Observation of. San-Qiang Qu Ming-gang Zhao Hai-long Ma Nankai University Institute of High Energy Physics

Transcription

1 Observation of CJ an-qiang Qu Ming-gang Zhao Hai-long Ma Nankai University Institute of High Energy Physics

2 Outline 1 Motivation Data sample 3 Event selection 4 Branching fraction 5 ummary

3 Motivation Theoretical work indicates that the color octet mechanism could have large contributions to the decays of the P-wave charmonium states. However, Many theoretical calculations and experimental measurements still have large errors. more precise experimental data besides more theoretical efforts are mandatory to further understand Thus, the measurement of as many exclusive hadronic possible is valuable. First observations of CJ CJ decay dynamics. CJ decay as 1

4 Data ample 1. DATA : 447.9M Ψ(3686) (16.8M(9) M(1)). Inclusive MC : 56M Ψ(3686) (16M(9) + 4M (1)) (3686 ) anything 3. Exclusive MC : (PGC/PGC1/PGC PHP) 1 for J =,1, 1 for 1 for ThemeGallery is a Design Digital ( 3686) Content & Contents mall CJ _ developed by Guild Design Inc. * ( 3686) f(171) _ * ( 3686) f ' Boss Version: 6.6.4

5 Event selection Charged track selection : 1. cosθ <.93. Momentum cut : P <.Gev 3. Charge cut : Q = 1 ; um(q) = 4. ngood = 8 reconstruction : 1. econd vertex fit applied. DecayLength/DecayLengthError > <.1GeV M 4. n = 4 3

6 Event selection Good photon : 1. The timing information of the EMC should be within t 14 (in the unit of 5 ns).. The deposited energy should be larger than 5 MeV in the endcap cos θ <.8 and larger than 5 MeV in the barrel (.86< cosθ <.9); 3. The angle between the photon and the nearest charged track must be larger than to distinguish the shower from charged particles inematicfit If more than one combination survived in one event, the one with the smallest is retained. 4

7 reconstruction 5

8 CJ candidates after event selection 6

9 Backgrounds No. Decay Chain Final states nevt Total: Total: f f,, ' ' _ * ' _ * ' f f, (171) (171), ' _ * _ * ' Table1: topological analysis for Inclusive MC 7

10 Backgrounds Distribution of invariant mass of backgrounds 8

11 9 Backgrounds

12 1 Backgrounds

13 11 Comparison of M

14 1 Comparison of momentum

15 13 Comparison of cosθ

16 Comparison of M Update 14

17 Fitting Update 1. ignal shape: Breit-Wigner convoluted with double Gaussian, where the widths are fixed to the PDG value and resolution is not fixed.. Background shape: polynomial function 15

18 Branching fraction Update obs N B( CJ 4 ) 4 N B( (3686) ) B ( (3686) CJ ) CJ obs 4 N Efficiency [%] ignificance B. F [1 ] C C C notes: FCN1: fitting data ignificance loge( ( FCN1 FCN)) FCN: fitting data without the corresponding peak

19 ystematic uncertainty Update [%] [%] [%] Description ψ(3686) total numbers.8 CPC37 (13) 631 γ detection efficiency 1. PRD83-16 C C 1 C Reconstruction of 6. PRD9-71 MC model following slide inematic fit following slide Fitting range following slide ignal shape following slide MC statistics binomial ' CJ B( ) PDG16 B( ).3 PDG16 Total Add in quadratic 17

20 ystematic uncertainty 1. Reconstruction of We use the same data-mc different of selection criteria as used in PRD9-71. The reconstruction is studied in PRD9-71 and shown below. The fit give the fitted data-mc difference to be ( assign 1.5% as systematic uncertainty per )%. o we the uncertainty includes differences between data and MC in tracking efficiency, 18 decay length cut, mass spectra cut, vertex and second vertex fitting.

21 ystematic uncertainty Update. MC model The uncertainty in MC model is assigned by comparing the MC efficiencies 19 with the ones involving possible sub-resonances. C C C Channel [%] [%] [%] CJ CJ f ( 15) f(15) CJ f (15 ) ' CJ f (155 ) CJ f ' (15 ) f (155 ) CJ f ( 15) f(171 ) CJ f (1565 ) CJ f ( 15) f(1565) ' CJ f ( 155) f (1565) systematic uncertainty

22 ystematic uncertainty 3. inematic fit systematic error The uncertainty is assigned by the difference of the branching fractions measured with and without cuts. In the case of no cut, the infit 1 9 is set to be. signal eff [%] B.F.[%] signal eff [%] B.F. [%] signal eff [%] B.F. [%] no infit err C C1 C Update

23 ystematic uncertainty Update Too loose the 8 pions. cut may lead to too many mis-combinations among C Figure: efficiency fitting for under different cut 1

24 ystematic uncertainty Update 4. Fitting range The uncertainty is estimated by comparing the branching fractions with the alternative fit ranges of C C 1 C Range signal eff [%] B.F. [%] signal eff [%] B.F. [%] signal eff [%] B.F. [%] [3.3, 3.59] [3.3, 3.6] [3.3, 3.61] [3.3, 3.6] [3.8, 3.6] [3.9, 3.6] [3.31, 3.6] [3.3, 3.6] range err [%]

25 Update ystematic uncertainty 5. ignal shape The uncertainty is obtained by comparing the branching fractions measured with the signal shapes of Breit Wigner convolution double Gaussian(left figure) and PDF generated by the MC histogram convolution Gaussian(right figure). 3 signal shape signal eff [%] B.F. [%] signal eff [%] B.F. [%] signal eff [%] B.F. [%] BW with double Gauss MC pdf with Gauss C C 1 C uncertainty

26 ummary Update The decays of CJ fractions are measured for the first time. are observed and their decay branching 4 B. F [1 ] CJ C C1 C

27 Thank you!!

28 Backup Cosθ of CJ in MCtruth check efficiency of C

29 Cosθ of CJ in MCtruth 5

30 Cosθ of CJ in MCtruth 6

31 Check efficiency of C Update We found the efficiency decreased when inematic fit restricted. o we check the histogram of MC simulation for we get the result. CJ is not, and then range no cut entries < entries C [ ] [ ] C1 [ ] [ ] C [ ] [ ]