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Diphoton+MET: FAR Followup

This talk discusses the optimization and background estimation process for the Diphoton+MET signal regions. The focus was on refining the background estimation, including the reweighting of the QCD diphoton model and the confirmation of the electron and jet -> gamma fake models. The Wgamma gamma signal was constrained with the lepton-gamma gamma control region, and the Zgamma gamma mode was estimated from MC simulations. Further analysis was done to compare the cross sections from different calculations, and improvements in the background estimation were made. The talk concludes with the validation region results.

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Diphoton+MET: FAR Followup

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  1. Diphoton+MET: FAR Followup Osamu Jinnouchi Tokyo Tech Stefano Manzoni Milano Max Baugh, Ryan Reece, Bruce Schumm (presenter) SCIPP 26 May 2017

  2. Signal Regions

  3. Signal Regions

  4. Signal Regions

  5. STATUS AT FAR (May 3 2017) • Optimization done; focus was background estimation • QCD diphoton model from SHERPA, but required reweighting to refine Data/MC agreement • Electron   fake model in place and confirmed • Jet   fake factors from photon isolation determined and initial backgrounds estimated • W signal constrained with lepton- control region, complete up to small tweaks (see this talk) • Z mode from SHERPA, but cross section needed confirming

  6. Signal Regions

  7. Diphoton MC Reweighting Njet = 0 Njet = 1 Njet > 1 Before After

  8. Signal Regions

  9. JET   Background New fake-factor estimates base on loose-vs-tight rather than anti-isolated-vs-isolated Switch from isolation to photon-ID fake factors provides somewhat better control of background estimate (particularly in the barrel)

  10. Electron   Fakes • For each of the five SRs, form data sample with all requirements, except replace one of the gammas with an electron • Scale with fake factor (below) determined via Z  ee events (Milano, La Plata)

  11. W Background As presented in the FAR, constrain with l control region Introduces scale factor of 1.59  0.64  0.68, where the systematic error arises from an assumption of 100% uncertainty on the non-W backgrounds.

  12. Z Background: ISSUE • Z background contributions are small; we have always estimated them directly from MC • Z simulated with SHERPA MC  Leading order + parton-shower corrections • Nominal Cross section taken from metadata • There exists an NLO calculation (Bozzi et al., arXiv:1107.3149v1 [hep-ph]) with theoretically controlled uncertainties • Project: Compare total cross sections from Bozzi and Sherpa and come to some conclusion or other

  13. FURTHER ISSUE • SHERPA sample generated at 13 TeV with certain cuts • Bozzi calculation for 14 TeV with other cuts • Biggest difference is photon pT cut (30 GeV for Bozzi and 50 GeV for SHERPA), then beam energy • Must figure out a way to compare apples to apples • Approach: Use MadGraph to reproduce Bozzi, then change MadGraph cuts to compare to SHERPA and hope for agreement. • We don’t see agreement (and we didn’t in Run I either; too small to worry about for our strong production 2015 analysis)

  14. MadGraph vs. Bozzi Cuts used in 14 TeVBozzi calculation: • pT,> 30 GeV; || < 2.5 • R > 0.4 • Various parton-photon separation cuts that shouldn’t make any difference at leading order (and seem not to) Results for total Leading Order Z(ll) cross section, per species l of neutrino: ~5% agreement

  15. Now apply SHERPA cuts to MadGraph Cuts used in 13 TeV SHERPA generation: • pT,> 50 GeV; || < 9999. • R > 0.2 • M > 10 GeV • “Photon isolation cut” Apply cuts in black to 13 TeV Z() MadGraph calculation (couldn’t figure out how to easily apply green cuts, but note that those would lower the MadGraph result further. (Again, per neutrino species)

  16. Compare Bozzi to Sherpa via MadGraph Cuts used in 13 TeV SHERPA generation: • pT,> 50 GeV; || < 9999. • R > 0.2 • M > 10 GeV • “Photon isolation cut” Apply cuts in black to 13 TeV Z() MadGraph calculation (couldn’t figure out how to easily apply green cuts, but note that those would lower the MadGraph result further. (Again, per neutrino species)

  17. Z Summary • Using MadGraph, we translated the Bozzi NLO calculation for the Z cross section onto the SHERPA MC sample • The Bozzi calculation produces has an estimated uncertainty of less that 20%, but the cross section is about 45% lower than that determined by SHERPA • We also observed this for the 8 TeV analysis. • Some cuts made during the SHERPA generation were not applied to the translation of the Bozzi result to the SHERPA phase space, but these would only increase the discrepancy (probably slightly) • We have lowered the Z cross section in our analysis by (45  45)%, as we did for 8 TeV.

  18. Validation Region Results  Statistical error only!!

  19. Background Results: Strong Production Systematic Error

  20. Background Results: EW Production and Model-Independent Selection

  21. Wrap Up • Optimization unchanged from time of FAR • Background model largely in place at time of FAR; since then small adjustments have been made to finalize the estimates • Overall background estimate changes on order to ~10% • Background levels and systematics fully estimate • Validation regions look pretty good; pulls amplified by lack of systematic error estimate (remaining task) • Get very close to unblinding request (just VR errors in our minds.

  22. The Gluino-Bino Grid

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