Preparation for Supersymmetry Searches at CMS: Jets and Missing Energy

1. Preparation for Supersymmetry Searches at CMS: Jets and Missing Energy Edmund Widl, Robert Schöfbeck 60. Jahrestagung der ÖPG

2. References • Martin, S., “A Supersymmetry Primer”, arXiv:hep-ph/9709356v5 • CMS Collaboration, “The CMS Experiment at the CERN LHC”, JINST 3, S08004 (2008) • CMS Collaboration, “CMS Jet Performance in pp Collisions at √s = 7 TeV”, CMS Physics Analysis Summary, CMS PAS JME-10-003 • CMS Collaboration, “CMS MET Performance in Jet Events from pp Collisions at √s = 7 TeV”, CMS Physics Analysis Summary, CMS PAS JME-10-004 • CMS Collaboration, “Performance of Methods for Data-Driven Background Estimation for SUSY Searches in the CMS Experiment”, CMS Physics Analysis Summary, CMS PAS SUS-10-001 Edmund Widl (HEPHY Vienna)

3. Why jets and missing energy? • The theoretical framework of supersym-metry allows for a very, very large amount of contrasting phenomenological features: • different mass spectra with distinct decay channels • different cross sections and branching ratios • even different conservation laws • What is expected by the LHC experiments: • strong production of gluinos and squarks • dominant SUSY processes in pp-collisions • source of high-pT jets • decay chains ending with a stable, unchar-ged sparticle (neutralino) • dark matter candidate for cosmology • source of high excess of missing energy Example: mass spectra for three different SUSY scenarios Edmund Widl (HEPHY Vienna)

4. Edmund Widl (HEPHY Vienna)

5. Commissioning of CMS • QCD backgrounds are expected to be orders of magnitude larger than any SUSY signal • Experimental requirements • a good understanding of complex physics observables • control over backgrounds from standard model processes • Careful commissioning is the key to success (since end of May) • performance of the reconstruction of jets and missing transverse energy (MET) • validation of methods for background suppression and data-driven estimation • study QCD backgrounds • validate predictions of background distributions • comparison with predictions from simulation • The first proton-proton collision data at a center-of-mass energy of 7 TeV recorded by CMS has been used to do exactly that • first collisions at 7 TeV on March 30th • high efficieny data-taking (>90%) since the end of April Edmund Widl (HEPHY Vienna)

6. Performance of jet reconstruction (1) • Signature for the production of colored particles • in SUSY: production of squarks and gluinos hadronizing to high-pT jets • The instrumentation of CMS allows to reconstruct jets in various ways • Two examples: • calorimeter jets • uses only information about energy deposits from calorimeters • particle-flow jets (PF) • aims to reconstruct, identify and calibrate each single particle by combining all sub-systems • individual particles are the "bundled" to define jets Edmund Widl (HEPHY Vienna)

7. Performance of jet reconstruction (2) • Jet energy correction (JEC) done in three steps: • offset correction • due to electronics noise and additional pp-interactions in same bunch crossing (pile-up) • from data: retrieve from zero-bias and minimum-bias data • relative correction • due to non-linear and non-uniform response of calorimeter • from data: use pT balance from back-to-back di-jet events • absolute correction • calibrate absolute jet energy scale • from data: use pT balance from back-to-back g+jet events, exploiting the extremely precise pT measurement of the g from the electromagnetic calorimeter Edmund Widl (HEPHY Vienna)

8. Performance of jet reconstruction (3) • jet resolution for jets with 0.0 ≤ |η| ≤ 1.4 • determined with "di-jet asymmetry method" • asymmetry variable A = (pT, jet1 - pT, jet2) / (pT, jet1+pT, jet2) • for approximately equally values of pT one finds s(pT)/pT = √2 sA Edmund Widl (HEPHY Vienna)

9. Performance of MET reconstruction (1) • Signature for the production of uncharged, weakly interacting, long-lived particles • in SUSY: long-lived neutralinos (WIMPs) causing high excess of MET • CMS has implemented various algorithms to reconstruct missing transverse energy • Two examples: • calorimeter MET (caloMET) • based on calorimeter energies, using the tower geometry of the hadron calorimeter • particle-flow MET (pfMET) • calculated using a complete particle-flow technique Edmund Widl (HEPHY Vienna)

10. Performance of MET reconstruction (2) Performance of MET reconstruction in di-jet events. Edmund Widl (HEPHY Vienna)

11. Performance of MET reconstruction (3) • Removal of anomalous signals in the calorimeters • caused by particles hitting the transducers or rare random discharges • can be characterized by unphysical charge sharing between neighboring channels as well as timing/pulse shape information • Removal of beam-induced backgrounds (beam halo) • veto on parallel-to-beam trajectories reconstructed in the endcaps of the muon system • Corrections due to non-compensating nature of the calorimeter • response of hadronic and electromagnetic component of calorimeter showers differs (hence non-compensating) • energy of hadrons therefore tends to be undermeasured • correction of type I: apply jet energy correction to all jets with electromagnetic energy fraction < 0.9 and corrected pT > 20 GeV • correction of type II: account for the remaining soft jets below threshold and energy deposits not clustered in any jet Edmund Widl (HEPHY Vienna)

12. Performance of MET reconstruction (4) ECAL: electromagnetic calorimeter HE: hadronic calorimeter endcap region HF: hadronic calorimeter very forward region HB: hadronic calorimeter barrel region Edmund Widl (HEPHY Vienna)

13. Performance of MET reconstruction (5) • Resolution for MET • caloMET: calorimetry only • pfMET: particle flow algorithm • tcMET: combined information from calorimetry and tracking • Measured from photon+jet sample • use the very precise photon momentum measurement as reference • The good agreement between data and simulation confirms that the MET reconstruction (including also cleaning proce-dures) works properly! Edmund Widl (HEPHY Vienna)

14. SUSY backgrounds at the LHC • SUSY cross sections are expected to be orders of magnitude smaller than typical QCD cross sections: • backgrounds from QCD processes have to be understood and controlled • the corresponding tails in MET distributions have to be quantified accordingly • Modeling and controlling the high-energy tails of QCD processes is very difficult: • QCD cross sections are not predicted with high enough precision • key topological and kinematic distributions such as the number of jets and their pT spectra are difficult to predict • Strategy pursued by CMS: • determine backgrounds using data-driven methods whenever possible • use multiple methods of cross-checks Edmund Widl (HEPHY Vienna)

15. Example: Suppression of QCD contributions • Kinematic variables HT and aT • characterize the overall transverse momentum balance of the event • in practice, QCD background is largely confined to the region aT<0.5 • suppression improves with increasing HT Edmund Widl (HEPHY Vienna)

16. Background estimation: Templates • The concept of the "template method": • assume that the signal of channel A looks like the background for channel B • retrieve the shape of signal A and normalize it to unity • use this shape as a template for estimating the background of B • Example: • use multi-jet QCD events to model g+jets events with artificial MET • channel g+jets is also a relevant background for SUSY searches Edmund Widl (HEPHY Vienna)

17. Conclusions and outlook • The CMS Collaboration has used the first data from pp-collisions at a center-of-mass energy of 7 TeV to commission the detector. • This commissioning included also the proper processing and handling of complex physics observables likes jets and MET. • The performance of jet and MET reconstruction has come up to the expectations of the collaboration. • This performance also allowed to successfully launch the physics programs, including the search for supersymmetry. • Even though supersymmetry studies will still lack of statistics for some time, studies concerning backgrounds are progressing well. Edmund Widl (HEPHY Vienna)

18. Backup Slides Edmund Widl (HEPHY Vienna)

19. Backup: beam halo event Event display for beam halo event faking significant caloMET (224 GeV). Edmund Widl (HEPHY Vienna)

20. Backup: Another example of background suppression • Kinematic variable Df∗: • defined as the minimum angle bet-ween one jet and the MHT computed using the remaining jets • tests whether there is at least one jet which, if rescaled by a certain factor, would be able to balance the event • peaks around zero for QCD events • distributions of Df*: • red: multi-jet events • black: multi-jet events with on jet removed mimicking SUSY events Edmund Widl (HEPHY Vienna)