Top -> l+jets @ 10 TeV Updates on Efficiencies and Event Shapes

1. Top -> l+jets @ 10 TeVUpdates on Efficiencies and Event Shapes Xiaowen Lei, Ken Johns, Venkat Kaushik (U. Arizona)

2. Outline • Top with C++ ARA • Redesign of code • Update on efficiencies • Update on likelihood study • Analysis redone with bug-fixed Wjets sample; results look reasonable • TMVA approach • Started Muon Isolation Study

3. Top with C++ ARA ARATopAnalysis • ARATopAnalysis package developed by Venkat is committed into the Arizona group cvs area • http://atlas-sw.cern.ch/cgi-bin/viewcvs-atlas.cgi/groups/Arizona/ARATopAnalysis/ • ARATopAnalysis package provides the following • Steering base class with common functions • A default steering class with default selectors • Analysis in this talk was done by selection routines written by user (not the default ones) • Configuration and messaging service • Scripts and executables for submitting jobs to panda • Additional details is available on twiki • https://twiki.cern.ch/twiki/bin/view/Sandbox/VKaushikSandbox#ARATopAnalysis

4. Top with C++ ARA Changes to the user analysis code • Steering in ARATopAnalysis is used now • Analysis methods are rewritten to separate classes • They serve as the user-implemented “selectors” (processors) • Helper classes for “communication” between the processors are added. • Selected objects are stored in mySelectedObjects • Event weights, trigger information, as well as the cut bits are stored in myEventInfo • Rewrote the class for calculating topological variables. Fixed some mistakes. • Now it’s ready to be put into cvs

5. Efficiencies • Lepton+jets selection efficiencies were updated • Weights are properly included • Corrected W+jets samples are used • E368_s463_r563 • Began processing smaller background samples • Updated samples include • Wenu+Np: 108241, 108242, 108243; Wmunu+Np: 108245, 108246, 108247 • Single top: 108240(schan_enu), 108241(schan_munu), 108243(tchan_enu), 108244(tchan_munu) • Tables are on the twiki page • https://twiki.cern.ch/twiki/bin/viewauth/AtlasProtected/TopCSBenchMark#Single_lepton_channel

6. Cuts from the Spreadsheet • Cut 1 – lepton trigger • EF_e20i or EF_mu20 • Cut 2 – exactly 1 (medium) lepton with Pt>20GeV • For electron require • isem(egammaPID::ElectronLoose) ==0 • |eta|<2.5 && !(1.37<eta<1.52) • etcone20<6GeV • For muon require • |eta|<2.5 • etcone20<6GeV • Note for muon, for the mc08 data, isolation is shifted down • etcone40 returns energy in cone with radius 0.3 • should probably correct for it • Cut 3 – MET>20GeV • Cut 4 – 4 good jets with Pt>30GeV • Cut 5 – 3 good jets with Pt>40GeV • Cut 6 – 150<m_jjj<190GeV

7. e+jet Efficiencies • Efficiencies

8. mu+jet Efficiency • Efficiencies

9. Topological Variables • Analysis was redone with corrected W+jets samples (e368_s462_r563) • As a first step, used only 8242 (Np4) for Wenu+jets and 8246(Np4) for Wmunu+jets • Repeated our previous analysis to see if it works • No further optimization of the likelihood is done yet • Use events which passed cuts 1-5 • A total number of 12 transformed variables are currently used • See following slides for plots of topological varialbes and template functions • TMVA approach • TMVA seems to be a good tool for optimizing the likelihood

10. Topological Variables – mu+jets log(ht): sum(et) for jets et>15GeV log(ht_2): log(et_j1+et_j2) log(ht_3): log(et_j3+et_j4) log(ht’_2): log(Sum(et)_j234/Sum(pz)_j1234) log(he) is also used but not shown here

11. Topological Variables – mu+jets log(centrality): log(ht/he) To remove? exp(-11apla): apla = 3/2Q_1 log(sphe): sphe = 3/2(Q_1+Q_2)

12. Topological Variables – mu+jets Log(mjj_min): minimum dijet mass Use 4 leading jets dPhi: angle between leading lepton and missing et log(K’_Tmin): minimum dijet distance * et of the lower in the pair / hadronic W et masschisq

13. Topological Variable Fits – mu+jets

14. Topological Variable Fits – mu+jets

15. Topological Variable Fits – mu+jets

16. Topological Likelihood Lt e+jets: mu+jets:

17. Study with TMVA • Get similar comparison plots and likelihood plots. TMVA also give extra outputs which I am learning to understand • TMVA is nice because it gives correlation between variables. It can also be easily configured to use diferent variables

18. Muon Isolation • We started looking at muon isolation • As a first step we compared etcone20 (cone size 0.1) of ttbar (105200) and bbmu15X (108405) • No cuts on muons • We are still at a very initial stage but plots can be easily added and quickly produced • A few things on our to-do list: • Compare etcone for different cone sizes. Also need to compare different inner cone sizes • Come up with cuts to extract the signal (muon from W) • Need to add cuts and change to log scale to see more clearly

19. Conclusions • Conclusions • We changed our C++ ARA code into a better design • The code is ready to be put into cvs • We updated lepton+jets efficiency tables for bug-fixed W+jets samples and single-top samples • We redid our likelihood analysis with the new W+jets sample • Background still has low statistics • We tried the same likelihood analysis with TMVA • Looked at the correlation matrix • We made preliminary plots for muon isolation study

20. To-Do List • To-do list: • We need to take into account the problem of shifted muon isolation • Since Atlfast samples for W+jets are available now (e368_a68), we can use them to increase the background statistics • Next we will consider single top as a background in our likelihood study • TMVA seems to be a nice tool for optimizing likelihood analysis. We want to use it to: • Try different combination of the variables • Study the correlation between the variables • We would like to continue with muon isolation study