1. January 29 2010 1/55
Some Recent Results from the MEG Experiment on
µ → eγ:
Benjamin Golden
Joint Particle Seminar
February 8, 2012
University of California, Irvine

2. Outline
• Part I - The Theory of Lepton Flavor
– Lepton Flavor Symmetries in the Standard Model
– Lepton Flavor Symmetries and the Lack Thereof Beyond the Standard Model
• Part II - The MEG Detector
– Event Signatures
– Hardware Design
• Part III - Event Reconstruction
– Photon Reconstruction
– Positron Reconstruction
• Part IV – A UCI Search for µ → eγ
– Likelihood Framework
– PDFs
– Results
– Comparison with (collaboration) published results

3. Part I
The Theory of Lepton Flavor:
A Window to the UV Completion of the Standard Model

4. The Standard Model Achromatic Sector: Leptons
• SU(2)L x U(1)Y couples to leptons, there are no right-handed ν’s
• Three generations are known to exist: f=e,µ,τ
• Left-handed leptons: Right-handed leptons:
• With massless neutrinos, the SM conserves lepton flavor for each generation classically
– Result of 3 accidental global U(1) symmetries:
– Gives 3 Noether charges:
• Instantons spoil the classical conservation of Lf but exactly preserve
– B – L (Sufficient to keep neutrinos massless even at non-perturbative level)
– (Lτ – Le), (Lµ – Le) (Sufficient to exclude µeγ)
• Neutrino masses must enter the SM Lagrangian in some unknown way
– µeγ receives contributions from active neutrino loops
– With experimental information on ∆mij
2
, these diagrams alone
imply undetectably small rates for µeγ
– Additional diagrams with new matter content
would be needed to enhance Br(µeγ)
to something detectable
– An observation of µeγ would demonstrate
the existence of new physics
Lf
f
f
l 





=
ν
L
Rff l )(R =
ff
f
LeL
-iq
→ ff
f
ReR
-iq
→
fff N-NQ =
µ±
e ±
γ
W±
νiUµi U*
ei

5. ~eµ~
CLFV in SUSY Models: A Little Help from the Sleptons
• The SUSY flavor problem
– µeγ can proceed in SUSY through diagrams that
communicate slepton mixing to leptons
– BR(µeγ)<10-11
requires a fine alignment between
lepton and slepton mass matrices
– Yet lepton masses come from Yukawa interaction, while
slepton masses arise from SUSY breaking
– Addressed by a number of proposed solutions, all with highly model dependent
consequences for BR(µeγ), here focus on one example: Gravity mediation
• Gravity Mediation
– SUSY broken in a hidden sector, gravitational interactions generate diagonal squark and slepton mass
matrices, all with the same universal scalar mass at MPlanck ~ 1018
GeV
– Slepton mixing appears from RGE’s running from
MPlanck to electroweak scale
– An oft-cited, cliché of an example is SO(10) GUT
– At MPlanck, theory is tied down by choice of m0
(scalar mass),M1/2 (gaugino mass), A0 (trilinear coupling)
– Fix tan β, make assumptions about
parameters in superpotential
– Scan (m0,M1/2,A0)in a region that allows a squark mass below
2.5 TeV (LHC accessible)
×
µ e
γ
~χ0
Large mixing in ν Yukawas
Small mixing in ν Yukawas

6. CLFV’s Place in the Landscape of Gauge Hierarchy
Problem Solutions: Generic
• Non-SUSY solutions to hierarchy problem allow µeγ for other reasons
• Dynamical EWSB (Technicolor)
– Fermion condensate develops dynamically, plays the role of the Higgs
– Requires non-universal gauge groups that induce LFV couplings of gauge boson to lepton
mass eigenstates
• Little Higgs
– New vector bosons, fermions, scalars cancel 1-loop corrections to Higgs
– LFV from gauge bosons and exotic scalar multiplets
• Extra Dimensions
– Planck mass is actually small (Gravity weak from loss of flux to extra dimensions)
– RHN in bulk generate µeγ where KK states play similar role to sparticles
• Some discerning power available: Linear correlation in BR(µeγ) & BR(µNeN)
would favor MSSM over these

7. Part II
The MEG Detector:
At the Frontier of Low Energy Precision Measurement

8. Signal and Background
• Accidentals are dominant
background at rates high
enough to reach 10-13
sensitivity
Signal
µ+
→e+
γ
µµ++
γγee++
Radiative decay background
µ+
→e+
νeνµ γ
ν
ν
µµ++ee++ γγ
Accidental background
µ+
→e+
νeνµ
+
µ+
→e+
ννγ or
e+
e-
→γγ or
e+
Z→e+
Zγ ν
νµµ++ee++
γγ
ΘΘeeγγ == 180°180°
EEee ≈≈ EEγγ ≈≈ 52.852.8 MeVMeV
TTee = T= Tγγ
ΘΘeeγγ = any angle= any angle
EEee, E, Eγγ << 52.852.8 MeVMeV
TTee = T= Tγγ
ΘΘeeγγ == randomrandom
EEee, E, Eγγ << 52.852.8 MeVMeV
TTee –T–Tγγ == randomrandom
• For fixed MEG acceptance: Naccidental /Nμ ∝ Rate × ∆teγ × ∆Ee × (∆Eγ)2
× (∆Θeγ )2
Ee ~ flatEγ ~ rising linearly

9. 1
History of µ→eγ Searches
10-2
10-4
10-16
10-6
10-8
10-10
10-14
10-12
1940 1950 1960 1970 1980 1990 2000 2010
MEGA
BranchingFractionUpperLimit
MEG goal
MEG
2009+201
0 result

10. MEG Timeline: Past, Present, and Future
• Data Taking
– 1998: Original LOI (PSI-RR-99-05)
– 2002: Proposal with a goal of 10-13
sensitivity
– 2007: (Nov-Dec): Engineering run
– 2008: (Sep-Dec): 1st
physics run, some hardware problems
– 2009: (Nov-Dec): 2nd
physics run
– 2010: (Aug-Dec): 3rd
physics run
– 2011: (July-Nov): 4th
physics run
– 2012: continue data taking
• Physics Analysis for Br(µeγ)
– 2008 Data Analysis:
• 90% CL UL = 2.8 x 10-11
• Sensitivity = 1.3 x 10-11
– 2009 Data Analysis:
• 90% CL UL = 9.6 x 10-12
[Collaboration result]
• Sensitivity = 3.3 x 10-12
[Collaboration result]
• Also the object of independent UCI analysis [Primary Content of this Talk]
– 2009+2010 Data Analysis:
• 90% CL UL = 2.4 x 10-12
• Sensitivity = 1.6 x 10-12

11. MEG Experiment Design
• ~ 3x107
µ ＋
/s beam incident on a thin stopping target
• Positron detection
– Gradient B-field to sweep out e+
quickly and keep bending radius constant
– Low mass drift chambers to measure energy, emission angles, & path to timing counter
– Timing counter with scintillating plastic for precise time measurement
• Photon detection
– Energy, position, and time measured in a liquid xenon calorimeter
– Fast response time, high light yield, high photocathode coverage

12. Paul Scherrer Institut (PSI)
• The other accelerator lab in
Switzerland
• Highest power operating proton
accelerator
– 2.2 mA, 590 MeV kinetic energy, 1.3 MW
beam power
– Extremely reliable
– Provides secondary pion, muon, neutron
beams
590 MeV proton ring cyclotron
MEG
Office
Apartment:
45 minute
journey
through
forest

13. Muon Delivery to MEG: Beam & Target
• Muon Beam
– Produce pions in graphite target
– Extract 29 MeV/c muons from π+
decay at rest (can be stopped in thin target)
– Wien filter for µ/e separation
– Beam transport solenoid for focusing
– Mylar degrader to slow muons (~300 µm)
– 3x107
µ/s, final spot size σx,y ~ 1 cm
• Muon Stopping Target
– 205 µm thick polyethylene
– 20° slant from beam direction for more stopping power
– Holes to check alignment using reconstructed e+
tracks
590 MeV proton beam
target
µ+
beam line µ+
/e+
separator
beam transport
solenoid
MEG
Detector
Degrader
µ+

14. COBRA Magnetic Field
COnstant Bending RAdius
Positrons swept out quickly
z
θ
• R=Psin(θ)/QB
• B-field must decrease with |z| to
keep R constant and independent
of θ (range: 0.5-1.3 T)
• Allows precise selection window
in R for high momentum tracks
• R changes with |z| in such a way
to make fewer turns in the DCH
• Simplifies pattern recognition
• Helps limit rate for stable
chamber operation

15. The Drift Chamber
• Measure e+ energy, extrapolate to target for angles and decay vertex
• Extrapolate to TIC to correct impact time by flight time (to ~1 cm in path length)
• 16 chambers radially aligned at 10.5° intervals
• 2 planes of drift cells staggered by ½ cell; 18 wires each chamber
• Acceptance matched to that of calorimeter
• Radial position from drift time
• Resistive wires for approximate Z by charge division, pattern etched on cathode
pads to interpolate Z
• Gas: He – Ethane mixture (50:50): (X0~650 m, vd saturates at ~4 cm/µs)
• Goals: σR = 200 µm σZ = 300 µm σe+ energy = 180 keV
• Total average path of one turn .002 X0

16. Timing Counter
• Primary purpose: trigger & precise e+ time
• Inner layer of 256 scintillating plastic fibers
– Coupled to APD’s (tolerate B-field,
Smaller->easier to align with small fibers)
– Each end of COBRA at fixed Z
– Used for z measurement and in the trigger
• Outer layer of 15 scintillating plastic bars
– Coupled to PMT’s
– Each end of COBRA at fixed φ
– Used for impact time and φ measurement
• 29 cm < |z| < 109 cm
• TIC surrounded by N2 because PMT’s have short life in Helium
• Goal: σt = 40 ps

17. Liquid Xenon Calorimeter
Liq. Xe
H.V.
Vacuum
for thermal insulation
Al Honeycomb
window
PMT
Refrigerator
Cooling pipe
Signals
fillerPlastic
1.5m
Density 2.95 g/cm3
Boiling and melting points 165 K, 161 K
Energy per scintillation photon 24 eV
Radiation length 2.77 cm
Decay time 4.2, 22, 45 ns
Scintillation light wave length 175 nm
Scintillation light absorption length > 100 cm
Attenuation length (Rayleigh scattering) 30 cm
Refractive index 1.56
• Relatively high light yield, uniform response
• No self-absorption of scintillation light:
attenuation only from impurities
• 900 L liquid xenon (largest LXE volume)
• 846 mesh phototubes on surfaces, in LXE
• Thin magnet wall to reduce photon conversions
• Goal is to measure photon properties:
– Position: σRMS = 3.5 mm
– Time: σRMS = 40 ps
– Energy: σRMS = ~900 keV at 52.8 MeV

18. Dedicated Calibration Tools
• Calorimeter
– CEX reaction: π−
+p (LH2 target)  π0
+ n followed by π0
 γγ (98.8%)
• Select events with 83 MeV γ in NaI detector and a back-to-back γ in XEC (55 MeV)
• Used to measure γ energy scale, resolution; γ time resolution, PMT time delays
• Position resolution of γ from data with lead collimator in front of XEC entrance
– Cockcroft-Walton proton accelerator (Li2B4O7 target)
– LEDs mounted in XEC
• Flash with different intensities
• Calibrate PMT gains
– QE measured by scintillation light from α sources
mounted at known positions (241
Am)
• Laser measurements of reference marks on drift chambers and target for
primary alignment
• Relative TIC-XEC timing from Dalitz data (π0
 e+
e-
γ )
Reaction Eγ [MeV] Uses
p + Li → Be + γ 17.6 Monitor light yield
p + B → C + γ + γ
4.4 + 11.6
Cross-time LXE and timing counter
check
α source wire
LED
LED

19. Part III
Event Reconstruction:
Getting Particle Kinematics from Waveforms
I don’t know
what I’m
looking at.

20. Photon Reconstruction in the Calorimeter
• Position (of 1st
conversion)
– Fit to pattern of light on inner face PMTs
– Angles at target from e+
vertex and
γ conversion position
• Energy
– First estimate from sum of all PMT signals weighted by local photocathode
coverage
– Apply corrections as function of position, determined from calibration photons (55
MeV, 17.6 MeV)
• Large variation of photocathode coverage with position for shallow depth conversions
• Same occurs near edges in transverse coordinate
• Time
– Weighted average of PMT leading edge times
– Correct for flight time from vertex to conversion position

21. Positron Reconstruction in the Drift Chamber & Timing
Counter
• Drift Chamber
– Hit Reconstruction
• Identify cells with waveforms consistent with through-going charged particle
• Hit time from leading edge of pulse
• Z from charge division
– Clustering: Group hits on a chamber, spatially consistent with charged particle
– Tracking
• Group clusters into tracks
• Drift times using TIC time to get track time
– Kalman Filter to fit track
• Calculates positron energy
• Extrapolation to target for angles and vertex
• Extrapolation to TIC for path length
• Provides event-by-event uncertainties in track
parameters (energy uncertainty, …)
• Timing Counter
– Impact time at bar from waveform leading edges of PMTs
– Correct for time of flight from vertex to bar

22. Part IV
Current MEG Results
& UCI Analysis on 2009 Data:

23. Summary of Published MEG Results (October 2011)
|teγ|<0.28ns;
cosΘeγ< -0.9996
51<Eγ<55 MeV;
52.3<Ee<55 MeV
BR(best fit) LL 90% CL UL 90% CL
2009 3.2×10-12
0.17×10-12
9.6×10-12
2010 -0.99×10-13
-- 1.7×10-12
2009+2010 -0.15×10-13
-- 2.4×10-12
Expected UL
(2009+2010)
1.6×10-12
2009 Data 
2010 Data 
(~2 x as much
data as 2009)
Contours:
1σ
1.64σ
2σ

24. • A rare decay search is very sensitive to the exact values of selection cuts
• If it is known which events satisfy cuts during analysis, 2 extreme cases of bias:
– Cut to eliminate individual events, yielding better upper limit than justified
– Cut to retain individual events, producing a signal where none is present
• Use “Hidden Signal Box” technique (<0.2% of data in blind box)
– Signal-like events are hidden until
selection cuts and likelihood function
are determined
• 48 E≤ γ 58 MeV≤
• | Teγ | 0.7 ns≤
– Sidebands adjacent to signal box
(16% of data)
• Can look at radiative decays for Eγ 48 MeV≤
• Can look at accidental photons
in | Teγ | > 0.7 ns
• Analysis Window
– 48 E≤ γ 58 MeV≤
– | Teγ | 2.1 ns≤
• Effective constraint on accidentals by including sidebands in fit
• Collaboration uses | Teγ | 0.7 ns, adds constraint on accidentals from sideband extrapolation≤
– |φeγ|, | θeγ | 50 mrad (angles btw. reversed e+ and≤ γ vectors)
– 50 E≤ e 56 MeV≤
Blind Analysis Technique: Setting σexperimenter bias = 0
UCI Analysis Window
BLIND BOX
(Collaboration
Analysis
Window)
Left
Sideband
Right
Sideband
Bottom
Sideband

25. Event Selection Criteria: Quality Control
• Basic strategy
– If we wouldn’t believe a signal event with some characteristic, we remove such
events from the sample
– Incorporate the dependence of resolutions on event properties into event-by-
event probability density functions (PDFs)
• Positron
– Track quality (# of hits, chamber extent, χ2
of fit, etc…)
– Remove events not consistent with a muon stopping in the target
– Imposed some cuts not present in collaboration analysis
• Photon
– Cosmic ray veto based on conversion depth and ratio of inner/outer face γ’s
– Preserve events with in-time pileup by removing energy in secondary shower
centroid
– Reject irrecoverable pile-up events

26. Maximum Likelihood Analysis
• Fit for numbers of signal (NSig) and accidental (NAcc) events by maximizing an
extended likelihood function
– N= NSig +NRD + Nacc
– NRD is fixed to expectation from bottom sideband extrapolation
– Kinematic observables: Ee, Eγ, teγ, φeγ,θeγ
– S is probability for a signal to result in the set of observables of a given event, similarly for
R and A (S, R, & A are called PDFs)
• Some differences with collaboration likelihood fit
– Collaboration handles background differently
― NRD is floated rather than fixed
― Fit in 3 times smaller time region, 3 times fewer accidentals in the fit
– Collaboration adds Gaussian constraints to likelihood function on NAcc and NRD
― Means of Gaussians from extrapolations
― Sigmas of Gaussians from statistical uncertainties of predictions
• Normalization sample is a highly pre-scaled, simultaneous Michel e+
sample:
– BR(µ→eγ)= NSig * (9.7 x 10-13
± 10%)
– 9.7 x 10-13
is also the branching ratio for which we expect to see 1 event in analysis window
in a background-free experiment (single event sensitivity)
( ) ( )
∏=






++
−
=
obsobs N
i
AccRDSig
obs
N
AccSig A
N
N
R
N
N
S
N
N
N
NN
NNL
1!
exp
,

27. • Fit accidental Ee (i.e. Michel) spectrum with model:
theoretical*acceptance ⊗ resolution
– Acceptance: error function plateauing at high energy
– Resolution: sum of two Gaussians
• Use event-by-event estimator of Ee uncertainty from Kalman track fitter (δEe), expect
strong correlation with Ee resolution
– Fit spectrum in nine bins of δEe
– Interpolate between bins by deforming shape of PDF from one bin to next
• Differences from collaboration analysis
– Collaboration divides positrons into only 2 categories based on track fit χ2
, # of hits, etc…
– A PDF for each category is prepared, no interpolation done between them
PDFs: Accidental Positron Energy
δEe<0.345 MeV 0.345≤δEe<0.365 MeVInterpolation of PDF shape
Norm
alized
δE
e

28. PDFs: Signal Positron Energy
• Take signal Ee PDF from resolution component of fit to Michel spectrum
(sum of 2 Gaussians)
• Varies significantly with δEe as one would expect
– Full RMS varies by 60%
– Again interpolate PDF shape between bins
• Average Ee resolution: σcore=310 keV, 83% in core, σtail=1.5 MeV
• Differences from collaboration analysis
– Collaboration uses only the 2 positron categories
– PDF for each category, no interpolation done between them
– Full RMS changes by just ~14%

29. PDFs: Signal Photon Energy
• Eγ resolution from 55 MeV γ source (π0
γγ)
– Gaussian high energy part (σEγ)
– Exponential low energy tail from early
conversions, shower escape through inner face
• Response map prepared in 3D bins of conversion point
– Spatial variations of performance (e.g., PMT saturation near edges)
– Smooth each parameter with series of 2D linear interpolation surfaces
• Resolution: 2.1% (1.1 MeV) for deep events (w>2 cm), ~3% when shallower
• Differences from collaboration analysis
– Same 3D response map is used
– Collaboration does not smooth, arbitrarily similar events may get 40% different PDF widths
σEγ

30. • Plot accidental Eγ distribution in time sidebands
– Hard to model γ’s from different sources, resolution, acceptance, pileup
– Use histogram itself as PDF shape
– Try binning in each of 3 dimensional coordinates of 1st
conversion
• Distribution expected to change due to spatial variations of Eγresolution
• Fit histogram of one bin to other bins of the same coordinate and check for bad χ2
• Only significant variation is with conversion depth (w)
• Use four bins of conversion depth and interpolate PDF shape between
• Differences from collaboration analysis
– Collaboration analysis fits complicated model to distribution
– Full three-dimensional binning in conversion position
– No interpolation between bins
PDFs: Accidental Photon Energy
w<1.5 cm 1.5≤w<3.7cm 3.7≤w<7.2 cm w>7.2 cm

31. PDFs: Accidental and Signal Relative Time
• Accidental time PDF from time sidebands
– Expect flat distribution aside from any trigger effects
– Distribution indeed consistent with flat line
– Flat line used for the PDF
– No event-by-event variation necessary
• Signal time PDF from µ→eνeνµ γ in lower Eγ sideband
– Fit Gaussian + accidental background floor
– No significant variation with event properties
– Use constant PDF
– Resolution in teγ of 150 ps
• Differences from collaboration analysis
– Collaboration prepares different signal PDF for each positron category, width changes by
only 2σ
– Includes correlation of mean of teγ with Ee
• Error in Ee changes path length of projection to timing counter
• Taking signal MC result on faith of ~50 ps / MeV

32. PDFs: Accidental Relative Angles
• Fit accidental φeγ and θeγ distributions in time sidebands to polynomials
• Sensitive to trigger effects and acceptance edge effects
• For fixed φeγ and θeγ, fixing the photon conversion location
almost fixes the full orientation
– Bin φeγ distribution in coordinate along inner face arc (v)
– Bin θeγ distribution in coordinate along beam axis (u)
• Interpolate PDF shape between bins
• Differences with collaboration analysis
– Same technique for binning in conversion coordinates
– No interpolation of PDF shape between bins
φ
θ
u<-12 cm -12 ≤u<-2.5 cm u>14.5 cm

33. • Simulate relative angle resolutions using component resolutions
– Combine the effects of:
• Resolution in e+ angle: from 2 turn tracks
– Measure θe resolution in bins of δEe and
interpolate between them
– Measure φe resolution in bins of δEe and φe,
only interpolate in φe
• Vertex resolution at target:
from measured correlations
– Vertex position error is correlated with
and dominated by angle error
– Measure correlations with data and
tracking algorithm
• Photon position resolution: from lead collimator data + MC
– Resolutions in each of 3 coordinates binned in relevant coordinates
– Smooth parameters of resolution function with interpolation surfaces
– Average relative angle resolutions (full RMS):
θeγ~ 16.8 mrad, φeγ~15.1 mrad
• Differences with collaboration analysis
– Collaboration prepares 2 PDFs for positron angles: 2 categories, no interpolation
– No smoothing of photon position resolutions in the conversion coordinates
PDFs: Signal Relative Angles
-100≤φe<400 mrad 500≤φe<950 mrad
Fixed δEe < 0.258 MeV

34. PDFs: Signal Relative Angle Correlations
• Signal φeγ PDF correlated with signal Ee PDF
– Error in e+ momentum (path length) affects
projection to target
– Size and sign of effect depend on φe
• Signal φeγ PDF correlated with
signal θeγ PDF
– Error in θe affects vertex z and x, and thus φe
– Size depends on e+,γ angle resolutions
• Correlations measured directly with data & tracking algorithm, collaboration relies on
Target
x
y
Correct
Ee
Error in Ee
Target z
x
Correct θe
Error
in θe
Example of simulated
correlation for a certain event

35. PDFs: Radiative Decay
• Relative time PDF is same as signal
• Other variables (Ee, Eγ, φeγ,θeγ ) are correlated by RD BR from theory
• Need to multiply by acceptances and convolve with response functions
– Acceptance and response functions differ for each event
– Strength of correlations differ for each event
– Perform for each event, most computing intensive part of analysis
• Differences with collaboration analysis
– Collaboration folds φeγ,θeγ into opening angle resolution, convolve in (Ee, Eγ, Θeγ)
– Ignores correlation between error in Ee and error in φeγ
– Ignores correlation between error in θeγ and error in φeγ
1D Projections of RD PDF onto each kinematic observable for an example event

36. Confidence Level and Sensitivity
• Need 90% confidence interval on NSig with nuissance parameter NAcc:
• Feldman-Cousins technique using profile likelihood statistic
– At some test point Ni
Sig calculate L ratio for data:
– Generate experiments of Ni
Sig according to PDFs, for each compute:
– Confidence level at test point is probability P(Ri
data>Ri
sim) over the simulations
• Collaboration analysis has 2 nuissance parameters since is NRD floated
• Blind estimates of sensitivity
– Set NSig=0 andNRD,NAcc=expected number in
analysis window
– Simulate ensemble of experiments and
plot distribution of 90% UL
– Median value at 4.9 x 10-12
– Collaboration result of 3.3 x 10-12
– Fit and calculate 90% UL in time sidebands
where no signal is expected: 3-5 x 10-12
( )AccSig NNL ,
),(/ max
max Acc
i
Sig
i
data NNLLR =
),(/
max
max
j
j Acc
i
Sig
i
sim NNLLR =
Best fit NSig
Test NSig
Rdata
Rsim

37. • Fit to analysis window
– Best fit NSig =1.5
– NSig =0 falls in 90% CI
– NSig =8.1 (90% CL UL)
– BR(µeγ)< 7.9 x 10-12
(90% CL)
– 28% of simulated UL’s at this level
or greater for null experiment
• Collaboration result
– Best fit NSig =3.4
– NSig =0 just outside 90% CI
– NSig =10.4 (90% CL UL)
– BR(µeγ)< 9.6 x 10-12
(90% CL)
– 3% of simulated UL’s at this level
or greater for null experiment
• Why the difference?
– UCI selection cuts removed some events including 2nd
ranked event in LSig/Ltotal
End Result
Signal PDF
RD PDF
Accidental PDF
Total

38. Conclusion
• An independent, UCI likelihood analysis was performed on 2009 data to
search for µeγ
• Results consistent with null hypothesis
• BR(µeγ)< 7.9 x 10-12
(90% CL) improves collaboration result by 20%
• Both results improve limit from MEGA
of BR(µeγ)< 1.2 x 10-11
(90% CL)
• Current most stringent published
result is collaboration analysis of
2009+2010 data: BR(µeγ)< 2.4 x 10-12
(90% CL)
• MEG will continue running toward the goal of reaching few x 10-13
sensitivity
Large mixing in ν Yukawas
Small mixing in ν Yukawas

39. Backup

40. Moving Forward from Previous Experience
Exp./Lab Year σRMS Resolutions Stop rate
[MHz]
Duty cycle
[%]
BR
(90% CL)
Ee [%] Eγ [%] ∆teg[ps] ∆θeg[mrad]
LANLLANL 19791979 3.73.7 3.43.4 810810 1616 2.42.4 6.46.4 1.7 x 101.7 x 10-10-10
Crystal BoxCrystal Box 19861986 3.43.4 3.43.4 765765 3737 0.40.4 6.96.9 4.9 x 104.9 x 10-11-11
MEGAMEGA 19991999 0.510.51 1.91.9 680680 77 250250 6.76.7 1.2 x 101.2 x 10-11-11
MEG
prop.
20X
X
0.38 1.7 64 8 30 100 2 x 10-13
• MEG uses continuous muon beam
– Accidental background rate proportional to instantaneous beam rate
– For same resolutions as MEG, MEGA would’ve faced 8 times the
accidental background rate
• MEG utilizes liquid xenon calorimeter
– Good photon timing resolution (43 ps) and high detection efficiency (60%)
– MEGA used Pb layer to convert photon to e+ e- pairs, then measured in drift
chambers
– Thin converter for good energy resolution limits the acceptance (~5%)
– Time resolution ~ 600 ps

41. Systematic Uncertainties
• Sources of systematic uncertainties
– PDF shapes: means, widths, correlation magnitudes
– Predicted number of radiative decays since it is fixed
– Normalization
• Inclusion in the analysis
– In CL calculation: PDF shapes, true NSig, and true NRD fluctuated by estimated
uncertainties
– Get feel for effects by changing things and refitting for Nsig
• Effects from systematic uncertainties: σ(NSig) ~ 0.6
• Largest sources from center of φeγ PDF and teγ resolution
• Effects from statistical uncertainty of fit: σ(NSig) ~ 3