Search for Narrow Resonance Decaying to Muon Pairs in 2.3 fb -1 Chris Hays 1, Ashutosh Kotwal 2, Ye Li 3, Oliver Stelzer-Chilton 1 1 Oxford University 2 Duke University 3 University of Wisconsin-Madison

APS April Meeting, St. Louis - 14 April Ye Li Motivation  Theory Driven  Standard Model successful but incomplete  Strong discovery potential in dimuon channel  New models predict narrow neutral resonance, e.g. additional U(1) symmetry: Z’ extra space-time dimension: Randall-Sundrum graviton  The present analysis focuses on Z’ →  channel

APS April Meeting, St. Louis - 14 April Ye Li Motivation  Experiment Driven  Last CDF and DØ dimuon resonance searches performed with integrated luminosity 200 pb -1 → Our search: L ≈ 2.3 fb -1 of CDF Run II data  Significant increase of sensitivity to dielectron and diphoton channels  Excellent tracking resolution (Central Outer Tracker, Drift Chamber)

APS April Meeting, St. Louis - 14 April Ye Li Methodology  Model Drell-Yan background and signal resonance with PYTHIA + fast simulation for W mass measurement  Use Z region for normalization  Remove uncertainty on luminosity  Easy accounting  Compare CDF fast simulation (FastSim) to full Geant simulation (CDFSim) and data for acceptance and efficiency study

APS April Meeting, St. Louis - 14 April Ye Li Methodology  Inverse Mass (1/m  ) Scan  Excellent angular resolution → negligible  Track curvature (~1/P T ) resolution constant for high P T → constant 1/m  resonance width  1/m ≈ 0.16/TeV

APS April Meeting, St. Louis - 14 April Ye Li Methodology  Fit for N Z’ (number of Z’ candidate)  Calculate Binned Poisson likelihood L(N Z ’;M Z’ ) for region 1/m  < 10/TeV  Construct the narrowest possible interval in N Z’ at 95% C.L.  Scan 1/m  spectrum for Z’ resonance  Use Monte-Carlo Pseudo-experiments to determine the significance

APS April Meeting, St. Louis - 14 April Ye Li Dataset & Selection  Dataset from high P T muon trigger  The dimuon event selection  The muon identification requirement EM energy cut tuned for high efficiency of Z High identification efficiency ~ 95%

APS April Meeting, St. Louis - 14 April Ye Li Efficiency  Mass dependence  Assume track and muon-hit cuts independent of mass  Momentum dependence  Only consider P dependence, due to the normalization of background expectation  Assume no P dependence of trigger efficiency for P T > 30 GeV  Separate the sample into signal and normalization (Z-pole) regions

APS April Meeting, St. Louis - 14 April Ye Li Efficiency  EM and Hadronic Cut Efficiency  Signal region: constant ratio between FastSim and CDFSim (no inefficiency of Had cut for FastSim → 2% const. offset)  Z-pole region: ratio between FastSim and Data drops at low P (due to incomplete modeling) insufficient data for signal region compute uncertainty from data-simulation difference

APS April Meeting, St. Louis - 14 April Ye Li Acceptance  Implement detector Geometric information on FastSim  Map angular distribution of CDFSim to FastSim;  W →  data and FastSim agree reasonably Muon  for 0.6 < |  | < 1.0 (CMX) Muon  for |  | < 0.6 (CMUP)

APS April Meeting, St. Louis - 14 April Ye Li Acceptance  Mass-dependent Acceptance  Larger mass → Lower boost → More central events → Larger acceptance  Constant Ratio between FastSim and CDFSim → Validate acceptance calculation from FastSim  Uncertainty from the small slope of the ratio

APS April Meeting, St. Louis - 14 April Ye Li Background  Drell-Yan  */Z →   PYTHIA + FastSim  WW and tt-bar  CDF Simulation (PYTHIA + CDFSim)  Cosmic Rays  Identified Cosmic-ray samples  QCD Jets and Decays-in-Flight  Data

APS April Meeting, St. Louis - 14 April Ye Li Drell-Yan  Dominant source for background  Mass spectrum affected by higher- order corrections  Calculate up to next-to-next-to leading order (NNLO) correction → k-factor  Different Calculations give different k-factors  Average k-factor; Difference as uncertainty

APS April Meeting, St. Louis - 14 April Ye Li Drell-Yan The Stirling and Hamburg, van Neervan and Matsuura (HNM) calculations of the k-factor About 6% difference ( ~3% systematic uncertainty)

APS April Meeting, St. Louis - 14 April Ye Li WW tt & Cosmic Ray  WW, tt →  + missing E T : Simulate PYTHIA samples using CDFSim to compute background  Cosmic Ray : Use timing information of Drift Chamber to estimate  Background fraction ~ 1.2 X 10 -6

APS April Meeting, St. Louis - 14 April Ye Li QCD & DIF  Assumtions  QCD jets faking muons: same-sign dimuon (SS) and Opposite-sign dimuon background (OS) distribution have similar shape, i.e. constant OS/SS ratio  Decay-in-flight muons: flat distribution of DIF muons at small curvature (high P T → small 1/m  )  Track  2 cut reduces DIF events  Same-sign samples contains both jet fakes and decays-in-flight

APS April Meeting, St. Louis - 14 April Ye Li QCD & DIF SS dimuon obtained from jet triggered data SS dimuon obtained from signal dataset, with  2 cut removed SS dimuon obtained from signal dataset, with  2 cut on

APS April Meeting, St. Louis - 14 April Ye Li Other Issues  Momentum Scale & Resolution  Momentum scale measurement done by fitting Z peak using templates made with FastSim  Resolution tuned on the width of the Z peak  Systematic Uncertainties  Dominant uncertainties: Parton distribution functions Mass-dependent of the NNLO k-factor  Other uncertainties: Arise from P T -dependent acceptance and efficiency Affect the signal and background prediction at high mass

APS April Meeting, St. Louis - 14 April Ye Li Signal Scan  Pseudo-experiment: Standard Model process

APS April Meeting, St. Louis - 14 April Ye Li Signal Scan  Pseudo-experiment: M Z’ = 250 GeV

APS April Meeting, St. Louis - 14 April Ye Li Signal Scan  Expected limits on N Z’ from 1000 pseudo-experiments on 50 Z’ masses  Data: to be implemented …

APS April Meeting, St. Louis - 14 April Ye Li Summary  Use 1/m  distribution for constant resolution  Fitter and Simulation in place to study signal acceptance and identification efficiency  Analysis on different background fractions  Systematic uncertainties to be determined  Signal scan performed on pseudo- experiments

APS April Meeting, St. Louis - 14 April Ye Li Backup: Triggers and dataset  Integrated luminosity 2.3 fb -1 good muon data up to period 13  All CMUP18 and CMX18 triggers on  Reprocess all events with 6.1.4int11 and COT alignment developed for gen 7 of CDF software  Derive momentum corrections using E/p difference between electrons and positrons