Simone Gennai SNS, INFN-Pisa1 Radion searches in CMS A first look to  hh G. Dewhirst, L. Fano, S. Gennai, S. Nikitenko

Simone Gennai SNS, INFN-Pisa2 What is the Radion? branes bulk Gravitons can be exchanged from brane to bulk In the R.S. Model the graviton is the only particle that can “live” in the bulk, all other SM particles are confined in the brane. Describing the 5D graviton field in 3+1D leads to a representation of the type: h  +  (the radion) Coupling to the higgs comes from the metric scalar term in the lagrangian.

Simone Gennai SNS, INFN-Pisa3  Br of radion depends on m , m h,   (scale),  (  -h) mixing

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Simone Gennai SNS, INFN-Pisa7 This final state is common also to other scenarios, like MSSM or little Higgs, in the ED case the cross sections are enanched for some model parameters. (M  =300 GeV, M h =125 GeV) Possible backgrounds: tt, W+jj, Z+jj pp b b  jet l  hh  bb  +l+bb+

Simone Gennai SNS, INFN-Pisa8 Few words about tt bkg tt is the most dangerous Atlas has considered: tt  WWbb  l+ +jj+bb,  xBR=180 pb Probably we should consider also: tt  WW+bb  l+ +  +bb  l+ +  jet +bb,  xBR=18 pb considering the  -tagging efficiency and bkg rejection this channel could also contribute.

Simone Gennai SNS, INFN-Pisa9 Some kinematical distributions (II) E t of  -jet (GeV) (=E t  - E t ) = 55 GeV = 25 GeV

Simone Gennai SNS, INFN-Pisa10 Trigger and basic selections e/  +  -jet trigger will be used At least 3 jets + 1 e/  to be reconstructed  -jet identification (HLT + off line) At least 1 jet b-tagged (off line) E T missing based selection (to suppress W+jj) Invariant mass of bb and  +lepton Invariant mass ot 2 reconstructed Higgs

Simone Gennai SNS, INFN-Pisa11 Invariant mass distributions (I) Invariant Mass of REAL b-jet (no Energy Correction) Invariant Mass of REAL b-jet (with Calorimeter Energy Correction) = 100 GeV = 125 GeV M h = 125 GeV I take the reconstructed jets nearest to the b-quark flight direction in (  ) plane

Simone Gennai SNS, INFN-Pisa12 B and tau matching Efficiency (I) Matching efficiency : # of events with matched jet / # good events Good events = events in which I have reconstructed the electron Eff. 1 st Jet Eff. 2 nd Jet Eff. 1 || B-jet Eff. e comes from tau 53% Matching e with 1 st Tau jet 30% (out of 53%) Eff. tau Jet 65% (everywhere) 48% (first 3 jets) e  -jet (After L1 selection) PRELIMINARY

Simone Gennai SNS, INFN-Pisa13 Where to find Real tau: When electron is collinear to 1 st L1 Tau: 30% Real Tau is the 2 nd Tau jet 38% Real Tau is the 1 st Central jet 20% Real Tau is the 2 nd Central jet 8% Real Tau is the 3 rd Central jet..... Tau Tagging efficiency = 35% limiting to first 3 highest energy jets: Eff. = 30% Tau isolation parameters: P t LT >10 GeV R M =0.1 R SIG =0.07 R ISO =0.4 1.OR.3 Tracks inside Signal cone.

Simone Gennai SNS, INFN-Pisa14 B tagging Efficiency Tagging efficiency : # of events with tagged jet / # matched events Total Efficiency : Eff. Match X Eff. Tagging Btagging = Tk>2,  ip >2 As efficiency for 1st and 2nd Jet are different, we can relax selection but requiring 2 tagged jets instead of at least 1. B-jet Eff. 1 st Jet Eff. 2 nd Jet Eff. 1 || 2 Jet Tot Eff. 1 st Jet Tot Eff. 2 nd Jet Tot Eff. 1 || 2 Jet

Simone Gennai SNS, INFN-Pisa15 Signal invariant mass distributions No big discrepancy between full and fast simulation for the signal! FAST FULL Vs

Simone Gennai SNS, INFN-Pisa16 Signal P T distributions FAST FULL Vs

Simone Gennai SNS, INFN-Pisa17 Preliminary results Ev. tt = 107 Ev. W+jj = 0 Ev. Z+jj = 33 Ev. Bkg = 140 Ev Sig = 43 S/sqrt(B+S) = 3.2 Efficiency parametrization has been performed in order to have  the same number of signal events in both Full and Fast simulation

Simone Gennai SNS, INFN-Pisa Sigma regions Really PRELIMINARY Theoretically excluded 3 sigma 5 sigma CMS, 30 fb -1  hh  bb  hh  bb    GeV  h  GeV    (GeV)

Simone Gennai SNS, INFN-Pisa19 same point: m  = 300 GeV, m h = 125 GeV GenerationSimulationReconstructionevents signal PythiaORCA 6 4500 4b QCD P T >0 (*) 6 3500 4b QCD P T >100 (*) 6 1000 (*) at least one parton in the final state -> hh -> bbbb – First View

Simone Gennai SNS, INFN-Pisa20 Selection Efficiency - Energetic Threshold Eff Jet ET 1 Jet 2 Jet 3 Jet 4 Jet Signal 4b QCD – no cut 4b QCD – PT > 100 GeV 4 Jet ET > 50 GeV : 10% signal 1% QCD (PT>100 GeV)

Simone Gennai SNS, INFN-Pisa21 Selection Efficiency Energetic threshold + btag Eff Jet ET 1 leading Jet 2 leading tagged Jet 3 leading and next-to- leading tagged Jets Signal 4b QCD – no cut 4b QCD – PT > 100 GeV b-tag: 2 tracks with Sip2D>1.5

Simone Gennai SNS, INFN-Pisa22 Signal Kinematics = 4.6 = 2.5 Eta and PT distribution - 4 leading Jets EtaPTPT

Simone Gennai SNS, INFN-Pisa23 Signal Reconstruction M bb  124  39 GeV M bbbb  304  64 GeV Best jets combination is chosen minimizing the difference between all possible reconstructed mass M(i,j) – M(k,l) Jets are preselected in the barrel requiring E T >35 GeV

Simone Gennai SNS, INFN-Pisa24 Cuts and Selection Criteria 1 Jet E T > 177 GeV OR 3 Jets E T > 86 GeV OR 4 Jets E T > 70 GeV Invariant reconstructed mass:  < M bb <   < M bbbb <  AND Signal:   58 pb BR(->hh)  0.33 BR(h->bb)  0.9 Eff  5% 4b QCD (PT>100 GeV): (qq,gg->bbbb)  930 pb Eff  3% 22.5*10 3 events 837*10 3 events 30 fb -1

Simone Gennai SNS, INFN-Pisa25 What is missing? - Considering all QCD background sources - Considering resonant backgroud - Check other trigger strategy (using b-tag)