Luca Perrozzi 25
Tracker layers’ radiiTracker layers’ radii
04-05-2009 CMSSWPD meeting - Luca Perrozzi 26
D0 from V0ProducerD0 from V0Producer
04-05-2009 CMSSWPD meeting - Luca Perrozzi 27
Phi from V0ProducerPhi from V0Producer
04-05-2009 CMSSWPD meeting - Luca Perrozzi 28
J/Psi from V0ProducerJ/Psi from V0Producer
04-05-2009 CMSSWPD meeting - Luca Perrozzi 29
Last CMS WEEK Last CMS WEEK announcementannouncement
• Available (but non standard) in 2_2_X
• NOT available in 2_2_X
04-05-2009 CMSSWPD meeting - Luca Perrozzi 30
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
04-05-2009 CMSSWPD meeting - Luca Perrozzi 31
BACKUPBACKUPSLIDESSLIDES
04-05-2009 CMSSWPD meeting - Luca Perrozzi 32
• Pt/Pt distribution with/without R cut
Reco Reco pp(from (from )) association association cutscuts
Black: without cutRed: with cut
or protons
04-05-2009 CMSSWPD meeting - Luca Perrozzi 33
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
04-05-2009 CMSSWPD meeting - Luca Perrozzi 34
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-
04-05-2009 CMSSWPD meeting - Luca Perrozzi 35
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
top related