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New Particle Searches at the LHC SUSY - Inclusive search - Backgrounds - SUSY parameters Resonances in the Drell-Yan mass distribution Heavy long-lived.

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Presentation on theme: "New Particle Searches at the LHC SUSY - Inclusive search - Backgrounds - SUSY parameters Resonances in the Drell-Yan mass distribution Heavy long-lived."— Presentation transcript:

1 New Particle Searches at the LHC SUSY - Inclusive search - Backgrounds - SUSY parameters Resonances in the Drell-Yan mass distribution Heavy long-lived particles Universal Extra Dimensions Black holes

2 R. Ströhmer RAL-PPD Seminar First challenge: get the LHC operational Still on course for engineering run fall 2007: system commissioning single beam operations at 450 GeV collisions at 450 x 450 GeV, no ramp, no squeeze low luminosity: ATLAS/CMS commissioning First collisions at 14 TeV: June 2008 ? after system and beam commissioning 26 weeks of proton-proton physics run in 2008 phase 1: 43 bunches, L ~ 5 x phase 2: 75 ns, L ~2.5 x x phase 3: 25 ns, L ~4 x x cm -2 s -1 Integrated luminosity end of 2008: fb -1 ? (e.g.: 1 fb -1 = 120 effective cm -2 s -1 )

3 R. Ströhmer RAL-PPD Seminar And the experiments too: huge challenge Getting the subdetectors built, tested and installed. Power and signal cables, detector control and monitoring Cooling pipes, cryogenic installations, magnets… CMS: lowered central part (YB0) February 28 th, rest soon will run in 2007 without ECAL endcap and pixels rest going well ATLAS: on a tight schedule to run almost complete in 2007 No TRT at high ||, some muon chambers missing Both will have reduced trigger/DAQ capabilities initially

4 R. Ströhmer RAL-PPD Seminar Getting the data flowing… First individual detectors, then combined Commissioning the DAQ system with cosmics Single beam in LHC: beam halo Use: debug cabling errors initial alignment first intercalibration: uniformity to few % Data processing: Grid, Tier-1, Tier-2 etc Challenge: get processing of HUGE quantities of data going Data Challenges, Calibration Challenges, Computing System Commissioning (ATLAS 2007) ATLAS: CSC exercise should lead to notes CMS: published physics TDR in summer 06 5

5 R. Ströhmer RAL-PPD Seminar Particle Searches in a Nutshell Look for excess of events over Standard Model expectation -Multiple or high pt leptons, jets and missing transverse energy If excess is observed: Is the instrumental background understood? Is the expected SM background understood? Which models predict the excess? -How can we distinguish between models and measure model parameters? If no excess is observed: What is the signal efficiency: reconstruction and trigger efficiencies exclude models or parameter regions for models

6 R. Ströhmer RAL-PPD Seminar Calorimeter noise has to be understood Run II V. Shary CALOR04 E T miss spectrum contaminated by cosmics, beam-halo, machine/detector problems, etc.

7 R. Ströhmer RAL-PPD Seminar Material in front of calorimeter Affects electrons and photons: energy loss, conversions

8 R. Ströhmer RAL-PPD Seminar Getting efficiency from data Use Z µµ to study muons select one muon with tight requirements both muons from Z dont require quantity you want to test from second muon -tracking efficiency -muon chamber efficiency -trigger efficiency

9 R. Ströhmer RAL-PPD Seminar Top events as test sample If one sees the expected distribution and rate on can have confidence in the object reconstructions Isolated lepton p T > 20 GeV E T miss > 20 GeV 4 jets p T > 40 GeV NO b-tag !! 2 jets M(jj) ~ M(W) 3 jets with largest p T 100 pb -1 Bg: W+jets

10 R. Ströhmer RAL-PPD Seminar SUSY Searches Many SUSY searches are performed in the framework of mSUGRA Aim of SUSY searches Find SUSY (or something new) Measure quantities (e.g. mass differences) Prove that it is SUSY Determine model parameters WMAP: 0.094<Ω χ h 2 <0.129 Excluded by b- > s (CLEO,BELLE) Favored by g μ 2 at the 2σ level Muon g2 coll. Stau=LSP J. Ellis et al., Phys. B565 (2003) 176.

11 R. Ströhmer RAL-PPD Seminar Inclusive SUSY Search (Jets + missing Et) Calculate effective mass from jet pt and missing transverse energy Background estimates increased by Matrix Element Monte Carlo w.r.t. showering MC prediction Main backgrounds -Z(νν) + Jets -W + Jets -ttbar Backgrounds have to be estimated or checked with data

12 R. Ströhmer RAL-PPD Seminar Backgrounds from Data Replace observed µ by ν Z->µµ -clean sample -correct shape -small statistics W->µν -large statistics -problem: needs clean W+6jet sample Measure in Z -> μμ Use in Z -> νν

13 R. Ströhmer RAL-PPD Seminar Background Normalization from Data Systematic uncertainties due to: Renormalization scale, factorization scale, PDF mostly effect normalization and not shape. Same normalization for Z-> νν, Z->µµ, W-> ν µ Determine normalization from Z->µµ and apply to Z-> νν, W-> ν µ Test with pseudo data using different MC parameters Z 230 +/- 15 (pseudo-data) 200 +/- 23 (estimation) 190 +/- 14 (pseudo-data) 185 +/- 21 (estimation) W l Effective Mass Missing E T Leading Jet P T ATLAS preliminary ATLAS preliminary ATLAS preliminary ATLAS preliminary ATLAS preliminary ATLAS preliminary

14 R. Ströhmer RAL-PPD Seminar QCD Background Significant part with real missing Et from b- and c- decays Estimate effect of mismeasured jet energy with fast Monte Carlo -get transfer function from full detector simulation -get transfer function from data where missing Et points in jet direction MET jets Select events with: EtMiss > 100 GeV, dPhi(EtMiss, jet) < 0.1 Et(estimated)/Et(measured) ATLAS preliminary

15 R. Ströhmer RAL-PPD Seminar Inclusive SUSY Search (Jets+1lepton+missing Et) Strong reduction of background due to lepton requirement Main background is ttbar -important contribution from bl νblν with one missing lepton for M T >100 GeV

16 R. Ströhmer RAL-PPD Seminar Background from Data Find second quantity not correlated to missing Et General ideas: SUSY signal plus bg A BC D Missing ET other variable bg Bg in D = A x C/B normalize to data For ttbar-> bqqbl ν the top mass can be used as second quantity Contribution from ttbar-> bl νblν is under study

17 R. Ströhmer RAL-PPD Seminar Expected significance The statistical significances have been studied including background uncertainties with the likelihood ratio method

18 R. Ströhmer RAL-PPD Seminar Determination of SUSY Parameters Example: Coannihilation point Two edges in lepton- pair-mass Estimate background from eµ events 20.6 fb -1 MC Truth, l R MC Truth, l L MC Reconstructed ATLAS Preliminary Full sim , ~~ GeV

19 R. Ströhmer RAL-PPD Seminar Spin Measurement First emitted lepton (near) 01/20 More quarks than antiquarks (pp collisions) Remaining asymmetry: LHCC5: m 0 =100 GeV m 1/2 =300 GeV A 0 =-300 GeV tan(β) =2.1 sign(μ)=+ M(ql far ) quark antiquark ql - ql + ql - ql + M(ql near ) antiquark quark No spin correlations, no asymmetry After selection Parton level x 0.6 L=500 fb -1 ATLAS Fast Simulation ql + L=500 fb -1 SPS1a Non-zero M(ql) asymmetry may be observed with 30fb-1 ql - A. J. Barr Phys.Lett.B596: ,2004 Spin:

20 R. Ströhmer RAL-PPD Seminar RS Gravitons & Heavy Bosons pp θ graviton e e Characterisation Measure spin -G * Spin 2 -Z Spin 1 5 sigma discovery ATLAS preliminary

21 R. Ströhmer RAL-PPD Seminar Effect of initial alignment generator initial alignment CMS 1 TeV Z Track-based alignment using minimum bias, Z ee, initial alignment after few fb -1

22 R. Ströhmer RAL-PPD Seminar Search for Heavy Stable Particles Predicted in various models Long lived stau as next to lightest particle in GMSB R-hadrons in Split-SUSY -Colored SUSY particle hadronizes (e.g. gluino) Determination of mass from momentum and velocity (β) β can be determined in the range from 0.6 – 0.8 by: -Energy loss in the tracker -Time of flight in the muon system CMS preliminary

23 R. Ströhmer RAL-PPD Seminar Search for Heavy Stable Particles R–hadrons have hadronic interaction Energy/momentum mostly carried by SUSY particle Hadronic interactions will change the charge of the R-hadron ATLAS preliminary

24 R. Ströhmer RAL-PPD Seminar Search for Heavy Stable Particles Event selection β(dE/dx) < to exclude MIPs 0.6 < β(dE/dx) < < β(TOF) < 0.8 m(dE/dx) > 30 GeV -to reject slow standard model particles number of tracker hits > 10 -to eliminate fake tracks and optimize the quality of dE/dx pt cut at: -150 GeV (300 GeV gluino) -200 GeV (600 GeV gluino) -80 GeV (152.3 GeV stau) expect< 25 BG events at L= 500 pb -1 -(zero unweighted MC events) Combined β resolution for stau CMS preliminary gluino 300 GeV gluino 600 GeV stau GeV 500 pb pb -1

25 R. Ströhmer RAL-PPD Seminar Search for Long-Lived Neutralinos Event selection Isolated photon pt>80 GeV 4 Jets pt> 50 GeV missing energy > 160 GeV -not in Jet direction (Δφ>20 o ) Lifetime reconstruction photons from neutralino with finite lifetime are not pointing to primary vertex. shape of energy deposition in calorimeter depends on photon direction. sensitivity to log(c ) CMS preliminary CMS preliminary

26 R. Ströhmer RAL-PPD Seminar Universal Extra Dimensions (UED) mass - degenerate spectrum Conservation of KK parity (-1) n -n=1 similar to SUSY but Spin(KK) = Spin(SM) 2 nd excitation can be singly produced Pair production of g 1 g 1,q 1 g 1 and q 1 q 1 Signal: 4 leptons (2 pairs OSSF), jets, and missing energy Long decay chains

27 R. Ströhmer RAL-PPD Seminar Z veto: one OSSF with M 80 GeV Universal Extra Dimensions (UED) µ: pt> 5 GeV, |η|<2.4 e: pt> 7 GeV, |η|<2.5 CMS preliminary CMS preliminary

28 R. Ströhmer RAL-PPD Seminar Spectacular States : Micro Black Holes Large EDs Micro black hole decaying via Hawking radiation -Photons + Jets + … We will certainly know something funny is happening -Large multiplicities -Large ET -Large missing ET -Highly spherical compared to BGs Theory uncertainty limits interpretation -Geometrical information difficult to disentangle CMS preliminary Invariant mass [GeV/c 2 ] sphericity

29 R. Ströhmer RAL-PPD Seminar Conclusions ATLAS & CMS have significant discovery potential for physics beyond the standard model New physics could already show up in early data In order to claim a discovery on needs to understand the background -detector performance -standard model processes discovery of something is only first step, the second is to distinguish between models and determine parameters

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