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Plan for Large Extra Dimensions Search in the Diphoton Final State

This analysis note and PAS discusses the search for ADD signals in the diphoton final state, including the sensitivity with early CMS data and the necessary steps to determine it. It covers the generation of ADD signal samples, understanding high pT photons, estimating background and kinematic optimization, photon selections, and prompt photon subtraction.

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Plan for Large Extra Dimensions Search in the Diphoton Final State

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  1. Plan for Large Extra Dimensions Search in the Diphoton Final State John Paul Chou, Selda Esen, Greg Landsberg and Duong Nguyen Brown University Exotica non-resonance meeting Nov. 19, 2009

  2. Analysis Note and PAS

  3. What are we looking for?: ADD signal • Drell-Yan like virtual graviton production resulting diphoton final state. • Interference with SM  enhancement of the diphoton invariant mass spectrum, especially at high end. • Exhibits itself as a continuous spectrum (energy space between adjacent modes is ~ 1/R ~ 1 meV – 100 MeV). Determine the sensitivity of the diphoton channel with early CMS data.

  4. What should be done? • Generate ADD signal samples • Understand high pT photons (pT > 50 GeV): reconstruction, photon identification. • Estimate the photon selection efficiency • Estimate backgrounds

  5. Kinematic optimization • Chosen cuts: |η| < 1.5 and Mγγ> 700 GeV • Low invariant mass band is used to normalize SM diphoton background

  6. Photon selections • Kinematic cuts: ET > 50 GeV and |eta| < 1.5 • Raw photon is an ECAL supercluster with loose H/E cut  apply photon identification (photon ID) isolation cuts (reduce jet faking photon background) • HadronicOverEM < 0. 05 • Ratio of EM cluster energy and highest Hcal Rechit energy within dR < 0.1 of supercluster (Change to tower-based energy sum in 31X) • Tracking isolation < 5.0 GeV • Sum pT of tracks in hollow cone 0.04 < dR < 0.4 ofsupercluster • ECAL isolation < 10 GeV • Sum pT of ECAL rechits in hollow cone 0.06 < dR < 0.4 of supercluster • HCAL isolation < 4.7 + 0.003 ET GeV • Sum ET of HCAL rechits in hollow cone 0.1 < dR < 0.4 of supercluster • ET dependence cut to keep efficiency constant in ET • We apply a pixel seed veto to remove electron • Efficiency of pixel seed veto is (99 ± 1)%

  7. MC photon ID efficiency • Denominator consider all reco photons matched to MC photon. • Combine efficiency is ~85% efficiency and flat in ET and η

  8. Data-driven photon ID efficiency • Apply tag-and-probe method on Z->ee sample to estimate efficiency of electron passing photon ID isolation cuts: • Tight selection on tag leg: photon ID isolation + a track pT > 25 GeV within dR = 0.04 of SC • Probe leg: no photon ID isolation + a track pT > 25 GeV within dR = 0.1 of SC • Apply conservative 5% systematic on photon efficiency

  9. Background • Irreducible SM diphoton • Dominant background • Estimated from MC and normalized to data at low invariant mass • Dijet • Photon + jet • High mass Drell-Yan (e+e-) • Electron fake rate Jet-faking-photon rate Dijet background: Photon + jet background:

  10. Jet-to-photon fake rate • Derived from a control sample • Loose photon selection: • HadronicOverEm < 0.6 • 5 < Track isolation < 20 • Ecal isolation/photon pT < 0.5 • Hcal isolation/photon pT < 0.5 • Fake rate can depend on jet flavor. The ecal and hcal isolation ratio cuts can minimize the difference.

  11. Prompt photon subtraction: conversion Prompt photon • Need to subtract prompt photon from fake photon data  avoid to overestimate the fake rate • Use photon conversion by looking at the ratio between sum pT of two conversion tracks and total energy of supercluster. • Define control sample to extract the template and conversion probability  normalize template to data and divide by conversion probability to get the number of fake photons

  12. Prompt photon subtraction: shower shape Yong Yang (Caltech) Yong Yang (Caltech)

  13. Electron faking photon rate • Use Zee sample, di-em object (ee, e-gamma, gamma-gamma) invariant mass is reconstructed. • Electrons have a pixel seed while photons don’t • Fit region under the Z peak with a Breit-Wigner on top of quadratic background to find the number of di-em objects e  gamma fake rate

  14. Drell-Yan contribution • Check that fake rate is reasonably flat over pT and eta (In plots, 1 – fake rate is shown). • Apply fake rate to Drell-Yan (e+e-) events

  15. SM diphoton background • Model SM diphoton background using Sherpa or Pythia • Normalize at invariant mass range [200, 600] GeV • Small signal contamination but other background is non-negligible need to subtract or tighten the selections • K-factor is accounted but there is uncertainty contribution due to K-factor dependence on invariant mass

  16. Born diphoton: Sherpa, Pythia • Born diagram is dominant • Good agreement between two generators

  17. Background and signal at 100pb-1 (10 TeV) • We need to make this plot as soon as possible for early data

  18. Conclusions • The analysis is in good shape: tools and techniques are thoroughly studied using MC data. • As soon as we understand the photon objects, we can move fast to get the efficiency and fake rate. • Need to define the triggers and data set used for analysis but we plan to use exotica group skim.

  19. Backup slides

  20. 95% CL calculation • Find number of background, n, passing acceptance cuts by correcting number of observed background for photonID efficiency  measurement independent limit. • Use Bayesian approach • Poisson likelihood • Use flat prior for signal cross section • Incorporate systematic uncertainty on B, A, L by convoluting Poisson likelihood with Gaussian function • Integrate over nuisance parameters to get likelihood L(n|S). Solve this to get 95% CL cross section limit, • Sum of individual limits weighted with Poisson probability of observing n events

  21. 95% CL limit setting • Translate 95% CL cross section limit to 95% CL limit on effective Planck scale, Ms • Parameterize cross section as function of • Find cross section after acceptance cut • Subtract SM cross section • When nED > 2: • Use HLZ convention and translate limit on nG to limit on MS • When nED = 2: • Cross section is a function of • Calculate MS limit directly • 95% CL cross section limit can be used to set limit for any models in diphoton channel.

  22. 95% CL MS limit CMS Preliminary • Current best 95% CL limit on MS: • LEP: 1.1-1.2 TeV (depend on interface sign). • D0: 1-2 TeV (depend on nED) [Phys. Rev. Lett. 102 (2009) 051601]

  23. Discovery potential • What is the luminosity needed for • 3σ (evidence) • 5σ (observation or discovery) ? • Calculate the Poisson probability for background to fluctuate to or above the number of observed events, nobs • Convert that probability to one-side Gaussian significance and express this as number of sigmas • Further require nobs 3 for evidence and nobs 5 for observation.

  24. Discovery potential (cont.) • At ~100 pb-1, we can observe MS = 2.5 TeV, nED = 4 at 5 standard deviation level CMS Preliminary

  25. SM diphoton background from box diagram

  26. Pixel seed veto efficiency Single photon Diphoton

  27. Drell-Yan cross check

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