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This article covers small physics reminder, Zbb vs. + jet, selection without STT, background rejection, and calibration procedures. It explores ways to enhance signal resolution in Higgs search, particularly aiming to improve bb mass reconstruction resolution from 15% to <10%. The significance evolution with resolution at Mhiggs=120 GeV is examined, along with the impact on signal events for different processes. The complementary nature of Zbb and + jet selections, their systematics, and resonance mass independence of multiple interactions are discussed. Methods to select events without STT and the importance of stringent selection criteria are highlighted. Various physics processes, trigger mechanisms, and expectations from Pythia simulations are analyzed. The article also delves into discriminating variables, kinematic features, and neural network applications to enhance signal purity and reduce background noise in the Higgs search. The calibration process for b-jets versus q-jets, improvements in jet responses, and overall data selection are debated for better results in the future.
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Z bb Physics and Calibration • Small physics reminder • Z bb vs + jet • Selection w/o STT, Background rejection • Calibration procedures • A few plots on the Hit-Root-tuples
Higgs Search If Mhiggs < 135 GeV promising channel: pp WH l b b Signal to background depends crucially on b b mass reconstruction resolution Can we go from 15% resolution to <10% ?
Higgs Search Significance evolution with resolution at Mhiggs=120 GeV bb mass Resolution: 15% 10% Signal events/fb-1 4 4 Wbb 59 32 WZ 11 6 tt 34 24 single top 14 10 For 10 pb-1
Z bb vs + jet + jet : high statistics, allows for a tight b-jet selection (b-tagging). Systematics are not straightforward. Z bb: very low signal/noise but systematics closer to physics processes (H or Top), due to high pT . Resonance mass independent of mult. interactions. Complementarity !!
Z bb selection D0 will start without STT (and run this way about a year) Can we select these events w/o STT? CDF Run I S/N below 10-3 implies very stringent selection. On the total Run I lumi, only 45 events left, starting from about 120 000 Z bb events Trigger: central muon (pT> 7.5 GeV) 5.5 M evnts Offline: request 2 tagged (0.7 cone) jets 5479 evnts According to Pythia: expect 124 +/-14 evnts Needs further topological cuts
3ET and 12 • Signal and background are produced differently: Z is produced by a time-like q-qbar anihilation, Background is QCD induced. Color flow between initial and final partons only in the bckgd. Z is expected to have soft radiation between the jets, Background will also have strong radiation between IS and FS partons. Use 2 kinematic variables to discriminate • 3ET : sum of ET of the clusters outside the 2 leading jets • 12 : azimuthal angle difference between the 2 jets
QCD and E_Weak Samples • Discriminating power of the 2 variables 3ET and 12 on 2 samples of different origin
Z bb Signal • 3ET < 10 GeV 12 > 3 rad • Now S/N=1/6 at the Z mass peak • Select/antiselect w.r.t. the 2 var., tag probability • 3.2 excess • Background only
Z bb Sample 3ET
Likelihood fit to the Dijet Sample • Signal + Bckgd • Background only • Results: MZ=90.0 +/- 2.4 GeV Z = 9.4 +/- 3.5 GeV NZ=91+/30(st.)+/19(sys.)
Neural Net ? • With only 2 topological cuts, strong background reduction. • Neural net on further variables will improve purity, but input variables must be decorrelated from calibration variables. • With 0.4 fb-1, if S/N better than 1/2 precision on absolute scale may be better than 1% • With the STT, much purer sample, i.e. expect furter improvement
How to calibrate??? • On detailed MC, compare b-jets with light-q jets. Root-tuples available for b-jets (Hit), on request for q-jets. • Expect: wider b-jets (due to the large b-mass) , muons from semileptonic decays (to be corrected). study track multiplicity, and E/p to improve the jet response using Track+Calo • Devise a relative calibration b-jets vs q-jets from MC • Check it on the Z bb data sample selectionned with a Neural Net, while awaiting for the STT
Back To Earth: Root-tuples Hit Group Root-tuples : follow the colour code: Z-> bb , Z-> tau-tau , Z-> ee , Z-> mu-mu 8000 Events in each sample. Includes min. bias events To start: Compare Basic distributions
Conclusions • Hit Group Root-tuples are a good Tool to start • A few variables could be added, others improved • Need of Z -> qq to make real progress • Selection of Z->bb will require Neural Net • Calibration of b-jets will take time, but start now to implement track+cell for jets