BaBar Particle Identificationand

Measuring Direct CP Asymmetry in

b→sγ

Piti Ongmongkolkul

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Outline•BaBar Particle Identification(PID)•Is this track Kaon, Pion, Electron or

Proton?•BaBar Detector•Decision Tree•Error Correcting Output Code(ECOC)•Results•b→sγ Direct CP Asymmetry Measurement •Motivation•Current Progress•Outlook2

BaBar Experiment• Located at SLAC• PEPII Asymmetric e+e-

machine• 3 GeV and 9 GeV• • Main Goal is to measure CP violation in B meson• Generic enough to do many more interesting physics

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BaBar Experiment

• 2000-2008• ~470 million B Bbar pairs• +Others• Off resonance (udsc pairs)• Υ(3S)• Υ(2S)• ~1$ per B Bbar pairs

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SVT

• Silicon Vertex Tracker• 5 Layer Silicon Strip• Close to interaction region• tracking• dE/dx

SVT

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DCH

DCH •Drift CHamber•40 layer wire chamber•filled with He-based gas•provides tracking•dE/dx

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DIRC

•Detection of Internally Reflected Cherenkov•Quartz bars and Photo Multiplier Tube array the end•Measure Cherenkov radiation angle θc (function of β)• Mainly for π-K separation

DIRCPMT

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EMC• ElectroMagnetic Calorimeter• 6.5k CsI(Tl)• Photo diode at the end

measure energy deposited in the crystals• Electron -- bremsstrahlung + ionizing• photon -- pair production• pKπμ -- ionizing through• E/p is a very good variable for identifying electron. Electrons leave ~all of its energy in EMC.

EMC

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IFR•Instrumented Flux

Return•Many Resistive Plates•Identifying K-Long and muon•Just count how many plate it pass through

IFR

magnet

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BaBar PID• Identify track whether it’s kaon pion electron

or proton

• Get B meson’s flavor needed for CP violation study

• sin(2β) golden mode

• Cleaning up combinatoric background• Used in almost all analysis

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BaBar PID - How?• Each subsystem provides some information

about which type of particle pass through.• SVT DCH provides dE/dx, p, charge• DIRC provides Cherenkov angle θc• EMC provides energy deposited in CsI and various quantity associated with energy cluster (eg. how wide spread it is )• + combinations of above• Combine all the information• Decision Tree• ECOC (Error Correcting Output Code)

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Decision Tree• Binary question with many input -- given all

these information, is this track an e or a π?• Cuts scan for each

variable.

• Pick a split that maximize the separation (ex gini-index)

• Repeat the process until the node considering has event less than some number

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Combining Decision Trees

•Many trees are trained with slight difference.•Use different set of input variables, different set of weight or different subset of sample.•Average the result

X 100 = Better Classifier

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Added Bonus

• Intuitive to see importance of input variables• Sum of change in “score”

for each variable splitting• deltaFOM• Reduce number of input variables

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ECOC*•Decision Tree can answer binary

question.•“Is this track a p, π, K or e?” is a multiple choice question.•Error Correcting Output Code -- combining binary classifiers to make a multiclass classifier.•This is a more pedagogical example actual implementation is slightly different but the idea is the same

*Dietterich, T., Bakiri, G. (1995). "Solving multiclass problem via error-correcting output code"15

ECOC -- indicator matrix• 1 vs All is an obvious

choice• Is it • (e) or (p π K)--I• (p) or (e π K)--II• (K) or (e p π)--III• (π) or (e p K)--IV• Indicator Matrix• Template for answers• Ask all the question to an unknown track• Pick the closest one

I II III IV

e 1 0 0 0

p 0 1 0 0

K 0 0 1 0

π 0 0 0 1

(?) 1 0 0 0(?) 1 1 0 0

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ECOC -- Exhaustive Matrix•All the binary

questions one could ask•In general there are•2n-1-1•Those 4 and•(e π) or (p K)--V•(e p) or (π K)--VI•(e K) or (p π)--VII•Recovery power

I II III IV V V1 VII

e 1 0 0 0 1 1 1

p 0 1 0 0 0 1 0

K 0 0 1 0 0 0 1

π 0 0 0 1 1 0 0

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ECOC -- Recovery Power

I II III IV V V1 VII

e 1 0 0 0 1 1 1 0

p 0 1 0 0 0 1 0 4

K 0 0 1 0 0 0 1 4

π 0 0 0 1 1 0 0 4

(e) 1 0 0 0 1 1 1

win

• 4 outputs. 1 for each hypothesis

Hamming Distance

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ECOC -- Recovery Power

I II III IV V V1 VII

e 1 0 0 0 1 1 1 1

p 0 1 0 0 0 1 0 3

K 0 0 1 0 0 0 1 5

π 0 0 0 1 1 0 0 5

(e) 1 1 0 0 1 1 1

still win

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ECOC -- Recovery Power

I II III IV V V1 VII

e 1 0 0 0 1 1 1 2

p 0 1 0 0 0 1 0 2

K 0 0 1 0 0 0 1 4

π 0 0 0 1 1 0 0 6

(e) 1 1 0 0 0 1 1

A draw• Our implementation

uses real numbers instead of 1 and 0• and use sum of square• ~2 mistake to change the answer if we are unlucky

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ECOC--recovery power

•In 1 VS All•allow ~1 mistake

•Used in the the previous PID

I II III IV

e 1 0 0 0

p 0 1 0 0

K 0 0 1 0

π 0 0 0 1

(e) 1 1 0 0

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I II III IV V V1 VII

e 1 0 0 0 1 1 1

p 0 1 0 0 0 1 0

K 0 0 1 0 0 0 1

π 0 0 0 1 1 0 0

What I did•Adding 3 columns

I II III IV

e 1 0 0 0

p 0 1 0 0

K 0 0 1 0

π 0 0 0 1

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•e vs pion•Color Legend•1 vs All

Matrix•Exhaustive•Old

likelihood based

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•Color Legend•1 vs All

Matrix•Exhaustive•Old

likelihood based

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Conclusion I

•New method for PID system•ECOC with exhaustive matrix

•Adding 3 columns makes a huge difference

•Currently the recommended one at BaBar

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MeasuringDirect CP Violation in

Using Sum of Exclusive Modes

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Introduction• and •has slightly different branching

ratio

•SM* predicts*Tobias Hurth, et al. arXiv:hep-ph/0312260v2 25

Nov 200527

Feature• Highly suppressed• Flavor changing

neutral current • CKM suppressed*• GIM suppressed*• Require interference of Wilson coefficients• New physics could lift

CKM or GIM suppression• or change in C’s • up to 15%

Kagan Neubert PHYSICAL REVIEW D, VOLUME 58, 094012*Glashow, Iliopoulos, and Maiani*Cabibbo Kobayashi Maskawa

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More•Small long distance contribution (~1%)*•Depend very weakly on photon energy

cutoff*•low energy photon will bring large

background•Good probe for new physics. Happy

middle ground for both theorist and experimentalist.

Kagan Neubert PHYSICAL REVIEW D, VOLUME 58, 09401229

Current StateAcp

Standard Model (note %)

BaBar(2008) −0.011 ± 0.030 ± 0.014

Belle(2004) 0.002 ± 0.050 ± 0.030

Belle arXiv:hep-ex/0308038v4 22 Jul 2004 ~140e6 events (full data set 700e6)BaBar arXiv:0805.4796v3 [hep-ex] 7 Dec 2008 ~380e6 events (full data set 471e6)

• Our analysis will be done using full babar data set ~ 22% increased in data

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Measurement•Goal is to get the Acp

•Select Event as clean as possible•Reconstruct B from 16 final states•For charged B total charge tells us the flavor•Kaon identification tell us neutral B flavor•Get the yield for each flavor and done•Blind Analysis

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But....• For 1 event, there are many ways to

reconstruct B• All we have is a list of tracks with some PID associate

with it. Remember 1 event has 2 B’s although we only use one. Need to match which tracks belong B of our interest.• Even with mass, energy, vertexing among other things. There are still ~10-100 B candidates/event.• Select the best candidate• B doesn’t always decay to Xs gamma

• but could be mis-reconstructed as B->Xsγ• branching fraction ~ 3x10^-4• Photons from pi0• e+e- collision doesn’t always go to B pairs• light quark pairs

• Best Candidate Selection• Peaking BBbar• Fake high energy photon from pi0• continuum background

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Best Candidate•One event has many B candidates•ee→Υ(4S)→BB•We expect each B to have half of

the beam energy in CM frame. If we pick the right set of tracks.•Minimize•Used in all previous analysis but....

• Best Candidate Selection• Fake high energy photon from pi0• continuum background• Peaking BBbar

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Better• Best Candidate Selection• Peaking BBbar• Fake high energy photon

from pi0• continuum background

• Binary question if looking candidate individually• Is this B candidate correctly reconstructed?• Classifier(Decision Tree)• Separate correctly reconstruct B and mis-reconstructed one• Exploit more information*• XsMass• Minimum pi0 momentum• Thrust of B• ΔE (normalized by resolution)• Fox Wolfram Moment 0 and 5• Multiple candidates each with classifier score.• Select the one with the best classifier score*selected from deltaFOM

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More Information

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Improvement• Best Candidate Selection• Peaking BBbar• Fake high energy photon

from pi0• continuum background

Better

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Peaking BBbar• Bonus from SSC• We trained the classifier to separate correctly reconstructed B and mis-reconstructed one• BBbar background is mis-reconstructed by definition• Cutting on the output gives us handle on peaking BBbar Background

• Best Candidate Selection• Peaking BBbar• Fake high energy photon from pi0• continuum background

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Pi0 Veto•Fake high energy photon from pi0•pi0 decays primarily to 2 photon•Is this photon from pi0?

• Best Candidate Selection• Peaking BBbar• Fake high energy photon from pi0• continuum background

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Pi0 Veto• Pair up given high energy photon with all other photons in the event• many pi0 candidates per photon• Train a classifier separate true pi0 candidate and fake pi0 candidate*• Invariant Mass• Energy of the other photon• Take the maximum output• The higher the score the more likely it comes from

pi0• Since it’s linked with continuum background we used this as a variable for another classifier

• Best Candidate Selection• Peaking BBbar• Fake high energy photon from pi0• continuum background

*selected from deltaFOM39

Continuum*• light quark pairs udsc. Very jetty event.• mass of Υ(4S) ~ 2*mass of B. Isotropic.• Build classifier to separate continuum and

BBbar

• Best Candidate Selection• Peaking BBbar• Fake high energy photon from pi0• continuum background

*Done by Dr. David Doll

• Legendre Moments along photon axis and ratio• cosine angle of B and beam axis in CM frame• cosine angle thrust of B candidate and thrust of rest of event in CM frame• cosine angle of photon and thrust of rest of event• various momentum flow(momentum around B axis in various cone size) • pi0 Classifier

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Combining them

Optimizing

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SSC ΔE

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Getting Acp•Work in progress•Simultaneous Fitting of• should peak around mass of B

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Resolution• Generate 2000 set of sample based on pdf and refit to get

Acp• Compared to previous analysis of 0.030 ~ 1.5-2 times better* with only 20% more data• The improvement comes from better candidate selection and handle on BBbar background.

*There is some precision problem with the fitting program though but the residual should be correct4

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More to be done• Finalize Fitting procedure• Subtract off Inherent Detector CP Asymmetry (~1%)• Our detector is made of matter• Sideband/Offpeak• Acp in peaking BBbar component if any• Dilution from mis-PID (expected to be negligibly small)• Fitting Systematic

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Conclusion•BaBar PID•ECOC with exhaustive matrix•Current recommended one

•Acp•Event selection is finalized•Need to Extract Acp•Do systematic and etc.

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Backup

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Different level of tightness

I II III IV V V1 VIIe 1 0 0 0 1 1 1 0

p 0 1 0 0 0 1 0 4

K 0 0 1 0 0 0 1 4

π 0 0 0 1 1 0 0 4

• Each analysis has different requirement. Some need sample to be really clean and can take a hit from efficiency. Some need efficiency and just need pid to clean up a bit.• 4 output 1 for each hypothesis• Picking the best one means• e<p and e<K and e<π • Generalize• e/p>a and e/K>b and

e/π>c48

Bethe-Bloc•Mostly ionization for pi p K •Ionization and bremsstrahlung

(~β) for electron which lose almost all of its energy in CsI

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Acp formula helper

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Cutoff Dependence

• a27 weak dependence• a87 none• a28 yes but small compared to other two5

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Standard Model

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