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Investigating b→sγ Decay: Analysis and Implications for Standard Model and Beyond

This presentation by David Doll explores the decay process b→sγ, emphasizing its significance in testing the Standard Model (SM) of particle physics. The motivation for studying this decay stems from its absence at tree level in the SM and the potential for discovering new physics via deviations from expected results. The analysis utilizes advanced methods, including Random Forest techniques, to analyze photon energy spectra and improve branching fraction measurements. The findings suggest that different theoretical models can influence decay dynamics and branching fractions, offering insights that may enhance our understanding of particle interactions.

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Investigating b→sγ Decay: Analysis and Implications for Standard Model and Beyond

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  1. Oral Candidacy Presentation David Doll

  2. Outline • Thesis topic: b→sγ • Motivation • Previous Analysis • Babar overview • Subdetector introduction and impact on thesis • Previous work: • Introduction to Random Forest method • Applications to thesis topic and plans

  3. b→sγ Motivation γ • Flavor changing neutral current decay (absent at tree level in SM) • Precision test of SM • Different models may enhance or suppress the BF Source: U. Haisch, FPCP Conference Taipei, 2008

  4. b→sγ Motivation • For photon energy cut Eγ> 1.6 GeV in B meson rest frame • NNLO theoretical calculation • HFAG experimental results (as of March 15, 2007) Source U. Haisch FPCP Violation 2008 Error associated with subtraction of events Combined statistical and systematic error Systematic uncertainty associate with Ecut = [1.8,2.0]

  5. b→sγ Motivation • Photon 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

  6. Different Photon Models • Shape function of b quark motion is universal • Applicable to all decays involving tranistions to massless states (B→Xsγ, B→ Xdγ, etc.) • Different shape function models exist Source Eur. Phys. Jour. C7, 5-27 (1999) Gaussian Ansatz A.L. Kagan and M. Neubert propose an exponential shape function (KN model): where:

  7. Dependence on Ecut • 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 point • Add nonperturbative pieces to the energy moments • Finally, they investigate the effects of the minimum photon energy cut to evaluate a bias in mb and μπ2 Without perturbative corrections Complete bias difference Source D. Benson, I.I. Bigi and N. Uraltsev FPCP Violation 2004

  8. Other Photon Models • B. 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: First and second moments are directly relatable to and μπ2 and: Is a good model for Exponential, gaussian, or hyperbolic

  9. Search Strategy for b→sγ • Performing a sum of exclusive states • 38 states total • Update of former analysis published in Phys. Rev. D (2005) 052004 • Based on 89.1 fb-1 of data collected at the Y(4S) Source Babar doc

  10. On CP Asymmetry Measurement • Because 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 data • Possible source of other new physics • Search to be performed in another analysis Source Babar doc

  11. Former Analysis Procedure • Reconstruct event candidates into the 38 different decay modes • Use a Neural Network to reject continuum events based on event shape variables • Set the lower cutoff energy at Eγ> 1.9 GeV (or equivalently at MXs between 0.6-2.8 GeV/c2) to limit peaking B background • Choose the ‘best’ candidate as the one that minimizes ΔE Source Babar doc

  12. Former Analysis Procedure • 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 function • As 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

  13. 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

  14. Impact of competing models • Ideally, photon spectrum measurement is model independent • Analysis 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 chosen • Measure parameters in all models considered (everyone’s happy)

  15. Results of Former Analysis • Quote results of KN fit, ‘kinetic’ model (BBU from above), and ‘shape function’ models (average of 3 BNP shapes from above) Source Babar doc

  16. PEP-II at SLAC Source Babar Doc • 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 = 0.56 • B meson lifetime 1.5-1.6 ps → Δz ≈ 250-270 μm • Turned off in April with a total of ~485 fb-1 at or just below the Υ(4S).

  17. Babar Detector Solenoid Magnet (1.5 T) EMC e + DIRC SVT e - DCH IFR

  18. Subsystems Overview

  19. SVT and DCH SVT DCH • SVT • 5 layers of double-sided silicon strip sensors • φ measuring strips parallel to the beam, z measuring strips perpendicular to the beam • 20-40 μm resolution in all 5 layers. • DCH • 7,104 small drift cells arranged in 40 cylindrical layers • dE/dx measured by total charge deposited in each cell Source Babar doc

  20. DIRC • Particle ID for particles with momentum above 750 MeV/c • 144 fused, synthetica silica bars arranged in a 12-sided polygon • Readout by 11,000 PMTs Source Babar doc

  21. IFR Muon efficiency Pionmis-id rate • Segmented steel flux return (later also brass), instrumented in gaps • Originally used resistive plate chambers (RPC) to detect streamers from ionizing particles • Upgraded to limited streamer tubes (LST) starting in 2004 RPC data LST data Source Babar doc.

  22. EMC • Designed to operate over the energy range of 20MeV to 9GeV • 6,580 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 endcap • Each crystal read out by two 1cm2 Si photodiodes • Calibration 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.

  23. 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 arXiv:0708.4089v2 [hep-ex]

  24. 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 Tag B Signal B

  25. Analysis Procedure, Cuts • Separately pursued two different techniques to suppress background • Standard Rectangular Cut method • More sophisticated Multivariate technique with a Random Forest • For Rectangular Cuts, separated the Monte Carlo (MC) into 3 sets: train, valid, test; in a 2:1:1 ratio • Optimized the ‘Punzi’ Figure of Merit: Where S is the number of signal, Nσ is the sigma level of discovery, and B is the number of background

  26. Rectangular Cut Results

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