09-03-2009PDCMSSW - Luca Perrozzi1 Looking for… Punch throughs… Looking for… Punch throughs…

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Presentation transcript:

PDCMSSW - Luca Perrozzi1 Looking for… Punch throughs… Looking for… Punch throughs…

PDCMSSW - Luca Perrozzi2 Summary Searching for K 0 s →     and  →     punch through rates as a function of: P t Eta Impact parameter Phi 240K events analysis (BCtoMu sample from LNL) –8 files: QCD_BCtoMu_Pt30to50_PAT_30000ev_Xover8.V0.g4.root (X=1..8) available on /raid4/perrozzi/PAT_production/ Framework used: CMSSW_2_2_3 V0 producer module

PDCMSSW - Luca Perrozzi3 K 0 s selection Invariant mass fit (m= 498 MeV, σ  6.5 MeV) –2.8  window for signal & background signal background (GeV) Counts

PDCMSSW - Luca Perrozzi4 Strategy Pi tracks from K 0 s Signal Reco K0s Pi tracks from K 0 s Background Reco Mu Mu associated to Pi track from K0s Signal Mu associated to Pi track from K0s Background  R<0.01  Pt<0.01  R<0.01  P t <0.01 Sig - Bkg Pi Rate Mu Rate Mu/Pi Pi (from K 0 s ) punch through (as function of Pt, Eta, Phi,dxy, decay length)

PDCMSSW - Luca Perrozzi5 K 0 s RecoPi-RecoMu track association   R<0.01  P t /P t |<0.01   R(cm) Counts  P t /P t

PDCMSSW - Luca Perrozzi6 K 0 s Pi Punch through vs. Pt Red: Muon Black: Pi Distributions before ratio Increases with P t As aspected! Meaningless after 10 GeV More statistics needed! Log scale!

PDCMSSW - Luca Perrozzi7 K 0 s Pi Punch through vs. Eta Red: Muon Black: Pi Distributions before ratio Shows hadronic calorimeter “holes”at  ~2 More statistics needed! Log scale!

PDCMSSW - Luca Perrozzi8 K 0 s Pi Punch through vs. dxy Red: Muon Black: Pi Distributions before ratio Decreases with dxy To be well understood Meaningless after 0.4 cm More statistics needed! Log scale!

PDCMSSW - Luca Perrozzi9 K 0 s Pi Punch through vs. Phi Log scale! Red: Muon Black: Pi Reasonably flat Can be used as reference plot More statistics needed! Distributions before ratio Pi punch through probability ~ 0.6%

PDCMSSW - Luca Perrozzi10  selection (part I) Invariant mass best cut selection with significance maximization: –  2 track <2 –P t >1.0 GeV –dxy< (less important) Significance =

PDCMSSW - Luca Perrozzi11  selection (part II) Invariant mass fit (m= 1.02 GeV, σ  MeV) –2.8  window for signal & background signal background Mass (GeV) Counts

PDCMSSW - Luca Perrozzi12 Strategy K tracks from  Signal Reco K0s K tracks from  Background Reco Mu Mu associated to K track from  Signal Mu associated to K track from  Background  R<0.01  Pt<0.01  R<0.01  P t <0.01 Sig - Bkg K Rate Mu Rate Mu/K K (from  ) punch through (as function of Pt, Eta, Phi,dxy, decay length)

PDCMSSW - Luca Perrozzi13  RecoK-RecoMu track association   R<0.01  P t /P t |<0.01   R(cm) Counts  P t /P t LOG SCALE!

PDCMSSW - Luca Perrozzi14  ’s K Punch through vs. Pt Log scale! Red: Muon Black: K Distributions before ratio Increases with P t What happens after 10 GeV? Meaningless after 20 GeV More statistics needed!

PDCMSSW - Luca Perrozzi15  ’s K Punch through vs. Eta Log scale! Red: Muon Black: K Distributions before ratio Shows hadronic calorimeter “holes”at  ~2 More statistics needed!

PDCMSSW - Luca Perrozzi16  ’s K Punch through vs. dxy Log scale! Red: Muon Black: Pi Distributions before ratio Increases with dxy To be well understood Cut at 4.5 cm to select  More statistics needed!

PDCMSSW - Luca Perrozzi17  ’s K Punch through vs. phi Log scale! Red: Muon Black: K Reasonably flat Can be used as reference plot More statistics needed! Distributions before ratio Pi punch through probability ~ 3.6% Factor 10 more than Pi!

PDCMSSW - Luca Perrozzi18 Summary Punch through probability: –From Pi seems to be around 0.6% –From K seems to be around 3.6% A factor 10 between the two particles Distribution behaviors: –Some as aspected Phi Eta –Some to be understood dxy Pt MORE STATISTICS NEEDED!!!

PDCMSSW - Luca Perrozzi19 Next steps Include lambda particles Automatize Phi particle reconstrction in V0 producer module Increase statistics (at least 1M events) Better understand distribution behaviors

PDCMSSW - Luca Perrozzi20 On demand slides

PDCMSSW - Luca Perrozzi21 Significance F = N s + N b – N c Se N B =N C S+B C