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

Steven H. Robertson Stanford Linear Accelerator Center Outline Motivation Hadronic B reconstruction B+ g K+nn selection Sideband samples and backgrounds Results and future prospects 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

Steven H. Robertson Stanford Linear Accelerator Center Introduction Standard Model b g s nn process is a flavour-changing neutral-current process occurring via loop and box diagrams Potential for significant enhancement from additional non-SM diagrams Inclusive B g Xsnn is theoretically clean, but very difficult experimentally Look instead for exclusive decay modes Best published limit is from the CLEO experiment: Br(B+ g K+nn)SM ~ 4 x 10-6 Br(B+ g K+nn) < 2.4 x 10-4 at 90% CL 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

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- 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+ 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

Steven H. Robertson Stanford Linear Accelerator Center B reconstruction Exclusively reconstruct B decay modes in hadronic final states: ereco = (0.131  0.006  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) 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

Steven H. Robertson Stanford Linear Accelerator Center Event shape cuts Reduce continuum backgrounds by exploiting topological differences between Y(4S) g BB and “continuum” events f e+ e- B PB~320 MeV Require angle between the thrust axes defined by the reconstructed B and by everything else to satisfy: |cos qT|<0.8 Thrust magnitude: |T| <0.925 (reject residual tt background) B+ g K+nn simulation Data and background simulation 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

B+ g K+nn signal selection Signal “signature” is a single kaon and nothing else recoiling against the opposing reconstructed B Require exactly one track, identified as a kaon, with charge opposite that of the reconstructed B 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

Kaon momentum spectrum Buchalla et al. (hep-ph/0006136) Faessler et al. (hep-ph/0205287) Phase-space Signal kaon has a fairly hard momentum spectrum Require PK >1.5 GeV to further reduce backgrounds Differential decay rate (arbitrary units) Effective q2 cut nn invariant mass (q2/mB2) Some theoretical uncertainty due to modeling of decay form factors “New physics” also potentially has different spectrum 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

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) 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

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) 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

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) 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

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) 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

Steven H. Robertson Stanford Linear Accelerator Center Control sample yields All control samples consistent with Monte Carlo simulation at the level of the available statistics Estimate combinatoric 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 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

Steven H. Robertson Stanford Linear Accelerator Center Results Observe three events in signal region in 80.7 fb-1 of data consistent with expected background of 2.7  0.8 Overall selection efficiency of etot = (0.046 0.005)% Limit computed using modified frequentist approach (Cousins & Highland) Systematic uncertainties modeled in “toy” Monte Carlo by Gaussians Limit set at branching fraction value at which 10% of toy experiments give less than observed number of signal candidates Br (B+ g K+ nn) < 1.05 x10-4 at 90% CL BABAR PRELIMINARY (March 2003) 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

B+ g K+nn (semileptonic reco) D0 B+ B- e- n Previous BABAR analysis based on a semileptonic B- g D0 l- n X0 reconstruction sample Search based on 50.7 fb-1 of data Observed two events in signal region (treated as signal for limit determination) expected background ~2.2 Eextra (GeV) Br (B+ g K+ nn) < 9.4 x10-5 at 90% CL BABAR PRELIMINARY (Spring 2002) 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

Combined B+ g K+nn result Analyses are statistically independent and so can be combined to give a single result: Combined limit : Semileptonic reconstruction: Br (B+ g K+ nn) < 9.4 x 10-5 at 90% CL (50.7 fb-1) Hadronic reconstruction: Br (B+ g K+ nn) < 10.5 x 10-5 at 90% CL (80.7 fb-1) Br(B+ g K+nn) < 7.0 x 10-5 at 90% CL Standard Model prediction: Br(B+ g K+nn) ~ 4 x 10-6 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

Conclusions and prospects New B+ g K+nn search based on 80.1 fb-1 data set (87M BB pairs) using hadronic B reconstruction Observe three events consistent with background prediction of 2.7  0.8 Combine this result with previous statistically independent result using semileptonic tags to give combined limit of Expect significant increase in BABAR data set over next several years (factor of ~10 – 20 by 2009) Add also B g K*nn and neutral B0 g K0(*)nn modes Significantly increased sensitivity to b g s nn process Br (B+ g K+ nn) < 1.05 x 10-4 at 90% CL (Hadronic reconstruction) Br (B+ g K+ nn) < 7.0 x 10-5 at 90% CL (Combined limit) 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

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 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

Steven H. Robertson Stanford Linear Accelerator Center The BABAR Detector 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

B+ g K+nn (hadronic tags) Limit also the extra neutral energy: Eextra < 300 MeV Observe three events in the signal region Predicted background: (2.7  0.8) Overall efficiency: (0.046 0.005)% B+ g K+nn simulation Data Data Br (B+ g K+ nn) < 1.05 x10-4 at 90% CL BABAR PRELIMINARY 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

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 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

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 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

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) 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

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) 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center

K – p separation with the DIRC pions >3s K – p separation up to ~4 GeV kaons 31 December 2018 Steven H. Robertson Stanford Linear Accelerator Center