1. Optimizing Higgs Analysis at DØ John Sandy – SULI Intern (Texas Tech University) Mentors: Michael P Cooke and Ryuji Yamada (Fermilab National Accelerator Laboratory) John Sandy - 8/9/121

2. Optimizing Higgs Analysis at DØ Physics – The Standard Model and the Higgs Mechanism The Standard Model of Particle Physics: Three generations of matter Quarks and Leptons Force Carriers Initially predicted that particles should be massless! Peter Higgs and his colleagues (Englert, Brout, Guralnik, Hagen, Kibble) came to rescue in 1964 and introduced what is now known as the Higgs Mechanism. John Sandy - 8/9/122

3. Optimizing Higgs Analysis at DØ The Higgs Boson Excitation of the Higgs field (analogous to photon in E&M field) Gives mass to all particles Interacts more frequently with more massive particles, attributing more mass to them The Higgs FieldTwo particles attempting to move across the Higgs Field. More massive Less massive John Sandy - 8/9/123

4. Optimizing Higgs Analysis at DØ Higgs Boson Signal vs. Background The Higgs boson has been notoriously difficult to search for: Complex, mass dependant branching ratios Low production rates Lots of SM backgrounds John Sandy - 8/9/124

5. Optimizing Higgs Analysis at DØ The DØ Detector Inner silicon detector Scintillating fiber tracking system 2 tesla solenoid Uranium liquid argon calorimeter Large muon system 900,000 individual channels The Tevatron provided proton-antiproton collisions with a center of mass (CM) energy of 1.96 TeV John Sandy - 8/9/125

6. Optimizing Higgs Analysis at DØ Event Displays with D0Cafvis John Sandy - 8/9/126

7. Optimizing Higgs Analysis at DØ The Higgs Boson Search at DØ My search is focused on four Higgs final states: H → WW → lνlν WH → lνbb ZH → llbb ZH → ννbb Pre-selection: Triggering Lepton Tagging “b-tagging” Electron / muon events 0tag, 1tag, 2tag, loose, medium, tight John Sandy - 8/9/12 7

8. Optimizing Higgs Analysis at DØ The Higgs Boson Search at DØ Boosted Decision Trees (BDTs) Mass jj > 120 Pass Fail ? ? p p f f … and so on … S / B BDT makes cuts based on signal purity parameters Never throw out any data, so no chance of losing signal Bins that pass more cuts have higher signal to background ratio John Sandy - 8/9/128

9. Optimizing Higgs Analysis at DØ Using BDTs to train Multi-Variate Analyses (MVAs) Create a variable list to build a BDT Run analysis framework and prune variable list: Variable Importance Variable Correlation Variable Modeling …. I used BDTs to train MVAs for separating Higgs boson signal from the tt, V + jets, and VV backgrounds John Sandy - 8/9/129

10. Optimizing Higgs Analysis at DØ Variable modeling based on simulation: Well modeledPoorly modeled Using BDTs to train Multi-Variate Analyses (MVAs) John Sandy - 8/9/1210

11. Optimizing Higgs Analysis at DØ Using BDTs to train Multi-Variate Analyses (MVAs) BDTs expected signal and background separation My own training for Higgs vs. VV background discrimination Multijet training that I am helping train John Sandy - 8/9/1211

12. Optimizing Higgs Analysis at DØ Final BDTs (Low Mass) After training, the final BDTs are produced and can be used to separate signal from background John Sandy - 8/9/1212

13. Optimizing Higgs Analysis at DØ Final BDTs (High Mass) John Sandy - 8/9/1213

14. Optimizing Higgs Analysis at DØ Final BDTs for 2-Tight Tag Events (Low Mass) John Sandy - 8/9/1214

15. Optimizing Higgs Analysis at DØ Conclusions The training of secondary MVAs has shown improvement in other channels (4jet) Further training may improve modeling When training is fully completed, improved MVAs will improve overall Higgs search at the Tevatron, allowing for stronger results Recompiled D0Cafvis will allow DØ collaborators to use event displays in future talks and presentations (already been used at DØ collaboration meeting in UK) John Sandy - 8/9/1215 On July 4 th CERN announced a new “Higgs like” particle using γγ and Z-Z channels DØ and CDF recently published results claiming evidence for such a particle using the bb channel

16. Optimizing Higgs Analysis at DØ This work was supported by the Experimental Particle Physics Division at Fermilab National Accelerator Laboratory, U.S Department of Energy Office of Science’s and Office of Workforce Development for Teachers and Scientists. I would like to thank my mentors Ryuji Yamada and Michael P. Cooke. I would also like to thank Anthony Podkowa and Herb Greenlee for their assistance. Acknowledgments John Sandy - 8/9/1216

17. Optimizing Higgs Analysis at DØ Backup John Sandy - 8/9/1217