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Measurements of CP asymmetries and branching fractions in B 0 p + p - , K + p - , K + K -PowerPoint Presentation

Measurements of CP asymmetries and branching fractions in B 0 p + p - , K + p - , K + K -

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Measurements of CP asymmetries and branching fractions in B 0 p + p - , K + p - , K + K -

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Measurements of CP asymmetries and branching fractions in B 0 p + p - , K + p - , K + K -

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Measurements of CP asymmetries and branching fractions inB0 p+p- ,K+p-,K+K-

Paul Dauncey

Imperial College, University of London

For the BaBar Collaboration

Paul Dauncey - BaBar

CP violation in the Standard Model

CP violation arises due to complex CKM matrix; e.g. Wolfenstein parametrisation:

CKM unitarity; represent as triangle in r,h plane

Vtd e-ib

Vub e-ig

- is third internal angle

Paul Dauncey - BaBar

CP violation requires interference between at least two amplitudes with different phases, e.g. B0 K+p-

T

Relative weak phaseeig

K+p-

B0

P

CP violation gives a non-zero asymmetry:

AKp = G(B0 K-p+)-G(B0 K+p-)/G(B0 K-p+)+G(B0 K+p-)

In principle leads tog measurement

–

–

Paul Dauncey - BaBar

–

Mixing gives two paths if final state accessible from B0 and B0, e.g. B0 J/Y K0S

T

B0

J/Y K0S

Relative weak phaseei2b

–

T

–

M

B0

CP violation gives a time-dependent asymmetry:

Amplitude = Im(ei2b) = sin2b

Leads to b measurement: see talk by S. Rahatlou

Paul Dauncey - BaBar

CP violation in B0 p+p-

B0 p+p-has both effects

T

P

B0

p+p-

–

Relative weak phaseeia

P

M

–

–

T

B0

No relative weak phase

Relative weak phaseei2a

If both tree and penguin significant: parametrise as sin2aeff

Interpretation also depends on strong amplitudes

Paul Dauncey - BaBar

Analysis is different from B0 J/Y K0S…

- No clean pp or Kp sample; need to determine particle type
- Particle identification needed
- Analyse both modes simultaneously; also include KK

- No clean signal sample; high backgrounds from udsc
- Branching fractions are ~ 10–6– 10–5
- Need to use kinematics and event shapes to distinguish modes
- Use unbinned maximum likelihood fit to extract signals
…but some elements are identical:

- Need to “tag” the other B to find if B0 or B0
- Use lepton charge, K charge or neural networks
- Inefficiency and impurity (“dilution”)

- Cannot measure time directly
- Time difference Dt between two B decays

–

Paul Dauncey - BaBar

–

Pep-II delivers boosted e+e- Y(4s) BB, on and off the Y(4s)

Integrated luminosity: 55.6 fb-1 on peak, 60.2 0.7 million BB events

–

1.5T solenoid

EMC

6580 CsI(Tl) crystals

DIRC (PID)

144 quartz bars

11000 PMs

e+ (3.1GeV)

Drift Chamber

40 stereo layers

e- (9 GeV)

Silicon Vertex Tracker

5 layers, double sided strips

Instrumented Flux Return

iron / RPCs (muon / neutral hadrons)

Paul Dauncey - BaBar

Particle identification with the DIRC

Detector of Internally Reflected Cherenkov light (DIRC): essential for this analysis to distinguish K from p

Reconstruct Cherenkov angle cosqC = 1/nb

from rings seen in PMTs

Cherenkov light transmitted down quartz bars by internal reflection

Paul Dauncey - BaBar

Analysis is done in two stages:

- Direct CP; extract branching fractions for pp, Kp and KK and also the Kp decay CP asymmetry AKp
- Maximum likelihood fit to kinematic/event shape quantities
- Requires no tag or vertex measurement
- Separate fit reduces systematic error

- Indirect CP; extract pp CP asymmetry sin2aeff
- Fix branching fractions and AKpto above results
- Requires tag to determine if B0 or B0
- Requires vertex information to find time dependence
All results are preliminary

–

Paul Dauncey - BaBar

Kinematic variables - mES

B candidate mass using beam “energy substitution”

mES = (Ebeam2 – pB2) in CM

Select 5.2 < mES < 5.3 GeV/c2

- Depends on reconstructed momentum of B candidate, pB ~ 325 MeV
- Same for all signal modes
- Resolution dominated by beam energy uncertainty
- s(mES) ~ 2.6 MeV/c2
- Signal shape from MC, background from fit

Signal Monte Carlo; Gaussian

Background; ARGUS threshold function

Paul Dauncey - BaBar

Kinematic variables - DE

B candidate energy difference from beam energy

DE = EB – Ebeam in CM

Select | DE | < 0.15 GeV

- Depends on masses of B decay products; p mass assumed
- Kp and KK shifted to non-zero average; ~ 45 MeV per K
- Resolution dominated by tracking
- s(DE) ~ 26 MeV
- Signal shape parametrised from MC; background from fit

Kp

KK

pp

Signals: Gaussian

Background; quadratic function

Paul Dauncey - BaBar

DIRC c mean and resolution parametrised from data using D*+ D0+ (K–+)+ decays

s(qC) = 2.2 mrad

9s

K/p Separation

2.5s

Momentum range of decays

Paul Dauncey - BaBar

Background suppression - Fisher

Cut on angle between B candidate and sphericity of the other tracks in the event: |cos qs| < 0.8

Background

Signal Monte Carlo

Signal Monte Carlo

Background

Cut

F - optimized linear combination of energy flow into nine cones around candidate (CLEO Fisher discriminant). Signal shape from MC, background from fit

Paul Dauncey - BaBar

Branching fraction maximum likelihood fit

Five input variables per event; assume independent (uncorrelated) PDFs for each:

- mES
- F Discriminate signal from background
- DE
- qC+ Discriminate different signal modes
- qC–
Eight fit parameters: four for signal, four for background

- N(p+p-)
- N(K+p-)
- N(p+K-)
- N(K+ K-)

Fit directly for N(Kp) and AKp:

N(K+p-) = N(Kp) (1–AKp)/2

N(p+K-) = N(Kp) (1+AKp)/2

Paul Dauncey - BaBar

Fit results are:

No significant direct CP violation seen in B0 K+p-

- 90% C.L. –0.14 AKp 0.05
- Main systematics:
- Branching fractions – uncertainty in shape of qC PDF
- Asymmetry - possible charge bias in track and qC reconstruction

Paul Dauncey - BaBar

Branching fraction projections

Likelihood projections: remove one variable from fit and cut on fit probabilities to give enhanced signal samples:

B0pp

B0Kp

Fit sample: 17585 candidates, e ~ 38%

Background and crossfeed

Paul Dauncey - BaBar

Measuring indirect CP violation

Extend the branching fraction analysis to extract indirect CP information:

- Needs extra information on:
- Time of decay (vertexing); reconstruct “other” B decay point and find time difference of B decays
- Flavour of the decaying B0 (tagging); use tracks whose charge carries flavour information
- Use identical techniques to sin2b analysis

- Fit for CP violation asymmetries while holding branching fractions and Kp asymmetry to previously determined values
- Vary these parameters within determined errors for systematics; small effect for asymmetries

Paul Dauncey - BaBar

Asymmetric beam energies mean Y(4s) is boosted:

Best vertex for “other” B

Fully reconstructed Bpp

p-

(4s)

Dz

p+

bg = 0.55

Dt @Dz/gbc

Dt is time difference between the two decays:

- Resolution is dominated by the “other” B, s(Dt) ~ 0.8 ps
- Independent of signal type
- Can use same resolution model as sin2b analysis
- Exploit mixing to measure signal performance (dilutions) and efficiencies
- Signal resolution determined from large sample of fully reconstructed B’s, background shape determined from fit

Paul Dauncey - BaBar

The signal modes depend differently on Dt:

- ppgeneral form allows for both tree and penguin: rates
- f(Dt) ~ 1 Spp sin(DmdDt) Cpp cos(DmdDt) for B0(B0) tag
- Spp = 2Im(l)/(1+|l|2) and Cpp = (1-|l|2)/(1+|l|2)
- For pure tree, l = ei2a so Spp = sin2a and Cpp = 0
- With some penguin contribution,Cpp 0andSpp = (1-Cpp2) sin2aeff

- Kptime dependence due to B0 mixing: rates
- f(Dt) ~ 1 cos(DmdDt) for unmixed (mixed) B0

- KK general form similar to pp in principle
- Model with simple exponential

- Actual PDFs used in fit:
- Diluted due to mistags
- Convolved with Dt resolution functions

–

Paul Dauncey - BaBar

Use same flavour tagging as sin2b measurement:

Lepton;eeff ~ 8%

Fit sample: 9220 tagged candidates

Kaon;

eeff ~ 14%

Separate into tag categories

mES

Gev/c2

Neural Net 1;eeff ~ 2%

Neural Net 2;eeff ~ 1%

Untagged events (~ 33%) retained in the fit to determine background shapes

Paul Dauncey - BaBar

Fit results in:

Spp = –0.01 ± 0.37 ± 0.07

Cpp = –0.02 ± 0.29 ± 0.07

No significant indirect CP violation seen in B0 p+p-

- 90% C.L. –0.66 Spp 0.62
- 90% C.L. –0.54 Cpp 0.48
Main systematic:

- Uncertainty in shape of qC PDF

Fit result

Enhanced B pp sample: Dt distributions and asymmetry between mixed and unmixed events.

Fitted background

Paul Dauncey - BaBar

Time-dependent fit cross checks

Fit checked using “toy” studies of simulated experiments

- All parameters unbiased
- All errors consistent with expectations
- Likelihood value (goodness of fit) consistent with expectations
Fit holds B lifetime and mixing constant: cross check by fitting

- tB = 1.66 ± 0.09 ps (c.f. PDG value 1.54 ± 0.02 ps)
- Dmd = 0.517 ± 0.062 ps–1 (c.f. PDG value 0.479 ± 0.012 ps–1)

Enhanced B Kpsample: asymmetry between unmixed and mixed events.

Paul Dauncey - BaBar

Summary of BaBar preliminary results

Branching fractions:

B(B0 p+p-) = (5.4 ± 0.7 ± 0.4) 10–6

B(B0 K+p-) = (17.8 ± 1.1 ± 0.8) 10–6

B(B0 K+K-)= 1.1 10–6 (90% C.L.)

CP asymmetries;no evidence for CP violation:

Spp = –0.01 ± 0.37 ± 0.07 or 90% C.L. –0.66 Spp 0.62

Cpp = –0.02 ± 0.29 ± 0.07 or 90% C.L. –0.54 Cpp 0.48

AKp = –0.05 ± 0.06 ± 0.01 or 90% C.L. –0.14 AKp 0.05

Paul Dauncey - BaBar