1. 1 UPDATE: 1. Selection reorganized : Triggered, 2Zs, 2Leading Jets 2. Issue of W mass reconstructed For signal, show the efficiency of matching btw leading jets and partons A look at pure W sample, WZ  jj+nu+nu 4. More background included, ttbar, zbb, wz, etc 5. JJZZ, JZZ, ZZ issues 3. Scatter plot of Mwz1 vs Mwz2

2. 2 Search New Gauge Boson W 1 ± in the Minimal Higgless Model at LHC Jian-Guo Bian, Ming-Shui Chen

3. 3 Introduction New gauge bosons (W 1 ±, Z 1 ) are predicted in the Minimal Higgsless Model Signature of W 1 ± in the processes pp  W ± Z 0 qq’  v3lqq’ and pp  W ± Z 0 Z 0  qq’4l was investigated at the parton level [1] We study the W 1 ± via pp  W 1 ± Z 0  W ± Z 0 Z 0  qq’4l using fully hadronized events both for signal and backgrounds [1]: Phys. Rev. D78(2008) 031701(R), Zhang Bin, Kuang Yuping, et al.

4. 4 Signal production Generator for signal was developed by the authors of Ref.[1] It is interfaced with PYTHIA to perform initial and final radiation, parton showers and hadronization Pre-seletion at parton level: –partons : p T q > 15GeV, |  q |<4.5 –leptons : p T l > 10GeV, |  l |<2.5 First study the W 1 ± with mass = 500 GeV Cross sections after pre-selection are 0.267fb and 0.109fb for W 1 + and W 1 - respectively Generate 2000 events totally

5. 5 Background production The signal process that we study gives rise to a clean signature of 4-leptons and 2-jets A) The irreducible background is SM pp  W ± Z 0 Z 0  qq’4l B) The reducible SM pp  Z 0 Z 0 Z 0  qq’4l with one Z 0 decaying into two jets and mis-identified as W C) The SM pp  qq’Z 0 Z 0  qq’4l, pp  qZZ  q4l and pp  ZZ  4l, other than A) and B) A), B) and C) are simulated using the Madgraph package which also is interfaced with PYTHIA D) Other SM processes including 4 leptons in the final state are produced by PYTHIA

6. 6 ProcessXsec (fb)EventsNorm. factor Signal (500GeV)0.3762.0E30.0188 SM W ± Z 0 Z 0  jj4l 0.141.0E40.0014 SM Z 0 Z 0 Z 0 10.02.0E50.005 SM qq’Z 0 Z 0  jj4l 12.81.0E50.0128 ZZ  j4l ZZ  4l 23.4 46.5 1.5E5 1.0E5 0.0156 0.046 ttbar  2l2v2b230008.0E70.029 Zbb  2lbb WZ  3lv (pythia)ZZ  4l 3.2E5 389 70 4.0E8 1.5E6 7.0E5 0.08 0.026 0.01 Or we may Utilize zz events produced by pythia, not from MadGraph, it will include zz, zzj, zzjj, zzjjj, etc

7. 7 Event selection Pass HLT, 2e 15GeV or 2mu 10GeV 4 leptons(2e + 2e -, e + e - mu + mu -, 2mu + 2mu - ) –leptons : p T l > 10GeV, |  l |<2.5 Z mass requirement –|M ll -91|<15GeV 2 leading jets (algorithm provided by PYTHIA) –jets : p T j > 15GeV, |  j | 0.3

8. 8 Delta R btw partons Delta R btw leading jets and partons (<=0.3) 2328  1453 Delta R btw best jets and partons (<=0.3) 2328  1258

9. 9

10. 10 Debugging W mass Sample: 30K events pp  WZ, W  2j, Z  2nu Blue is from two leading jets Black is the best combination with mass closest to 80 Tried two Jet reconstruction algorithms, cone0.7 and KT, results are similar Requiring inside the mass window, (65~95), for blue line, it’s reduced from 24271 to 14706

11. 11 Cuts hunting

12. 12 Cuts hunting (cont.)

13. 13 Cuts flow

14. 14 Final distribution

15. 15 1. 对于 100/fb 情况, 事例数太少 2.Cut 之后只剩 10 个实例不到, 能否应用 Dalitz 分析显著性 ? 3.May we use the same technique to calculate the significance as Ref did

16. 16 Issues jjzz, jzz and zz Jet reconstruction  poor W mass resolution Calculation of significance –In conversional way ? S=Ns/sqrt(Nb)

17. 17 To-do More mass points will be included Look for more powerful cuts to optimize Estimate systematic uncertainties