Using Object Correlations to Extract New Physics from the LHC

1. Using Object Correlations to Extract New Physics from the LHC Rouven Essig, Michael Graesser, Eva Halkiadakis, Dmitry Hits, Amit Lath, Pablo Mosteiro, Keith Rose, Steve Schnetzer, Jessie Shelton, Sunil Somalwar, Scott Thomas Rutgers HEX + HET

2. (Reconstructed) Objects Leptons Photons Missing Transverse Energy Jets Exotic Objects (New Long Lived Particles) Displaced - Leptons, Photons, Jets Highly Ionizing Tracks Highly Ionizing to Minimum Ionizing Kinks Highly Ionizing Stopped Track Out of Time Decays Charge Exchange Tracks Charge Changing Tracks .....

3. (Reconstructed) Objects Leptons Photons Missing Transverse Energy Jets New PhysicsSearches – Hadron Collider Strong Production Cross Section . Electroweak Decays . Background / Signal Suppressed (pp  QQ) / (pp  Jets) Q  Leptons, Photons, MET

4. (Reconstructed) Objects Leptons Photons Missing Transverse Energy Jets New Physics Searches – Hadron Collider Strong Production Cross Section . Decay to Strong States . Background / Signal Severe (pp  QQ) / (pp  Jets) Q  Jets New Physics Search in Multi-jets : • Challenging - .... • But Possible - New Physics May be Hidden in Jets … (c.f. Higgs at LEP) • Techniques may be Useful for Multi-jets in Association . with Leptons, Photons, MET

5. New Physics Searches in Multi-Jets • Magnitude of Multi-Jet Backgrounds from High Order Processes . Difficult to Calculate a priori sn • High Multiplicity-Jet Backgrounds, Lower Rate - More Tractable • Kinematic Features + Correlations pp  QQ Q = SU(3)C Adjoint Majorana Fermion  j j j Kinematic Features + Correlations + Hadronic Top Guidance . (No b-tagging or mW resonance )  j j j • Hiding New Physics in Multi-Jets • SUSY gluino  j j j Signal : Pythia 6 Jet Background : ALPGEN  Pythia Hadronic Top Background : Pythia Detector Simulator : PGS Analysis : ChRoot + R-Parity Violation uud Yukawa

6. Semi-Leptonic Top Decays pp  tt  l  j j j j pp  W j j j j 150 pb-1 Njet¸ 4 Ne = 1 pT,4th jet¸ 40 GeV PT,e¸ 20 GeV | mjjj – mW | · 10 GeV j j j Furthest R from Electron GeV 150 pb-1 PT,5th jet· 10 GeV mjjj GeV

7. pp  QQ  j j j j j j Njet¸ 6 mQ = 420 GeV Signal Hadronic Background 2 fb-1 0.015 fb-1 PT,6th jet PT,6th jet Gluino300-Effjet6Effjet Alp6j50-Effjet6Effjet PT, jets PT, jets

8. pp  QQ  j j j j j j Cut : pT, jets¸ 700 GeV pT, 6th jet¸ 60 GeV Njet¸ 6 mQ = 420 GeV Signal Hadronic Background 2 fb-1 0.015 fb-1 Cut Cut PT,6th jet PT,6th jet Gluino300-Effjet6Effjet Alp6j50-Effjet6Effjet PT, jets PT, jets Signal Efficiency ' 0.25

9. pp  QQ  j j j j j j Two Three-Body Resonances mjjj = mjjj Choose Pair of Jet triplets with Smallest| mjjj – mjjj | · 60 GeV | i=16 pT,i,jet | · 60 GeV Signal Hadronic Background 2 fb-1 0.015 fb-1 mjjj mjjj • Cuts Necessarily Shape Background • Magnitude of Background Uncertain - . Use Signal + Background Distributions as Templates

10. pp  QQ  j j j j j j Scaled Cuts pT, jets¸ 1.7 mQ . pT, 6th jet· 0.15 mQ . | i=16 pT,i,jet | · 0.15 mQ | mjjj – mjjj | · 0.15 mQ MQ (GeV) S/BS/ B1/2 / fb-1Signal Events / fb-1 420 1/29 17 9000 660 1/22 5 600 890 1/17 2 70 Note: Magnitude of Background Uncertain

11. pp  QQ  j j j j j j Choose Pair of Jet triplets with Smallest | mjjj – mjjj | · 60 GeV | i=16 pT,i,jet | · 60 GeV Signal Hadronic Background mjjj mjjj Improve Contrast Between Signal and Background Tail much larger than Jet Resolution - . Mismatching of Jet Triplets - . Combinatoric Background Within Signal

12. pp  QQ  j j j j j j Reduce Combinatoric Background from Radiated Jets with Cut on 7th Jet MQ = 290 GeV pT,jets¸ 500 GeV pT, 6th jet¸ 30 GeV pT, 7th jet· 20 GeV | i=16pT,jeti | · 50 GeV • Improves Contrast AND . S/B by Factor 2 Hadronic Background Signal 0.3 fb-1 0.09 pb-1 mjjj mjjj MQ (GeV) S/BS/ B1/2 / fb-1Signal Events / fb-1 290 1/110 15 26850

13. pp  QQ  j j j j j j Kinematic Correlation – Separate Signal from Combinatoric Background mQ = 420 GeV Signal Signal mjjj mjjj pT,jets | i=13 pT,jeti | • Two Distributions of Events • Three Body Resonance Jet Resolution Apparent on Horizontal Branch • Most of the “Best” Pairs of Jet Triplets with small |mjjj-mjjj| . are NOT the Correct Pairing (Random Choice of Triplet » Same Distribution)

14. pp  QQ  j j j j j j Remove Combinatoric Background with Cuts Signal Signal mjjj mjjj pT,jets | i=13 pT,jeti | • Horizontal Branch - Region of High Signal to Combinatoric . Background Contrast • - Increase Signal Efficiency by Including All 20 Jet Triplets • - Remove | mjjj – mjjj | Cut ( | i=16 pT,jeti | Cut )

15. pp  QQ  j j j j j j Cuts Hadronic Top Background Hadronic Top Background mjjj mjjj Hadronic Background Hadronic Background Increase Signal Efficiency mjjj mjjj PT,jets | i=13 pT,jeti |

16. pp  QQ  j j j j j j Signal Hadronic Background 2 fb-1 0.015 fb-1 mjjj Hadronic Top Background 0.3 fb-1 mjjj

17. pp  QQ  j j j j j j Signal Hadronic Background 2 fb-1 0.015 fb-1 mjjj • Improves Constrast and S/B by 2.5 but Lowers Signal Efficiency by 2.8 MQ (GeV) S/BS/ B1/2 / fb-1Signal Jet Triplets / fb-1 490 1/15 17 4700

18. pp  QQ  j j j j j j Using Correlations – Possible to Separate pp  QQ  j j j j j j from Background Optimize Cuts Study Template Fitting to Signal + Background Validate Background Templates and Magnitude with Data Possible Reach (Preliminary) mQ» 600 GeV with 1 fb-1 » 800 GeV with 10 fb-1 Develop Kinematic Correlations for Other Multi-Jet Signatures Extend to Signatures with Other Objects - Correlation Templates

19. Kinematic Correlations Decay Trees Invariant Kinematic Correlations = f( mijk…2) (Unpolarized, . Spins Unobserved, . T-Invariance ) mijk…2 = f(mij2) Correlations in Generalized Dalitz Space mij2 i,j = All Pairs of Objects

20. Invariant Kinematic Correlations • New Physics Sample . Nl = 2-6 . Njet¸ 2 . Backgrounds Unimportant • Enhanced S/BCombinatoric Constrast • DS < DB (D=1 Histrogram DS = DB) • Two Body Resonant Tree • Correlation m122 + m132 = Constant • (Some of) The Two Body Resonances . Arise from Three Body Decay Nl¸ 3 6 fb-1 m13 m12

21. Invariant Kinematic Correlations • Uniform |M|2 on Two Body Resonances • Consistent with Intermediate Scalar • Edges • Three Body Tree (Only feature in . D=1 Histogram) • Coincide with Endpoint of Resonant . Two Body Correlation • - Arise from “Missing” Lepton • - Anything Else Contributing to . Edge is massless • Relative Density of Two Body Resonances, . Resonant Two Body Correlation, and . Edge Contrast • - Br ( lll) / Br(  llX) Dalitz (symmetrized) 2 m132 2 m122

22. Invariant Kinematic Correlations • Three Body Resonant Trees • 310 GeV · mlll· 330 GeV • Further Enhances . S/BCombinatoric Contrast m123 m132 m122

23. Kinematic Correlations Nl¸ 4 • No Kinematic Correlation • - Consistent with Arising from . Different Parent Particle • m14 = m and m23 m or • m14 m and m23 = m • - Single Resonant Two Body Decay • m14 = m23 = m • - If Density at Intersection \geq 2 . Some Events with (At least) . Two Resonant Two Body Decays • - Density at Intersection gives Fraction m14 m23

24. Invariant Kinematic Correlations Nj¸ 2 • Contrast S/BCombinatoric Improved • Two Four Body Resonant Decays • Density in Bands and Intersections Give • Br( 1 jlll) /  Br( 2  jlll) • Correlation Could Indicate Resonant . Five Body Decay   jjlll Mjlll Mjlll 30 fb-1 Mjlll

25. Object Correlations to Extract Low Order Trees (OCELOT) Kinematic Correlations Can Enhance Contrast DS < DB Menu of Correlations for Low Order Trees - Develop Templates to Search for Correlations Extend to Trees with MET (Generalization to D > 1 of Edges and Endpoints) Correlations Allow Direct Measurements Implement Correlations in Fitting Procedure to Decay Trees . (Fitting to D=1 Counts Misses Many Correlations)

26. New Physics at the LHC Resonant Multi-Jets ….. Resonant Multi-Leptons Very HardVery Easy