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New Particle Searches at the LHC

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Presentation on theme: "New Particle Searches at the LHC"— 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 9.5.07
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 1030 phase 2: 75 ns, L ~2.5 x  1 x 1032 phase 3: 25 ns, L ~4 x  1 x 1033 cm-2s-1 Integrated luminosity end of 2008: fb-1 ? (e.g.: 1 fb-1 = 120 effective 1032 cm-2s-1) R. Ströhmer RAL-PPD Seminar

3 R. Ströhmer RAL-PPD Seminar 9.5.07
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 28th , 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 R. Ströhmer RAL-PPD Seminar

4 R. Ströhmer RAL-PPD Seminar 9.5.07
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 R. Ströhmer RAL-PPD Seminar

5 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 R. Ströhmer RAL-PPD Seminar

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

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

8 Getting efficiency from data
Use Zµµ to study muons select one muon with tight requirements both muons from Z don’t require quantity you want to test from second muon tracking efficiency muon chamber efficiency trigger efficiency R. Ströhmer RAL-PPD Seminar

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

10 R. Ströhmer RAL-PPD Seminar 9.5.07
SUSY Searches Many SUSY searches are performed in the framework of mSUGRA WMAP: 0.094<Ωχh2<0.129 Excluded by b- > s (CLEO,BELLE) Favored by gμ−2 at the 2σ level Muon g−2 coll. Stau=LSP J. Ellis et al., Phys. B565 (2003) 176. Aim of SUSY searches Find SUSY (or something new) Measure quantities (e.g. mass differences) Prove that it is SUSY Determine model parameters R. Ströhmer RAL-PPD Seminar

11 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 R. Ströhmer RAL-PPD Seminar

12 R. Ströhmer RAL-PPD Seminar 9.5.07
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 m n Measure in Z -> μμ Use in Z -> νν R. Ströhmer RAL-PPD Seminar

13 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->νµ Determine normalization from Z->µµ and apply to Z->νν, W->νµ Effective Mass Missing ET Leading Jet PT ATLAS preliminary Test with “pseudo data” using different MC parameters Z -> nn 230 +/- 15 (pseudo-data) /- 23 (estimation) W -> ln 190 +/- 14 (pseudo-data) /- 21 (estimation) R. Ströhmer RAL-PPD Seminar

14 R. Ströhmer RAL-PPD Seminar 9.5.07
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 Select events with: EtMiss > 100 GeV, dPhi(EtMiss, jet) < 0.1 ATLAS preliminary MET jets Et(estimated)/Et(measured) R. Ströhmer RAL-PPD Seminar

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

16 R. Ströhmer RAL-PPD Seminar 9.5.07
Background from Data Find second quantity not correlated to missing Et General ideas: other variable SUSY signal plus bg bg D A bg B C bg Missing ET Bg in D = A x C/B normalize to data For ttbar-> bqqblν the top mass can be used as second quantity Contribution from ttbar->blνblν is under study R. Ströhmer RAL-PPD Seminar

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

18 Determination of SUSY Parameters
264 154 , 255 137 ~ Example: Coannihilation point Two edges in lepton-pair-mass Estimate background from eµ events GeV 20.6 fb-1 MC Truth, lR MC Truth, lL MC Reconstructed ATLAS Preliminary Full sim. R. Ströhmer RAL-PPD Seminar

19 R. Ströhmer RAL-PPD Seminar 9.5.07
Spin Measurement First emitted lepton (“near”) Spin: 1/2 LHCC5: m0 =100 GeV m1/2 =300 GeV A0 =-300 GeV tan(β) =2.1 sign(μ)=+ M(qlnear) M(qlfar) quark ql- quark ql+ ql- ql+ antiquark antiquark ATLAS Fast Simulation A. J. Barr Phys.Lett.B596: ,2004 More quarks than antiquarks (pp collisions) Remaining asymmetry: L=500 fb-1 L=500 fb-1 After selection Parton level x 0.6 ql- SPS1a Non-zero M(ql) asymmetry may be observed with 30fb-1 ql+ No spin correlations, no asymmetry R. Ströhmer RAL-PPD Seminar

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

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

22 Search for Heavy Stable Particles
CMS preliminary 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 R. Ströhmer RAL-PPD Seminar

23 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 R. Ströhmer RAL-PPD Seminar

24 Search for Heavy Stable Particles
Combined β resolution for stau gluino 300 GeV Event selection β(dE/dx) < 0.85 to exclude MIPs 0.6 < β(dE/dx) < 0.8 0.6 < 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) 30 pb-1 CMS preliminary gluino 600 GeV stau 152.3 GeV 500 pb-1 500 pb-1 R. Ströhmer RAL-PPD Seminar

25 Search for Long-Lived Neutralinos
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) Event selection Isolated photon pt>80 GeV 4 Jets pt> 50 GeV missing energy > 160 GeV not in Jet direction (Δφ>20o) CMS preliminary CMS preliminary R. Ströhmer RAL-PPD Seminar

26 Universal Extra Dimensions (UED)
mass degenerate spectrum Conservation of KK parity (-1)n n=1 similar to SUSY but Spin(KK) = Spin(SM) 2nd excitation can be singly produced Long decay chains Pair production of g1 g1 ,q1 g1 and q1 q1 Signal: 4 leptons (2 pairs OSSF), jets, and missing energy R. Ströhmer RAL-PPD Seminar

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

28 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/c2] sphericity R. Ströhmer RAL-PPD Seminar

29 R. Ströhmer RAL-PPD Seminar 9.5.07
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 R. Ströhmer RAL-PPD Seminar

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