2016 dat 2016 dataset aset Huajie Cheng 2020.11.13 Introduction - - PowerPoint PPT Presentation

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2016 dat 2016 dataset aset Huajie Cheng 2020.11.13 Introduction - - PowerPoint PPT Presentation

May 30, 2023 283 likes •500 views

Tau Energy Scale in Tau Energy Scale in 2016 dat 2016 dataset aset Huajie Cheng 2020.11.13 Introduction TES measurement using TauFW Preliminary results using 2016 dataset, in mu-tau events Coarse ES variations applied to real

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Tau Energy Scale in Tau Energy Scale in 2016 dat 2016 dataset aset

2020.11.13 Huajie Cheng

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Introduction

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◆ TES measurement using TauFW

◼ Preliminary results using 2016 dataset, in mu-tau events ◼ Coarse ES variations applied to real tau

  • 3% → 3% in steps of 1% (0.2% for final measurement)

◼ Compare the impacts in DY and TT processes ◼ Fit independently per DM

  • Only in DY process
  • Use mvis and mτ as observables
  • Fix “r” parameter and scan likelihood profile in TES
  • Fit the NLL profile by asymmetric parabola function
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Mu-tau selections

◆ Baseline

➢ Single muon trigger & SF applied ➢ Muon

  • pT > 23 GeV, |eta| < 2.1 or 2.4
  • |dxy| < 0.045, |dz| < 0.2
  • medium ID, rel. iso < 0.15

➢ Tau

  • pT > 20 GeV, |eta| < 2.3, |dz|<0.2, decay modes 0, 1, 10, 11
  • DeepTau2017v2p1VSjet Tight WP
  • DeepTau2017v2p1VSmu Tight WP
  • DeepTau2017v2p1VSe VVLoose WP

➢ Opposite sign mu-tau pair with ΔR > 0.5 and highest mu and tau pT ➢ Extra-lepton veto

◆ mT < 50 GeV

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TES systematic uncertainties

4 Nuisance Parameter Distribution Uncertainty Applied to lumi lnN ±2.5% all, except QCD mu Eff lnN ±2% all, except QCD tau ID shape from recommendation ZTT, TTT DY cross section lnN ±2% DY ttbar cross section lnN ±6% ttbar signle top cross section lnN ±5% single top VV cross section lnN ±5% diboson W+jets normalization lnN ±8% W QCD normalization lnN ±10% QCD jet -> 𝜐 fake rate lnN ±15% ZJ, W, QCD, TTJ, ST jet -> 𝜐 fake ES shape ±5% on jet → 𝜐 energy ZJ, W, TTJ ℓ -> 𝜐 fake rate shape from recommendation ZL, TTL ℓ -> 𝜐 fake ES shape ±2% on ℓ → 𝜐 energy ZL, TTL Z pt reweight shape apply weight ±10% DY

◆ All the shape uncertainties are not yet in place

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Datacard for DM0

◆ Not all syst included, e.g. tid

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Likelihood profile scan

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DM0 DM1 DM10 DM11

◆ Profile the NLL as a function of tes ◆ And the fit with asym parabola function

DM1 DM10 DM11

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Fit result

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◆ DM1 for m_tau

DM1

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Fit result

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◆ DM10 for m_tau

DM10

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Fit result

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◆ DM11 for m_tau

DM11

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Fit result

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◆ DM0 for m_vis

DM0

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Fit result

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◆ DM1 for m_vis

DM1

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Fit result

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◆ DM10 for m_vis

DM10

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Fit result

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◆ DM11 for m_vis

DM11

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Results

◆ Finally got the TES values w.r.t different DMs

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Before fit After fit Ref.

◆ Quite ugly due to very coarse variation step and missing uncertainties ◆ Jobs with step=0.2% almost done! ◆ Asked to give a status report next Monday

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Some distributions

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  • 3% TES

+3% TES

◆ Here are the plots with all DMs combined, the fit will be performed with each DM separately

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Some distributions

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Negligible impact from ttbar

◆ Will only apply the TES in ZTT for the measurement

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Framework: from nanoAOD to final plots

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Sample list

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1 10 100 1000 10000 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Counts in 5 mins (14.16L)

Cases

0.3um 0.5um 1.0um 2.0um 5.0um 10.0um

Air condition monitoring in the clean room

◆ Took 4 samples in each rooms (2 for room 110)

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IV-curve

◆ Finally managed to perform IV measurement remotely by LabView

➢ Change from GPIB to RS232-to-USB cable