Marcel Vreeswijk (NIKHEF) B tagging, performance vertexing Neural Net studies tt event selection mass reconstruction in tt events conclusions B tagging in the tt all jets channel By: Graziano Massaro Michiel Vogelvang (university student) Marcel Vreeswijk

Marcel Vreeswijk (NIKHEF) secprobPerformance secprob algorithm in tt events (p05 & p08) Reminder: B tagging & vertexing Start with (non PV) selected tracks Significance>3 Make all possible 2-track vertices (vertex fits) Keep/Kill vertices with shared tracks Add tracks (based on probability: opening angle, Pt) Vertex fit based on impact parameters

Marcel Vreeswijk (NIKHEF) Signal Events: Performance vertexing Background events KALMAN selects significantly more QCD jets (used without any additional cuts: what are they?) Efficiency SECPROB and KALMAN compatible. No large effect from min. bias. MC samples, thanks to Suyong!!!

Marcel Vreeswijk (NIKHEF) Performance vertexing Performance SECPROB as func of Et Performance KALMAN as func of Et S(ttbar)/B(QCD) Bjet eff. KALMAN: higher QCD background

Marcel Vreeswijk (NIKHEF) Signal Events (cuts): Performance vertexing S(ttbar)/B(QCD) Bjet eff. S/B ratio not dependent on Decay Length

Marcel Vreeswijk (NIKHEF) Reminder: vertex constructed based on probability (Opening angle, Et) Now: try to find variables to discriminate between B vertices and QCD fakes, using a Probalistic Neural Network vertexing and beyond Event CAL Jet-Tracks Vertex in Jet Preliminary!!!!!!!

Marcel Vreeswijk (NIKHEF) Strategy NN: take Et_vtx and Opening_Angle_vtx as base variables and see the effect of a third variable. the Et_jet and  based on jet-track impact parameters appear promising vertexing and beyond Jets-QCD Bjets-ttbar Ratio Probability from NN  -jet-track impact parameters Preliminary!!!!!!! 2bcontinued

Marcel Vreeswijk (NIKHEF) Conclusions The performance of the SECPROB and KALMAN algorithm are studied using ttbar and QCD events. KALMAN has a slightly higher efficiency for B-vtxs, but finds significantly more QCD fake vtxs To find discriminating variables between good/fake vtxs a NN is used as tool. Many variables are tried: Et_jet and  based on jet-track impact parameters appear promising

Marcel Vreeswijk (NIKHEF) For the ‘All jet’ channel tt event (pre)selection At least 5 jets with |  |<2 Et of jets tt qcd Simple, effective, but: QCD has to be multiplied by 10 7

Marcel Vreeswijk (NIKHEF) From D0-RunI pubs: E T3 = Et of jets, skipping 2 highest Et jets. tt event (pre)selection Cut appears less effective than in RunI. Why? In RunI: Initial jets in QCD events have large Et. The additional jets originate from QCD splittings and have low Et. Skipping 2 highest Et jets has large effect. For ttbar event effect is average: E T3 (QCD) < E T3 (ttbar) In RunII: QCD background has significant contribution from min. bias, which dillutes this effect. Note: multiply QCD by 10 7

Marcel Vreeswijk (NIKHEF) Alternative: tt event (pre)selection tt qcd Et(5-jets)/Et(jets) vs QCD: low Et per jet, many jets ttbar: high Et per jet contained in not so many jets. Need many more QCD events!!!!

Marcel Vreeswijk (NIKHEF) Mass reconstruction in tt--> all jets A very preliminary study b t W W b j j t j j Difficult final state: 4+2 jets But, many constraints: W mass (2x) Both branches should yield similar top mass Selection (no preselection): At least 6 jets. Keep 6 highest Et jets 2 jets have vertex--> B candidates. Reconstruction: 2x2 W jets lead to 3 mass combinations These mass combinations are then assigned to B candidates: 6 mass combinations. Take combination with best  2 based on Mw (2x) and Mt1-Mt2

Marcel Vreeswijk (NIKHEF) Mass reconstruction in tt--> all jets Background: 5* QCD events need more MC!!!!!! tt QCD True mass ALL

Marcel Vreeswijk (NIKHEF) Mass reconstruction in tt--> all jets Mass peak looks fine, but…. Good mass combs. Bad mass combs. The mass peak seems independend on bad/good combinations of the jets?!?! Side remark: particle info in IN_PRT is corrupted as reported. In this study we attempted to take this into account properly.

Marcel Vreeswijk (NIKHEF) Mass reconstruction in tt--> all jets W-mass (recoed) tt qcd tt Note: multiply QCD by 10 7

Marcel Vreeswijk (NIKHEF) Conclusions The performance of the SECPROB and KALMAN algorithm are studied using ttbar and QCD events. KALMAN has a slightly higher efficiency for B-vtxs, but finds significantly more QCD fake vtxs To find discriminating variables between good/fake vtxs a NN is used as tool. Many variables are tried: Et_jet and  based on jet-track impact parameters appear promising The (pre)selection of ttbar events was studied. Cuts used in RunI apeared to have less effects due to min. bias overlay. New cuts are suggested. Can we measure the top mass in ttbar->All jet channel? A preliminary study, using all mass constraints yield a mass peak. However, this peak also show up for wrong jet-combinations(?).

Marcel Vreeswijk (NIKHEF) Background Events (cuts): Performance vertexing

Marcel Vreeswijk (NIKHEF) Signal Events (cuts): Performance vertexing

Marcel Vreeswijk (NIKHEF) Strategy NN: take Et_vtx and Opening_Angle_vtx as base variables and see the effect of a third variable. the Et_jet and  based on jet-track impact parameters appear promising vertexing and beyond QCD jets B jets ttbar Probability from NN Ratio For Et-jet

Marcel Vreeswijk (NIKHEF) Validate ‘P9’ WH and QCD events versus ‘p8’ events (All samples from Suyong) First check distributions. Plots added of the tracking in jets related quantities: Check p8 vs p9 Sum of significances of tracks in jet wrt PV Sum of significances of tracks in SV wrt SV See Plots, distributions look ok. Differences probably due to different cuts (Et in QCD generation), #min bias events and code changes

Marcel Vreeswijk (NIKHEF) QCD p8

Marcel Vreeswijk (NIKHEF) QCD p9

Marcel Vreeswijk (NIKHEF) ttbar p8

Marcel Vreeswijk (NIKHEF) WH p9

Marcel Vreeswijk (NIKHEF) Signal events Efficiencies Background Number of ‘taggable’ Bjets + efficiency look fine Number of tagged PV jets in QCD is significantly higher in P9. Probably explained by Et generator cut and/or #min. bias events.