1. Search for Pair Produced Stops Decaying to a Dileptonic Final State at CMS David Kolchmeyer

2. Overview Introduction SUSY Overview The CMS Experiment The dileptonic stop search - Event Selection Data-driven estimation of background (Tight to Loose method) My Summer Project Potential Obstacles Fun Slide

3. Introduction Me: David Kolchmeyer, Rutgers University (New Brunswick, NJ) My Advisor: Alberto Graziano, Instituto de Física de Cantabria (Santander, Spain) Working in a collaboration with UMD, IFCA, Oviedo, Cantabria, CIEMAT Part of CMS SUSY sub-group I will be involved in offline physics analysis (work will mostly involve programming analysis code)

4. SUSY Overview SUSY posits that each SM particle has a superpartner Fermions paired to bosons, bosons paired to fermions Can solve Hierarchy/naturalness problem – Higgs mass is too low – Stops can cancel top quark loop corrections

5. The CMS Detector Tracker surrounds collision point; charged particles leave tracks Large magnetic field curves particles ECAL absorbs photons/leptons HCAL absorbs hadrons Muon detector detects long lived muons Jets are streams of particles created from individual quarks that emerge from the collision

6. Dileptonic Stop Decay stop top W b lepton neutrino Neutralino We consider the scenario: Hence, we expect: Two opposite sign leptons Two b-tagged jets Missing transverse energy (MET) x 2 since the stop is pair-produced with an antistop Note: Largest background is from ttbar production, which has similar end-products

7. Event Selection Standard muon and electron selection criteria, determined by Physics Object Group (POG) – Includes cuts on PT, eta, impact parameter, isolation Look for pair of opposite charged leptons in a dilepton triggered sample If ee or mumu final state, veto in Z window (76 to 106 GeV) Require m ll > 20 GeV to eliminate low mass resonances At least two jets, at least one b-jet MET > 40 GeV in ee, mumu final states to further eliminate Z background Define signal region for MT2(ll) > 80, control region MT2(ll) < 80 Blinding policy

8. The MT2 variable

9. Data Driven Background Estimation Backgrounds include ttbar, Drell-Yan, W+Jets, tW, WW, ZZ, WZ, … (dominated by ttbar) My focus: estimate Wjets background via data- driven method Lepton from W and fake lepton from jet can contaminate signal region ‘Prompt’ lepton is from W/Z decay (the leptons we care about) ‘Fake’ lepton is from meson decay, actual fake from jet, photon conversion, etc (these contaminate our signal)

10. Tight to Loose Method Define a tight lepton as a lepton candidate satisfying all selection criteria Define a loose lepton as a lepton candidate that satisfies all criteria except for the isolation criteria (instead it satisfies a looser isolation cut) So a lepton can be categorized as tight/prompt, loose/prompt, tight/fake, loose/fake In a sample of fake leptons (i.e. in a QCD dijet sample) calculate the ratio of tight leptons to all leptons  fake rate (f) Require jet that is separated from the lepton (“Away Jet”) to pass minimum energy threshold With the fake rate, go back to the dilepton sample and observe the number of loose leptons to calculate the number of tight leptons We can validate the estimation in a same-sign control region Prompt rate (p) is ratio of tight to all among prompt leptons (measure in Drell-Yan sample using tag and probe), usually is close to 1

11. My Summer Project Find the best definition of a loose electron and muon See how estimated background varies depending on this definition Determine best criteria of QCD sample to measure fake rate – Try different values of “Away jet“ threshold Validate the background prediction – Define control region, plot relevant variables – Compare with MC

12. Potential Obstacles Trying to determine fake rate with samples from different triggers of different luminosities (how to combine trigger luminosities to weight leptons appropriately?) Electroweak contamination in fake rate estimation Possibility of fake rate estimation being overly sensitive to definition of loose lepton Not being able to properly predict backgrounds in control region or MC Technical Difficulties

13. Jam Session sur le Bateau

14. Backup Slides

15. The MT2 variable

16. The MT2 variable (contd) Now consider two cases of W  l v happening at once We only know the sum p T of the two neutrinos So, let us try all the possibilities of dividing up p miss T into the p 1 T and p 2 T of each invisible neutrino, calculate MT twice to get the highest (best) lower bound for that possibility, and take the minimum over all the possibilities to get a lower bound on the W mass The distribution should not cross the W mass (80 GeV)

17. The MT2 variable (contd) Formally, we can now define MT2 = min { max { MT(p 1 T ), MT(p 2 T ) } } for p 1 T + p 2 T = p miss T For ttbar (largest background), neutrinos are only source of MET, so MT2 should stay below 80 GeV For dileptonic stops, neutralinos can add more MET, so MT2 distribution can exceed 80 GeV

18. Tight to Loose Method – 1 Lepton Example