

B  K νν
Theoretical Motivation
 Analysis Procedure
 Systematics
 Results

David Doll,
on behalf of the
BaBar Collaboration
1
APS 04/12/08
B  K  νν
Theoretical Motivation
Standard Model BF
3.810..26 10 6
*535 M
Experimental Limit
on BF (90% CL)*
arXiv:0708.4089v2 [hep-ex],
PRL 99, 221802 (2007)
1.4 10 5
BB pairs at Belle
•Highly suppressed Flavor Changing Neutral Current
•Not well constrained experimentally
•Several models enhance BF(Unparticle Model, MSSM at large tan β,…)
BaBar’s previous best upper limit is 7.8x10-5
for semileptonic tags with 81.9 fb-1
Current analysis at 319 fb-1
2
APS 04/12/08
B  K  νν
Analysis Procedure, Tagging

Perform a ‘semileptonic’ tagged analysis
◦ Fully reconstruct the ‘tag B’ in the decay
◦ Look at the rest of the event for our signal
D
l
0

Tag B
Signal B
B+


K
B-


0 
B D l ν
D0  K  {π  , π  π0 , π  π  π  }
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APS 04/12/08
B  K  νν
Random Forest (RF)

Use a multivariate analysis tool from
StatPatternRecognition (arXiv:physics/0507143v1)
 Sampling with replacement of both the training data and the input
variables (bagging)

Optimize the ‘Punzi’ Figure of Merit

The important input variables:




S
N
 B
2
number of charged tracks in the signal B (opposite the ‘tag B’)
the missing energy in the event
the signal Kaon candidate’s momentum
the unmatched neutral energy in the event
4
APS B->Knunu 04/12/08
Final Predictions, Continuum

Use sideband region in

Estimate the continuum data in the
signal region from amount of data in
sideband
m D0
RF continuum est.
mD0 for K - π 
sideband
5
APS B->Knunu 04/12/08
Final Predictions, Peaking



Peaking estimate from RF output,
separated into m D 0
sideband/signal regions
Subtract sideband from signal
region in both Data and MC and
take the ratio MC:Data
Extrapolate a line into the signal
region
trendline
signal
region
6
APS B->Knunu 04/12/08
Background Systematics

Continuum systematic from difference between MC and data

Peaking background systematic from difference between the
a trendline fit to all the MC:Data, vs. a trendline fit to just
the peaking component (above)

We also take a systematic based on our MC weighting
procedure.
MC Background
prediction
Statistical
Uncertainty
Systematic
uncertainty
7
APS B->Knunu 04/12/08
Control Sample
•Both Bs decay semileptonicly requiring:
•no remaining charged tracks in the event
•momentum of each lepton>1.24 GeV/c
•Resolved differences between signal MC and double tag data:
•particle substitutions
•kinematic corrections
•brute force variable redistribution.
•Serves as control sample for evaluating systematics for the
multivariate analysis.
D0
l
D0
B+
l
B-


8
APS B->Knunu 04/12/08
Signal Systematics

Tagging Efficiency: Taken
from ratio below in which both
0
 
tags are D  K π
double tag
)
single tag
double tag
RMC (
)
singl tag
RData (

Kaon Momentum: Evaluated
by comparing phase space
theory with SM-predicted
theory
9
APS B->Knunu 04/12/08
Signal Systematics

Correlations btwn.
Variables:
◦ 1-D distributions already
resolved
◦ Need to account for correlations
in order use the control sample
to evaluate signal box efficiency
in signal MC
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APS B->Knunu 04/12/08
Signal Systematics

Signal Box Eff.:
◦ Retrain RF with double tag MC
control sample substituted for signal
MC
◦ Evaluate systematic by comparing
efficiency of the RF cut on double tag
MC to double tag data

Ntrkleft=1:
◦ The control sample identified with
this cut, not present in signal MC
◦ Evaluate systematic from separate
rectangular cut based investigation
11
APS B->Knunu 04/12/08
Results

Upper limit at the 90%
confidence level

Expect 30.7 +/- 10.7 events,
corresponding to an upper limit
of 2.9 x 10-5

Inside the RF box, we saw 38
events, which gives an upper
limit:


5
BF(B  K νν)  4.2 10 @ 90% C.L.
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APS B->Knunu 04/12/08