1. A search for the rare decay B+ g K+nn
Steven Robertson
Stanford Linear Accelerator Center

2. Steven H. Robertson Stanford Linear Accelerator Center
Introduction
The Standard Model flavour-changing neutral-current process b g s nn occurs via loop and box diagrams:
Theory prediction:
Potential for significant enhancements from non-SM processes
Br( B+ g Xs+nn )SM ~ 4.1 x 10-5
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

3. Steven H. Robertson Stanford Linear Accelerator Center
B g Xsnn
Inclusive B g Xsnn is theoretically very clean, but is also very difficult experimentally
Look instead for exclusive decay modes:
Can also look for the corresponding neutral B decay modes:
B0 g K0s nn , B0 g K*0 nn
Best published experimental limit (CLEO):
Plenty of room for new physics!
Br( B+ g K+nn )SM ~ 4 x Br( B+ g K*+nn )SM ~ 1.3 x 10-5
~20% of inclusive rate
Br( B+ g K+nn ) < 2.4 x at 90% CL
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

4. Steven H. Robertson Stanford Linear Accelerator Center
B+ g K+nn with BABAR
In B-factory environment, B decays are produced via
Current BABAR analysis based on 80.1 fb-1 data set
(86.9  1.0) x 106 BB pairs
e+ e- g Y(4S) g B+ B-
at ~10.5 GeV in the CM frame
Need to determine that the Kaon is not accompanied by additional (charged or neutral) particles
Exclusively reconstruct hadronic B decays in order to identify tracks and clusters associated with the opposing B
Y(4S) B- B+ n K+
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

5. Steven H. Robertson Stanford Linear Accelerator Center
The BABAR Detector
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

6. Hadronic B reconstruction
Exclusively reconstruct “tag-B” decay modes in hadronic final states:
etag =
(0.131   0.009)%
~ 114k reconstructed B mesons!
Energy
substituted mass:
difference:
B- g D0 X-
K- p+
K- p+ p0
K- p+ p- p+
B+ g K+nn simulation
X- system: up to three charged tracks (K, p) and two additional p0
Data and background simulation
mES (GeV/c2)
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

7. Continuum backgrounds
Reduce continuum backgrounds by exploiting topological differences between Y(4S) g BB and “continuum” events f e+ e- B
PB~320 MeV
Thrust magnitude:
|T| <0.925
(reject residual tt background)
Require angle between the thrust axes defined by the reconstructed B and by everything else to satisfy:
|cos qT|<0.8
B+ g K+nn simulation
Data and background simulation
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

8. Steven H. Robertson Stanford Linear Accelerator Center
B+ g K+nn selection
Exploit the low multiplicity of B+ g K+nn signal events
Number of tracks
B+ g K+nn simulation
Data and background simulation
Require exactly one charged track (kaon), recoiling against the reconstructed B
Eextra (GeV)
B+ g K+nn simulation
Limit also the total “extra” energy in the calorimeter:
Eextra < 300 MeV
(Sum of all clusters with E>30MeV )
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

9. Steven H. Robertson Stanford Linear Accelerator Center
Kaon identification
Excellent charged kaon identification using the quartz Cerenkov detector (DIRC)
pions
>3s K–p separation up to ~4 GeV
kaons
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

10. Steven H. Robertson Stanford Linear Accelerator Center
Kaon momentum
Buchalla et al. (hep-ph/ )
Faessler et al (hep-ph/ )
Phase-space
nn invariant mass (q2/mB2)
Differential decay rate (arbitrary scale)
Effective q2 cut
B+ g K+nn signal kaon typically has fairly high momentum:
Require PK >1.5 GeV to further reduce backgrounds
B+ g K+nn simulation
Data and background simulation
Some theoretical uncertainty introduced due to modeling of decay form factors
“New physics” also potentially has different spectrum
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

11. Steven H. Robertson Stanford Linear Accelerator Center
Control samples
Use data control samples from several “sideband” regions to validate MC modeling and background estimates
mES (and “large” mES)
Eextra >0.5 GeV
Ntrks=2
Ntrks=3
Various samples test different aspects of the analysis, e.g.
peaking vs combinatorial background
MC modeling of Eextra endpoint
Eextra (GeV)
“Blinding box”
Signal region
mES (GeV/c2)
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

12. Steven H. Robertson Stanford Linear Accelerator Center
Control sample yields
All control sample yields are consistent with Monte Carlo simulation at the level of the available statistics
Estimate combinatorial background in signal region by extrapolating mES sideband into signal region (adds an additional 1.0  0.4 background events)
MC/data type
Signal region
mES
Large mES
Eextra
Ntrks=2
Ntrks=3
B+B-
1.7  0.6
1.1  0.5
7.0  1.4
3.3  0.9
17.4  1.9
54.6  3.4
B0B0
1.4  0.6
0.6 0.4
0.9  0.5
3.5  1.0
uds
1.8  1.0
14.0  2.9
2.4 1.2
0.6 0.6
1.2  0.9 cc
11.1  2.6
1.9 1.0
3.1  1.4 tt
Onpeak data
Total MC
(80.1 fb-1) 3
2.7  0.7 7
4.8  1.7 31
33.5  4.2 10
8.8  2.0 21
20.7  2.3 55
62.4  3.9
Offpeak data
Continuum MC
(9.58 fb-1)
0.11 0.05
0.4  0.2 1
3.0  0.5
0.6  0.2
0.3  0.1
0.5  0.2
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

13. Hadronic tag-B results
Observe three events in signal region in 80.7 fb-1 of data consistent with expected background of 2.7  0.8 events
Overall selection efficiency:
etot = (0.046 0.005)%
Branching ratio limit:
B+ g K+nn simulation
Data and background simulation
Br( B+ g K+ nn ) < x 10-5
at 90% CL
BABAR PRELIMINARY
(hep-ex/ , March 2003)
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

14. Semileptonic tag-B reconstructionK+ D0 B+ B- e- n
Previous BABAR search for B+ g K+ nn based on a semileptonic B- g D0 l-n X0 reconstruction sample
Higher reconstruction efficiency, but fewer kinematic constraints
Analysis based on 50.7 fb-1 of BABAR data
Observed two events in signal region (treated as signal for limit determination)
Eextra (GeV)
Br( B+ g K+ nn ) < 9.4 x at 90% CL
BABAR PRELIMINARY
(hep-ex/ Spring 2002)
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

15. Results and future prospects
Hadronic and semileptonic B reconstruction methods produce statistically independent samples
combine the two analyses to give an improved limit:
Plans:
Extend existing B+ analysis to include K*+nn final state
Perform B0 gK0nn and B0 gK*0nn searches using the corresponding hadronic and semileptonic B0 reconstruction samples
Add additional new BABAR data
Br( B+ g K+nn ) < 7.0 x at 90% CL
Factor of ~2.5 improvement on best published exclusive limit
a Double the effective sensitivity to B g Xsnn
a Double present data set by 2004
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

16. Steven H. Robertson Stanford Linear Accelerator Center
Backup slides
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

17. The BABAR Collaboration
USA [35/276]
California Institute of Technology
UC, Irvine
UC, Los Angeles
UC, San Diego
UC, Santa Barbara
UC, Santa Cruz
U of Cincinnati
U of Colorado
Colorado State
Florida A&M
U of Iowa
Iowa State U
LBNL
LLNL
U of Louisville
U of Maryland
U of Massachusetts, Amherst
MIT
U of Mississippi
Mount Holyoke College
Northern Kentucky U
U of Notre Dame
ORNL/Y-12
U of Oregon
U of Pennsylvania
Prairie View A&M
Princeton
SLAC
U of South Carolina
Stanford U
U of Tennessee
U of Texas at Dallas
Vanderbilt
U of Wisconsin
Yale
The BABAR Collaboration
9 Countries
72 Institutions
554 Physicists
Italy [12/89]
INFN and U Bari
INFN and U Ferrara
Lab. Nazionali di Frascati dell' INFN
INFN and U Genova
INFN and U Milano
INFN and U Napoli
INFN and U Padova
INFN and U Pavia
INFN, SNS and U Pisa
INFN, Roma and U "La Sapienza"
INFN and U Torino
INFN and U Trieste
Norway [1/3]
U of Bergen
Russia [1/13]
Budker Institute, Novosibirsk
United Kingdom [10/80]
U of Birmingham
U of Bristol
Brunel University
U of Edinburgh
U of Liverpool
Imperial College
Queen Mary & Westfield College
Royal Holloway, University of London
U of Manchester
Rutherford Appleton Laboratory
Canada [4/16]
U of British Columbia
McGill U
U de Montréal
U of Victoria
China [1/6]
Inst. of High Energy Physics, Beijing
France [5/50]
LAPP, Annecy
LAL Orsay
LPNHE des Universités Paris 6/7
Ecole Polytechnique
CEA, DAPNIA, CE-Saclay
Germany [3/21]
U Rostock
Ruhr U Bochum
Technische U Dresden
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

18. Steven H. Robertson Stanford Linear Accelerator Center
DIRC
(Detector of Internally Reflecting Cherenkov)
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

19. Steven H. Robertson Stanford Linear Accelerator Center
MC and data samples
Analysis based on Run1+2 data set (80.7 fb-1)
Use all available generic MC (VubRemoveOrphans for <10.3.1a)
MC type
Equivalent lumi (fb-1)
B+ g K+nn
254k events
B+B-
288
B0B0
277
uds
131 cc
130 tt
137
Onpeak data
80.07
Offpeak data
9.58
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

20. Systematic uncertainties
Systematic uncertainty estimates derived from MC - data comparison
Dominated by MC statistics and tag B reconstruction efficiency
Source
se / e (%)
Signal MC statistics
4.9
Tag B yield 7
Track reconstruction
1.3
Kaon particle ID 2
Eextra modeling
MC generator model 3
Total 10
Source
s bg/bg (%)
Generic MC statistics 27
Tag B yield 7
Track reconstruction 5
Eextra modeling 2
Total 29
Limit computed using modified frequentist approach (Cousins & Highland)
Uncertainties modeled in “toy” Monte Carlo by Gaussians
Limit set as value at which 10% of toy experiments yield less than observed number of signal candidates
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

21. Steven H. Robertson Stanford Linear Accelerator Center
Missing momentum
Requiring low charged and neutral multiplicity enhances backgrounds from events with unreconstructed particles (i.e. outside of detector acceptance)
Require the event missing momentum vector to satisfy |cos qPmiss|<0.8
Signal-B selection efficiency
esig =(35.0 0.5  1.1)%
(Buchalla et al. model)
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

22. Calorimeter energy deposition
Limit the amount of calorimeter activity which is not associated with the reconstructed B decay products
Require no signal-side p0 candidates
Limit also the total extra calorimeter energy:
Eextra < 300 MeV
(Sum of all clusters with E>30MeV )
Eextra (GeV)
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

23. Steven H. Robertson Stanford Linear Accelerator Center
Control samples
Eextra distribution in mES sideband
Dominated by continuum backgrounds
Onpeak data
Onpeak data
Offpeak data
Eextra (GeV)
Offpeak data
Eextra distribution in Ntrks=3 sideband
Dominated by peaking BB background
Eextra (GeV)
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

24. Semileptonic tag sample
Comparatively high statistics due to large b g c l n branching ratio
~5500 events per fb-1
Missing neutrino reduces available kinematic constraints
use kinematics of D0 - l combination:
Possibility of additional photons from D(*)0 g D0 g/ p0 feeding into signal channel B- n D0 L- K- p+
from Y(4s)
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center

25. B+ g K+nn (semileptonic tags)
Based on 50.7 fb-1 of BABAR data
Will be updated to full data set in the near future
Signal region defined as a box in Eextra and the reconstructed invariant mass of the tag-side D0
Observe two events in signal region (treated as signal for limit determination)
expected background ~2.2
Signal region
Sideband region
Br (B+ g K+ nn) < 9.4 x10-5 at 90% CL
BABAR PRELIMINARY
(Spring 2002)
27 December 2018
Steven H. Robertson Stanford Linear Accelerator Center