a.bozek t.lesiak inp krakow
DESCRIPTION
A.Bozek T.Lesiak INP Krakow. Selection criteria. Statistics: experiments 7 ,9,11,15,17 Track selection: PID: Kaon: Pion: Phi: B:. Continuum rejection. Fisher discriminant (9 variables) : - Fox Wolfram: so: 2,4 oo: 2 -4 - sphericity - angles (cosines): - PowerPoint PPT PresentationTRANSCRIPT
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A.Bozek
T.Lesiak
INP Krakow
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Selection criteria
• Statistics: experiments 7,9,11,15,17
• Track selection:
• PID:
Kaon: Pion:
• Phi:
• B:
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• Fisher discriminant (9 variables):
- Fox Wolfram: so: 2,4 oo: 2-4
- sphericity
- angles (cosines):
• Reject event if discriminant < 1.0
Efficiency: 92.8%(5K), 83.4%(K),85.5%( cK), 69.5%(cK*)
Continuum rejection: 58.1%(5K), 71.1%(5K)
• Fisher discriminant (9 variables):
- Fox Wolfram: so: 2,4 oo: 2-4
- sphericity
- angles (cosines):
• Reject event if discriminant < 1.0
Efficiency: 92.8%(5K), 83.4%(K),85.5%( cK), 69.5%(cK*)
Continuum rejection: 58.1%(5K), 71.1%(5K)
Continuum rejection
thrT ,,B
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Continuum rejection
data cont
data
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MC 10000 events
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M(KK) GeV
• 6 M(KK) hypothesis• If
• Only two other hypothesis M(KK) are left• Both are are combine two one histogram•Each B candidate has two entries, eventual fit should take it into account•Signal from rezonanses is compose of BW + feedacross to other KK combination see later ….
M(X) from X
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M(KKKK) GeV
M(KKKK) GeV
M(KKKK) GeV
•We have 3 mass combination for 4K hypothesis•Fortunatly due to kienamtics only in one eventual rezonaces are going to show up.•One excluding the fastest Kaon
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GeV
True from kaons pair comb.
Wrong kaons pair comb.
M(X) from X
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M() GeV
M() GeV
4K mass
• No intermediate
•At least one
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GeV
M(X) from X
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4K mass
• No intermediate
•At least one
One event
~900 events
M() GeV
M() GeV
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MC 40000 events
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M(X) from X
GeV
M() GeV
M() GeV
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GeV
M(X) from X
Exps 7,9,11,15,17 only
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Exps 7,9,11,15,17 only
M() GeV
M() GeV
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Exps 7,9,11,15,17 only
GeV
M(X) from X
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Exps 7,9,11,15,17 only
M() GeV
M() GeV
14 events pass selection criterias