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The study of ๐โฒ โ ๐+๐โ๐๐0,1,2
Zhang Jielei Zhang Jingzhi
Outline
1ใMotivation
2ใData sets
3ใThe study of ๐โฒ โ ๐+๐โ๐๐0,1,2
Event selection
Data and Background study
Data and MC distributions
4ใSummary
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Motivation
In theory, the transition process ๐โฒ(โฒ) โ ๐พ๐๐๐ฝ is not consistent with experiment measurement very well.
Q. Zhao et al consider open charm effects, many channels can consistent with experiment measurement very well except for ๐โฒ โ ๐พ๐๐2.
In the process ๐โฒ โ ๐+๐โ๐๐๐ฝ, ๐+๐โ from a virtual photon. To study the process can
provide more information for theory. Furthermore, we can get the distribution of form factor, from the distribution we can extract parameters as theoretical input.
Data sets
Boss Version : 6.6.4-p03
Data sets :
Signal MC :
๐โฒ โ ๐+๐โ๐๐0,1,2(DIY), ๐๐0,1,2 โ ๐พ๐ฝ/๐, ๐ฝ/๐ โ ๐+๐โ/๐+๐โ
Inclusive MC (2009 and 2012 ๐โฒ MC)
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106 M ๐โฒ of year 2009341.5 M ๐โฒ of year 2012continuum background study : ~44pbโ1 data @ 3650
Background MC :
1.๐โฒ โ ๐พ๐๐0,1,2, ๐๐0,1,2 โ ๐พ๐ฝ/๐, ๐ฝ/๐ โ ๐+๐โ/๐+๐โ
2.๐โฒ โ ๐๐ฝ/๐, ๐ โ ๐พ๐พ, ๐ฝ/๐ โ ๐+๐โ/๐+๐โ
3.๐โฒ โ ๐/๐0๐ฝ/๐, ๐/๐0 โ ๐พ๐+๐โ, ๐ฝ/๐ โ ๐+๐โ/๐+๐โ
Event selections
Charged tracks- ๐ ๐ฅ๐ฆ < 1๐๐, ๐ ๐ง < 10๐๐
- ๐๐๐ ๐ < 0.93- ๐ = 4, ๐ = 0
Good photon- 0 โค ๐๐ท๐ถ โค 14- Barrel :๐ธ > 0.025 GeV, ๐๐๐ ๐ < 0.8
- Endcap :๐ธ > 0.050 GeV, 0.86 < ๐๐๐ ๐ < 0.92
- โ๐ > 200
- ๐๐พ โฅ 1
Particle separation- ๐ from ๐โฒ โถ ๐๐๐๐ < 1 GeV- ๐ from ๐ฝ/๐ โถ ๐๐๐๐ > 1 GeV&&๐ธ๐๐๐ >1 GeV- ๐ from ๐ฝ/๐ โถ ๐๐๐๐ > 1 GeV&&๐ธ๐๐๐ <0.4 GeV
4C kinematic fit- Choose the photon with least ๐2
- ๐4๐ถ2 < 40
Other selections- ๐ฝ/๐ mass window : (3.08, 3.12) GeV- 0.16 < ๐ ๐พ๐+๐โ < 0.50 GeV- ๐ ๐ฅ๐ฆ < 1.5||๐ ๐ฅ๐ฆ > 7.0 cm
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๐4๐ถ2 of kinematic fit
๐2 distribution from 4C : ๐4๐ถ2 < 40
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๐ฝ/๐ invariant mass distributions7
๐ฝ/๐ mass window : 3.08 < ๐ ๐+๐โ < 3.12 GeV
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Background study
The main background :
1.๐โฒ โ ๐พ๐๐0,1,2, ๐๐0,1,2 โ ๐พ๐ฝ/๐, ๐ฝ/๐ โ ๐+๐โ/๐+๐โ
2.๐โฒ โ ๐๐ฝ/๐, ๐ โ ๐พ๐พ, ๐ฝ/๐ โ ๐+๐โ/๐+๐โ
3.๐โฒ โ ๐/๐0๐ฝ/๐, ๐/๐0 โ ๐พ๐+๐โ, ๐ฝ/๐ โ ๐+๐โ/๐+๐โ
๐พ conversion
Same final state
๐ ๐ฅ VS ๐ ๐ฆ distributions9
Background(๐พ๐1)
Background(๐พ๐2)
DATA(๐1)
DATA(๐2)
Some variables from GammaConv package.
MC(๐1)
MC(๐2)
๐พ conversion MC
in ๐๐1 region
in ๐๐2 region
๐ ๐ฅ๐ฆ distributions10 Remove ๐พ conversion background
๐ ๐ฅ๐ฆ < 1.5||๐ ๐ฅ๐ฆ > 7.0 cm
From ๐พ conversion MC, there are no events in the region. These events have large angle between ๐+ and ๐โ. For signal MC, if the ๐+
and ๐โ have large angle, the event will be reconstructed in the region.
๐พ conversion events
๐(๐พ๐+๐โ) distributions11
0.16 < ๐ ๐พ๐+๐โ < 0.50 GeV
Remove ๐โฒ โ ๐/๐0๐ฝ/๐, ๐/๐0 โ ๐พ๐+๐โ, ๐ฝ/๐ โ ๐+๐โ/๐+๐โ process
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Background study
From inclusive MC, we find only one events survived.
From 44 pbโ1 3650 data sample, only one event survived the event selections.
๐(๐พ๐ฝ/๐) distributions13
Clear ๐๐1 and ๐๐2 signal, and some ๐๐0 signal
๐โฒ โ ๐พ๐๐๐ฝ , ๐๐๐ฝ โ ๐+๐โ๐ฝ/๐ process
๐ ๐(๐+๐โ) distributions14
๐+๐โ recoiling invariant mass distribution ๐ ๐(๐+๐โ)
(before 4C kinematic fit)
Clear ๐๐1 and ๐๐2 signal, and some ๐๐0 signal
๐๐+๐โdistributions15
The angular distribution between ๐+ and ๐โ in ๐๐1
and ๐๐2 signal region
Momentum distributions16
๐+ and ๐โ momentum distribution in ๐๐1 and ๐๐2
signal region
๐๐๐ ๐ distributions17
๐+ and ๐โ ๐๐๐ ๐ angular distribution in ๐๐1 and ๐๐2
signal region
Invariant mass distributions18
๐(๐+๐โ), ๐(๐+๐๐1,2) and ๐(๐โ๐๐1,2) distribution in ๐๐1
and ๐๐2 signal region
Helicity ๐๐๐ ๐ distributions19
๐+ and ๐โ helicity angular distribution in ๐๐1 and ๐๐2
signal region
Scatter plots20
๐๐+๐โ VS ๐ ๐ฅ๐ฆ, ๐(๐+๐โ) VS ๐ ๐ฅ๐ฆ and ๐๐+๐โ VS ๐(๐+๐โ)
distributions for data.
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Signal extraction from data
Signal : MC-determined shape to describe signal ๐๐0,1,2, the ๐๐๐0,1,2 is float
Background : 1ใ1-st order polynomial, the ๐๐๐๐1 are float2ใ๐โฒ โ ๐พ๐๐0, ๐๐0 โ ๐+๐โ๐ฝ/๐ process MC-determined shape, the ๐๐๐๐2 are float
๐๐๐0 = 62 ยฑ 10 ๐๐๐1 = 884 ยฑ 30 ๐๐๐2 = 229 ยฑ 16
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Summary
1ใThe process ๐โฒ โ ๐+๐โ๐๐0,1,2 is studied, there are clear ๐๐1 and ๐๐2signal and some ๐๐0 signal.
2ใThe most of events focus on the small angle between ๐+ and ๐โ, and there are some events focus on the large angle between ๐+ and ๐โ, these events canโt be understood.
3ใThe process ๐๐๐ฝ โ ๐+๐โ๐ฝ/๐ also be observed.
Next to do1ใFurther analysis of the background
2ใStudy generator to get more accurate efficiency for data and give branching fraction
3ใStudy the process ๐๐๐ฝ โ ๐+๐โ๐ฝ/๐ in detail
Thanks for your attention!
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BACK UP
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Some distributions for large angle between ๐+ and ๐โ
๐(๐พ๐ฝ/๐) ๐2
๐+ track ๐2 ๐โ track ๐2
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Efficiency curve
26 Some events for large angle between ๐+ and ๐โ
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Branching fraction
โฌ ๐โฒ โ ๐+๐โ๐๐0,1,2 =๐๐๐0,1,2
๐๐ก๐๐ก โ โฌ(๐๐0,1,2 โ ๐พ๐ฝ/๐) โ โฌ(๐ฝ/๐ โ ๐+๐โ) โ ๐0,1,2
โฌ ๐โฒ โ ๐+๐โ๐๐1 = (5.9 ยฑ 0.2) ร 10โ4
โฌ ๐โฒ โ ๐+๐โ๐๐2 = (6.2 ยฑ 0.5) ร 10โ4
1. ๐0 = 11.7%
2. ๐1 = 8.1%
3. ๐2 = 3.5%
โฌ ๐โฒ โ ๐+๐โ๐๐0 = (6.7 ยฑ 1.3) ร 10โ4
Need further studyPHSP MC