3 )measurementbyB S π DK* atBelleepx.phys.tohoku.ac.jp/eeweb/meeting/201502_LLWI_negishi.pdf · φ...

φ3(γ) measurement by B0→[KS0π+π−]D K*0 at Belle

Kentaro Negishi 19th February 2015 Lake Louise

1

Lake Louise Winter Ins/tute

Introduc?on

•  CKM (Cabibbo-‐Kobayashi-‐Maskawa) matrix –  The quark mixing matrix, which is unitary.


3

3q

2q

2q

dm6

K¡

K¡sm6 & dm6

ubV

1qsin 2

(excl. at CL > 0.95) < 0

1qsol. w/ cos 2

2q

1q

3q

l-0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

d

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7ex

clud

ed a

rea

has

CL

> 0.

95

Summer 14

CKMf i t t e r

•  Unitary triangle

Complex phase

CKMfiCer 2014 Summer

φ3 Measurement

B0 → [ f ]D K*0


4

–  Access φ3 with interference D0K*0 and D0K*0 decays. Weak Int. phase Strong Int. phase Amp.

Difference between D0K*0 and D0K*0 φ3 δS rS

W!

b

d d

B0sK"0

u

cD0Vub

W!

b

d d

B0sK"0

c

uD0→ f → f

(No penguin)

rS is crucial parameter in φ3 measurement. (Expected to be ~0.3.)

_ _

_ _ _

Ø  B flavor can be decided by the charge of K from K*0. Br(K*0 → K+π−) = 2/3

_

Dalitz Analysis Method

•  Measure B0/B0 asymmetry across Dalitz plot. – D is required to decay in to three body like KS0π+π−.


5

•  Sensi/vity to φ3 in interference term. –  |f(m2

+, m2−)| from flavor-‐tagged D*+→D0π+ events.

–  Phase difference(δD) between D0/D0 from Charm-‐Factory.

_

_

D0 _

D0

←

B

m+2 m+

2

m−2

m−2

Model-‐Independent Dalitz 19th Feb. '15 LLWI’15 K.Negishi

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[A. Giri, Y. Grossman, A. Soffer, J. Zupan, PRD 68, 054018 (2003)]

where observables

i

-i

Number of events in D0-‐plot : Ki

Number of events in B-‐plot :

From Charm-‐Factory

Belle Experiments KEKB accelerator

•  Asymmetric energy collision –  (8.0 v.s. 3.5 GeV)

•  10.58 GeV center of mass energy at Υ(4S) resonance; It is suitable for BB produc/on.

•  772 × 106 BB pair

•  Charged par/cle momentum (σpt/pt(%) = 0.19pt + 0.30β)

•  Good par/cle iden/fica/on ((K/π) Eff. ~90%, Fake ~10%)

•  Good vertex resolu/on (~50 µm)


7

Belle detector

○

Signal and Backgrounds 19th Feb. '15 LLWI’15 K.Negishi

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Signal

•  Light quark jets (u,d,s,c). •  Random mis-‐reconstruc/on

makes fake signal candidate.

•  Other B decay modes. •  Difficult to dis/nguish from signal.

•  D true BB BG •  D fake BB BG

•  1 mis-‐PID π as K •  D0ρ0

•  1mis-‐PID and 1 lost π •  D0a1+

Rejec/on Use decay shape difference. Signal : spherical decay qq BG : 2 jet-‐like decay Neural network is used for mul/ variable analysis.

qq BG

BB BG

Peaking BG

B0 K*0

D

K+

KS π−

π− π+

(B flavor specific)

resonant π+

π−

e+e− → qq q = u,d,s,c

_

BB event qq event

3D Fit for Signal Extrac?on 19th Feb. '15 LLWI’15 K.Negishi

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E (GeV)"6A RooPlot of " E (GeV)"6A RooPlot of "

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"TRANSA RooPlot of "NB "TRANSA RooPlot of "NB

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"bcA RooPlot of "M "bcA RooPlot of "M

C’NB

Energy difference btw. beam energy and B candidate.

Modified distribu/on of Neural network output used qq suppression.

Mass of B candidate from beam energy and B’s momentum.

BB like qq like

[GeV] [GeV]

Ayer reconstruc/on and BG rejec/on, 3-‐D fit (ΔE, C’NB, Mbc) is done without Dalitz informa/on. Each component yield is free. Shapes are fixed.

Yield is Ntotal = 44.2 (sta/s/c significance 2.8 σ), which are used for the (x,y) fit.

+ 13.3 − 12.1

Red : Signal　　　Green : D0a1+　Blue : D fake BB　Light blue : D true BB　Magenta : qq

E (GeV)6-0.1 -0.05 0 0.05 0.1 0.15

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2+m0.5 1 1.5 2 2.5 3

2 -m

0.5

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Phase binsPhase bins

From CLEO

(x,y) Fit 19th Feb. '15 LLWI’15 K.Negishi

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…

N1.

N2.

Ki from D*+→D0π+, D0 decay

y

x

(x!, y!)

(x+, y+)

!3!3

"

rS

rS

PRD 82, 112006 (2010)

Obtain the signal number,

Obtain the signal number,

(x, y) Result BG frac/ons btw bins for each component are fixed from MC.


11

E (GeV)6-0.1 0 0.1 0.2 0.3

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0Bbin -6

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3 = 0.9iN

0Bbin +8

x− = + 0.4 ± 0.0 y− = − 0.6 ± 0.1 x+ = + 0.1 ± 0.1 y+ = + 0.3 ± 0.1

+ 1.0 + 0.0 − 0.6 − 0.1 + 0.8 + 0.1 − 1.0 − 0.0 + 0.7 + 0.0 − 0.4 − 0.1 + 0.5 + 0.0 − 0.8 − 0.1

stat. syst. ci, si

(x, y) Result 19th Feb. '15 LLWI’15 K.Negishi

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X-2 -1.5 -1 -0.5 0 0.5 1 1.5 2Y-2

-1.5-1

-0.50

0.51

1.52

CL

CO

MB.

0

0.2

0.4

0.6

0.8

1

X-2 -1.5 -1 -0.5 0 0.5 1 1.5 2

Y

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

x− = + 0.4 ± 0.0 y− = − 0.6 ± 0.1 x+ = + 0.1 ± 0.1 y+ = + 0.3 ± 0.1

+ 1.0 + 0.0 − 0.6 − 0.1 + 0.8 + 0.1 − 1.0 − 0.0 + 0.7 + 0.0 − 0.4 − 0.1 + 0.5 + 0.0 − 0.8 − 0.1

stat. syst. ci, si

B0

_

B0

Dot : Most probable point Line : 1σ contour

(x, y) Result 19th Feb. '15 LLWI’15 K.Negishi

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X-2 -1.5 -1 -0.5 0 0.5 1 1.5 2Y-2

-1.5-1

-0.50

0.51

1.52

CL

CO

MB.

0

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1

X-2 -1.5 -1 -0.5 0 0.5 1 1.5 2

Y

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

δS 2φ3

x− = + 0.4 ± 0.0 y− = − 0.6 ± 0.1 x+ = + 0.1 ± 0.1 y+ = + 0.3 ± 0.1

+ 1.0 + 0.0 − 0.6 − 0.1 + 0.8 + 0.1 − 1.0 − 0.0 + 0.7 + 0.0 − 0.4 − 0.1 + 0.5 + 0.0 − 0.8 − 0.1

stat. syst. ci, si

B0

_

B0

Dot : Most probable point Line : 1σ contour

(x+, y+) (B0) is 0 consistent.

Sr0 0.5 1 1.5 2

1 - C

.L.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

rS Result •  rS is crucial parameter in φ3 measurement.

–  φ3 uncertainty is scaled as 1/r.


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rS < 0.87 @ 68 % C.L. rD2 = (3.79±0.18)10-‐3 rD is small.

rS < 0.4 → RDK* ~ rS2

B0→[Kπ]DK*0 PRD 86 , 011101 (2012)

　　Blue : B0 (x−, y−) 　　Red : B0 (x+, y+) 　　Black : Combine

_

rS

Conclusion

•  New result of B0→[KS0π+π−]DK*0 Mod.-‐Ind. Dalitz analysis.


15

x− = + 0.4 ± 0.0 y− = − 0.6 ± 0.1 x+ = + 0.1 ± 0.1 y+ = + 0.3 ± 0.1

+ 1.0 + 0.0 − 0.6 − 0.1 + 0.8 + 0.1 − 1.0 − 0.0 + 0.7 + 0.0 − 0.4 − 0.1 + 0.5 + 0.0 − 0.8 − 0.1

rS < 0.87 at 68 % C.L.

φ3 measurement with neutral B is promising for Belle II!!

stat. syst. ci, si

BACK UP


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Event Selec?on

•  Primary track –  IP |Δr| < 5 mm, |Δz| < 5 cm

•  KS reconstruc/on –  NIS KS Finder

•  D0 reconstruc/on –  KS and opposite charge 2 π(LR(K/π) < 0.6) –  |MKsππ − mD0| < 0.015 GeV

•  K*0 reconstruc/on –  Opposite charge K(LR(K/π) > 0.7) and π(LR(K/π) < 0.6) –  |MKπ − mK*0| < 0.050 GeV

•  B0 reconstruc/on –  Best candidate is selected by D0 mass and B0 vertex –  Δm > 0.15 GeV for real D0 BG from D*±

–  |MK*0π− − mD0| > 0.04 GeV for [K+π−π−]D−[KSπ+]K*+


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qq suppression

•  qq events are suppressed by using following 12 parameters as NeuroBayes inputs.


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1.  LR(KSFW) 2.  cosθthr 3.  Δz 4.  dist. DK* 5.  |qr| 6.  |cosθB| 7.  cosθD

B 8.  v1_z 9.  v1_v1 10. v2_v2 11. v3_v3 12.  thru_oth

NB output-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

Nor

mal

ized

num

ber o

f eve

nts

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

NB output-1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1

Nor

mal

ized

num

ber o

f eve

nts

-310

-210

-110 Red : Signal Blue : qq BG

Signal efficiency0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Bac

kgro

und

reje

ctio

n

0.2

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Probability

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0.4

TransNB-10 -8 -6 -4 -2 0 2 4 6 8 10

Probability

00.010.020.030.040.050.060.070.080.090.1

NBlow = − 0.6 NBhigh = 0.9992

Red : Signal Blue : qq Green : BB

PDF 19th Feb. '15 LLWI’15 K.Negishi

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MCから分布の形状を得る

ピーキング背景事象

MC MC MC

MC MC MC

MC MC MC

•  シグナルは3次元(ΔE, NB’, Mbc)の分布をフィットして得る

•  同時に(コンティニュアム, BB, ピーキング)背景事象もフィットするコン

ティ

ニュ

アム

BB

イベ

ント

ΔE ΝΒ’ Mbc

ΔE ΝΒ’ Mbc

ΔE ΝΒ’ Mbc

MCから分布の形状を得る

Dが真 Dが真

Dが偽 Dが偽

_

_ + ピ

ーキ

ング

Dπ control sample analysis 19th Feb. '15 LLWI’15 K.Negishi

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•  We obtain Dπ (x,y) consistent with previous result.

Error contours are stat. err. only. (1, 2 and 3 σ)

x− = − 0.0130 ± 0.0077 y− = + 0.0018 ± 0.0076 x+ = − 0.0169 ± 0.0083 y+ = + 0.0225 ± 0.0076

x− = − 0.0045 ± 0.0087 ± 0.0056 y− = − 0.0231 ± 0.0107 ± 0.0077 x+ = − 0.0172 ± 0.0089 ± 0.0065 y+ = + 0.0129 ± 0.0103 ± 0.0088

•  Anton (Previous study, 605 �-‐1)

•  KS selection •  qq suppression •  D0 mass selection •  BGs Dalitz distributions •  Cross-feed between bins •  Efficiency correction.

Difference of my and previous study

•  To check (x,y) fit, we use B+→Dπ+ as control sample. •  B+→Dπ+ is also analyzed as control sample of

B+→DK+ (PRD 85,112014(2012))

Sta?s?cal uncertainty 19th Feb. '15 LLWI’15 K.Negishi

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•  We decide to not use normal error of likelihood distribu/on on (x,y) because of unreliable of (x,y) likelihood due to small sta/s/cs.

•  To obtain sta/s/c uncertainty, we use Feldman-‐Cousin method.

Feldman-‐Cousin method 1.  Generate >20,000 (x,y) fit result with toy MC at 1600 points. 2.  Dist. of (x,y)obt. fit results at (x,y)true space are obtained.

( PDF(xobt.,yobt.|xtrue,ytrue) ) 3.  We define confidence level as integral of the PDF

in a region Ω which sa/sfy PDF(x,y) > PDF(xmeas.,ymeas.). ( We call it “CL(xtrue,ytrue)”. )

4.  Draw contours of e.g.) α = 0.393 (1σ), 0.865 (2σ) and so on.

P(xobt., yobt.)

CL(xtrue, ytrue) Fit result = (xmeas., ymeas.)

(xtrue, ytrue)

Ω

(x(-2., 2.), y(-2., 2.)) 0.1 step

(BN#564 appendix D)

Total signal number = 44.2 +13.3 −12.1

Statistic significance = 2.8 σ

Systema?c uncertainty 19th Feb. '15 LLWI’15 K.Negishi

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We combine the uncertainty from stat. and syst. with assump/on of (x,y) 2D Gauss. for syst. err.

•  Δx− = ± 0.0 •  Δy− = ± 0.1

•  Δx+ = ± 0.1 •  Δy+ = ± 0.1

+ 0.0 − 0.1 + 0.1 − 0.0

+ 0.0 − 0.1 + 0.0 − 0.1

w/o ci,si ci,si

Discussion 19th Feb. '15 LLWI’15 K.Negishi

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•  rS は0と無矛盾 –  B0→DK*0シグナル数が小さかった 44.2 ��

崩壊分岐比で Br(B0→DK*0) = (2.9 ± 0.9)×10−5

–  統計的なふらつきによる

•  Belle II 実験(予定)では

+ 13.3 − 12.1

イベント数 Br(B0→DK*0) ずれ

本結果 44.2 (2.9 ± 0.9)×10-‐5

BaBar 78 (5.2 ± 1.2)×10-‐5 −1.5σ

PDG 64 (4.2 ± 0.6)×10-‐5 −1.2σ

(統計誤差が支配的)

ただし”ずれ”は大きくない

x− = + 0.4 y− = − 0.6 ± 0.1 x+ = + 0.1 ± 0.1 y+ = + 0.3 ± 0.1

+ 1.0　+ 0.0 − 0.6　− 0.1 + 0.8　 − 1.0　 + 0.7 − 0.4 + 0.5 − 0.8

統計系統

50倍BB 統計誤差→ O(<0.1)

現系統誤差と同等

1.  K/π識別能力が上がる　→BB背景事象の抑制

2.  Super-‐Charm-‐Factory 　→ci, siの誤差が減る

_

B0→DK*0崩壊を用いφ3測定の可能性

_

Belle II + Super-‐Charm-‐Factory Δ(x,y)stat. = ± 0.1 Δ(x,y)syst. = ± 0.1

3 )measurementbyB S π DK* atBelleepx.phys.tohoku.ac.jp/eeweb/meeting/201502_LLWI_negishi.pdf · φ...

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