annabelle chuinard mcgill university wipc 2013 measurement of cp violation with the lhcb experiment...

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Annabelle Chuinard McGill University WIPC 2013 Measurement of CP violation with the LHCb experiment at CERN WIPC 2013

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Annabelle Chuinard

McGill University

WIPC 2013

Measurement of CP violation with the LHCb experiment at

CERN

WIPC 2013

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Key facts

b-physics: study of particles containing a (anti-)beauty quark! Branching fraction of B

meson decay Feynman diagram

CP asymmetry CKM matrix terms

Physics beyond the SM

The LHC experiment

WIPC 2013

b

Physics goals

b

760 people, 14 countries 4500 t. apparatus, 100 m

underground single arm forward (≠

ATLAS)

3WIPC 2013

The LHCb detector

pp collisio

n

VErtex LOcator

RICH 1

Magnets

TrackersRICH 2

ElectronicCALorimeter

HadronicCALorimeter

Muons detector (MWPC)

-25°C

-5 to 5°C

-271.3°C

Proton beam

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My job: measure CP asymmetry for

WIPC 2013

There are 2 main Feynman contributions to this decay.

Tree

Penguin (loop)

Radiative B decay :

A1

A2

Amplitudes

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CKM terms and couplings

WIPC 2013

Cabbibo-Kobayashi-Maskawa CKM) matrix describes quark mixing in weak interactions.

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Asymmetry

Conjugate process (CP)

WIPC 2013

Charge asymmetry

Measured valuefrom experimental rates

Corrections

Detection asymmetry between K+ et K-

(found compatible with 0)

Asymmetry due to production rate of B+ et B-

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How to determine raw asymmetry?Distribution of the invariant mass η’K+

Blue line: Multiparameter fit to maximize the

extended likelihood function Distribution of the

invariant mass η’K-

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Detection asymmetry

Detection efficiency is a function of the cross-section of with matter.

At high energy, K+ and K- indistinguishable = same cross section

Use this as a boundary

condition to fit ρ as of function of pK+.

Map ρ and use MINUIT tool to minimize χ2

Test sample: (no production asymmetry)

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Detection asymmetry computation

Distribution ofas a functionof the momentum

Distribution of thenumber of eventsas a function of

Distribution of thenumber of eventsas a function of

Integrate over the distribution to have number of events

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SUMMARY

Calculated using new

method based on kaons cross-

sections

Calculated using rates from mass

distributions

Compatible with PDG world average :

Improvements :Increase luminosity = more statistics

Appendix 1: 2D Likelihood fit

Poisson’s distr.

mB and mη’ are uncorrelated

Unbinned limit (either 0 or 1 event per bin)

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Appendix 2: Detection asymmetry – Mapping

process

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