oral candidacy presentation
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Oral Candidacy Presentation. David Doll. Outline. Thesis topic: b →s γ Motivation Previous Analysis Babar overview Subdetector introduction and impact on thesis Previous work: Introduction to Random Forest method Applications to thesis topic and plans. b →s γ Motivation. γ. - PowerPoint PPT PresentationTRANSCRIPT
Oral Candidacy Presentation
David Doll
1
OutlineThesis topic: b→sγ
MotivationPrevious Analysis
Babar overviewSubdetector introduction and impact on thesis
Previous work: Introduction to Random Forest method
Applications to thesis topic and plans
KB
2
b→sγ Motivation
Flavor changing neutral current decay (absent at tree level in SM)
Precision test of SMDifferent models may enhance or suppress the BF
γ
Source: U. Haisch, FPCP Conference Taipei, 2008
3
For photon energy cut Eγ > 1.6 GeV in B meson rest frameNNLO theoretical calculation
HFAG experimental results (as of March 15, 2007)
b→sγ Motivation
409.010.0 10)03.024.055.3()B(
sXBF
410)23.015.3()B( sXBF
Combined statistical and systematic error Systematic
uncertainty associate with Ecut = [1.8,2.0]
Error associated with subtraction of events
dXB
Source U. Haisch FPCP Violation 2008
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b→sγ MotivationPhoton energy spectrum
In b quark rest frame (impossible to boost to), this would be a delta function (≈mb/2)
b quark motion within meson smears this spectrum Spectral shape dependent on modeling of spectator
quark In the framework of HQET, the parameters λ1 and
(or equivalently mb) may be determined from the first two moments of the spectrum
Beyond SM theories are not predicted to influence this much
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Different Photon ModelsShape function of b quark motion is universal
Applicable to all decays involving tranistions to massless states (B→Xs γ, B→ Xd γ, etc.)
Different shape function models exist
A.L. Kagan and M. Neubert propose an exponential shape function (KN model):
xaa exNkF )1()1()(
where: 1
kx
bB mm
)1(31
31 2
12
a
Source Eur. Phys. Jour. C7, 5-27 (1999)
Gaussian Ansatz
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Dependence on Ecut
7
D. Benson, I.I. Bigi, and N. Uraltsev also investigate an exponential and a Gaussian ansatz (with minimal difference between the two)Use purely perturbative spectrum calculated by Z. Ligeti, M. Luke,
A.V. Manohar, and M. Wise as a starting pointAdd nonperturbative pieces to the energy momentsFinally, they investigate the effects of the minimum photon energy
cut to evaluate a bias in mb and μπ2
Complete bias
Without perturbative corrections
difference
Source D. Benson, I.I. Bigi and N. Uraltsev FPCP Violation 2004
Other Photon ModelsB. Lange, M. Neubert, and G. Paz also
present shape functions based on exponential, gaussian, and hyperbolic functions (hep-ph/0504071)They detail how to fit the parameters:
8
),ˆ(ˆˆˆ),ˆ(0ˆ
00 i
NiN SdM
min
0 2ˆ EM B
First and second moments are directly relatable to and μπ
2 and:
Is a good model for
)ˆ()]ˆ(/),ˆ([ 0][
000 FMM Fi
Exponential, gaussian, or hyperbolic
),ˆ(ˆiS
Search Strategy for b→sγPerforming a sum of
exclusive states38 states totalUpdate of former analysis
published in Phys. Rev. D (2005) 052004 Based on 89.1 fb-1 of data
collected at the Y(4S)
9Source Babar doc
On CP Asymmetry MeasurementBecause of the final state
reconstruction, a direct CP asymmetry measurement is possible with this strategy in modes of definite flavor (yellow)Recently investigated with
~80% of the total dataPossible source of other
new physicsSearch to be performed in
another analysis
10Source Babar doc
Former Analysis ProcedureReconstruct event candidates into the 38 different decay modesUse a Neural Network to reject continuum events based on event
shape variablesSet the lower cutoff energy at Eγ > 1.9 GeV (or equivalently at
MXs between 0.6-2.8 GeV/c2) to limit peaking B backgroundChoose the ‘best’ candidate as the one that minimizes ΔE
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Source Babar doc
)2/(* sEBE
Subtract off the continuum, generic BB, and cross-feed backgrounds by fitting the beam substituted mass, mES and fit to signal on bin-by-bin basis in MXs
The peaking background contribution (cross-feed and generic BB) is fit with a Novosibirsk function:
The continuum contribution is fit with an ARGUS functionAs a default signal model, they use the KN exponential model
with mb= 4.65 GeV/c2 and λ1=-0.30 GeV2/c4
Kagan and Neubert recommend treating only the range between MXs={1.1 GeV/c2, 2.8 GeV/c2} as a non-resonant spectrum
Below MXs= 1.1 GeV/c2, they recommend using K*γ MC below 1.1 GeV/c2
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Former Analysis Procedure
Bin-by-bin fit to signal gives Partial Branching Fractions, PBF(MXs)
Need to correct PBF(MXs) for fractional coverage of inclusive b→sγ decays to get Total Branching Fractions, TBF(MXs)
Convert TBF(MXs) to TBF(Eγ)Fit TBF(Eγ) to different expected models, allowing
extraction of inclusive Branching Fraction measurement to lower Eγ
Also extract shape function paramters, mb and λ1 from model fit
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Former Analysis Procedure
Impact of competing modelsIdeally, photon spectrum measurement is
model independentAnalysis strategy forbids this
Need idea of total decay coverage in each MXs bin
Not able to extrapolate to a total BF without introducing some model dependencies
Use a sample with a flat Eγ distribution to reweight to any model chosenMeasure parameters in all models considered
(everyone’s happy)14
Results of Former AnalysisQuote results of KN fit, ‘kinetic’ model (BBU
from above), and ‘shape function’ models (average of 3 BNP shapes from above)
15Source Babar doc
PEP-II at SLAC
e- (at 9.0 GeV) on e+ (at 3.1 GeV)CM energy = 10.58, the mass of the Υ (3S)Lorentz boost of βγ = 0.56B meson lifetime 1.5-1.6 ps → Δz ≈ 250-270 μmTurned off in April with a total of ~485 fb-1 at or just below the
Υ(4S).
Source Babar Doc
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Babar Detector
DIRC
SVT
DCH
EMC
IFR
Solenoid Magnet (1.5 T)
e +
e -
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Subsystems OverviewSubsystem Measured
quantityMethod
Silicon Vertex Tracker (SVT)
Particle Tracking, Vertex Location,
dE/dx
Double sided silicon strips
Drift Chamber (DCH)
Particle Tracking, dE/dx
Sense wires in helium-isobutane gas
mixtureDetector of Internally Reflected Cherenkov
light (DIRC)
Particle ID for particles of
momentum greater than 700 MeV/c
Cherenkov light measured on PMTs
Electromagnetic Calorimeter
(EMC)
Energy, Shower Shape
CsI(Tl) crystals, read out by Si Photo-
diodesInstrumented Flux
Return (IFR)Penetration,
Shower ShapeStreamer detection
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SVT and DCH
SVT 5 layers of double-sided silicon strip sensorsφ measuring strips parallel to the beam, z measuring strips
perpendicular to the beam20-40 μm resolution in all 5 layers.
DCH7,104 small drift cells arranged in 40 cylindrical layersdE/dx measured by total charge deposited in each cell
Source Babar doc
SVT DCH
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DIRCParticle ID for particles with momentum above 750 MeV/c144 fused, synthetica silica bars arranged in a 12-sided
polygonReadout by 11,000 PMTs
Source Babar doc
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IFRSegmented steel flux return (later
also brass), instrumented in gapsOriginally used resistive plate
chambers (RPC) to detect streamers from ionizing particles
Upgraded to limited streamer tubes (LST) starting in 2004
Muon efficiency
Pion mis-id rate
RPC data
LST data
Source Babar doc.
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EMCDesigned to operate over the energy range of 20MeV to 9GeV6,580 CsI(Tl) crystals separated into 5,760 in the barrel, and 820 in the endcap
16.1 X0 in the backward half of the barrel, to 17.6 X0 in endcapEach crystal read out by two 1cm2 Si photodiodesCalibration at low energy using a 6.13MeV photon source and at high energies
using Bhabha events Studies of the low energy calibrations have shown light yield falloff to total around
8% or less after the run of the experiment (depending on crystal manufacturer).
Angular resolution vs photon energy
Source Babar doc.
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B+→K+νν (or the benefits of a multivariate classifier)
Performed search with D. Hitlin, I. Narsky, and B. Bhuyan
Also a FCNC, and therefore highly suppressed in the SM
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Standard Model BF
Experimental Limit on BF
(90% CL)62.1
6.0 108.3 5104.1 arXiv:0708.4089v2 [hep-ex]
Analysis Procedure, TaggingPerform a ‘semileptonic’ tagged analysis
Fully reconstruct the ‘tag B’ in the decayLook at the rest of the event for our signal
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νlDB 0
}{ 00 ππ,ππ,ππKD
0D
l
ν ν
ν
KTag B Signal B
BB
Analysis Procedure, CutsSeparately pursued two different techniques
to suppress backgroundStandard Rectangular Cut methodMore sophisticated Multivariate technique with
a Random ForestFor Rectangular Cuts, separated the Monte
Carlo (MC) into 3 sets: train, valid, test; in a 2:1:1 ratioOptimized the ‘Punzi’ Figure of Merit:
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BNS
2
Where S is the number of signal, Nσ is the sigma level of discovery, and B is the number of background
Rectangular Cut Results
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