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Update Nick Amin Nov. 14, 2019 Overview Last update These slides - - PowerPoint PPT Presentation

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Update Nick Amin Nov. 14, 2019 Overview Last update These slides L1 selection Misc. checks of muon chi2, track isolation Signal MC "scan" Start looking into GP regression 2 L1 selection Finalize L1

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SLIDE 1

Update

Nick Amin


  • Nov. 14, 2019
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SLIDE 2

⚫ Last update ⚫ These slides

  • L1 selection
  • Misc. checks of muon chi2, track isolation
  • Signal MC "scan"
  • Start looking into GP regression

Overview

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SLIDE 3

⚫ Finalize L1 selection

  • OR of
  • L1_DoubleMu4p5_SQ_OS_dR_Max1p2
  • L1_DoubleMu0er1p4_SQ_OS_dR_Max1p4
  • L1_DoubleMu_15_7
  • Removed L1_DoubleMu_15_5_SQ because it was not

part of HLT inputs, even though it was active/ unprescaled

  • Not updated yet (next set of babies)

L1 selection

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SLIDE 4

⚫ http://uaf-10.t2.ucsd.edu/~namin/dump/plots/plots_split_v4/ ⚫ Plot dump of various variables split by

  • nothing ("splitnone_")
  • near or away from pixel material ("splitpixel_")
  • DV rho ("splitrho_")
  • eta of dimuon system ("spliteta_")
  • pT of dimuon system ("splitpt_")
  • mass of dimuon system ("splitmass_")
  • dphi(mu1,mu2) ("splitdphimumu_")

⚫ Selection

  • ==2 OS muons
  • ==1 DV
  • DV rho > 1cm
  • cos(𝛦𝜚(dimuon,DV))>0
  • max(DV x error,DV y error)<0.05cm
  • DV z error<0.1cm
  • # valid muon hits > 0 for both muons

Plot dump

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SLIDE 5

⚫ Plot muon chi2 for subleading muons for 1<m𝜈𝜈<4 separated into on-

and off-j/psi

  • Comparing DY and j/psi so they look the same (off and on)

⚫ Also include signal MC, and data on-j/psi with pT,𝜃 reweighted to MC

Muon chi2

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SLIDE 6

⚫ Track isolation computation based on the

hltIter2L3MuonMergedNoVtx track collection

  • Calculated within a cone of 𝛦R<0.3 for tracks within

dz<0.2 and d0<0.1

  • Exclude 𝛦R<0.01 tracks
  • Exclude leading track if it has pT>2 GeV and 𝛦R<0.025

⚫ Stored ScoutingTrack collection from

hltIterL3MuonAndMuonFromL1MergedNoVtx

⚫ Isolating the peak around 1, I couldn’t find a track close to

the subleading muon (in 𝛦R and pT) in the stored collection.

  • However, sanity cuts on DV errors eliminate the

majority of the peak at 1

TrackIso == 1

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max(DV x error, DV y error) DV z error

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SLIDE 7

⚫ Generated 100k events for a handful of lifetimes and masses (still H(125)→ZdZd→2𝜈+2X)

  • Efficiency of gen-level fiducial denominator requirement wrt full sample is ~64%
  • Reco*trigger efficiency below

Signal MC

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SLIDE 8 ⚫ Other groups looking to use gaussian process regression fits
  • Non-parametric, learns distribution over space of functions rather than space of parameters
⚫ Still need to understand how (poisson) error is encoded, and certain input parameters ⚫ But, out of the box, we can get smooth fits when blanking out resonances in order to subtract out background ⚫ Left
  • In data, fit invariant mass distributions around J/psi in bins of DV 𝜍
⚫ Right
  • Plot background-subtracted J/psi yields as a function of displacement
  • Overlay yields from a JpsiToMuMu MC sample (note, scouting collections are included up to AODSIM)
  • Seems like prompt Jpsi MC

GP regression

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SLIDE 9

Backup

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SLIDE 10

⚫ Repeat L1 checks from previous set of slides, but

with full 2018 data (4B events) instead of just 50M events in 2018C

  • The seeds I’ve been using since last time

(DoubleMu4p5_SQ_OS_dR_Max1p2 || DoubleMu_15_5_SQ || DoubleMu_15_7) are still in the unprescaled=1 set. Good.

⚫ EXO-19-018 AN has

L1 in full 2018

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fired unprescaled L1_DoubleMu0 L1_DoubleMu0_Mass_Min1 L1_DoubleMu0_OQ L1_DoubleMu0_SQ_OS L1_DoubleMu0er1p5_SQ L1_DoubleMu0er2p0_SQ_OS_dR_Max1p4 L1_DoubleMu0er2p0_SQ_dR_Max1p4 L1_DoubleMu_12_5 L1_DoubleMu_15_7_Mass_Min1 L1_ZeroBias 6.2417E-05 L1_DoubleMu0er1p5_SQ_OS 0.00138888 L1_DoubleMu4_SQ_OS 0.001443 L1_DoubleMu0_SQ 0.002448 L1_DoubleMu4p5_SQ_OS 0.00408753 L1_DoubleMu4p5er2p0_SQ_OS 0.0107283 L1_DoubleMu0er1p5_SQ_dR_Max1p4 0.0689305 0.155734 L1_DoubleMu10_SQ 0.0295695 0.29647 L1_DoubleMu4_SQ_OS_dR_Max1p2 0.471659 0.732179 L1_DoubleMu9_SQ 0.110944 0.919628 L1_DoubleMu_15_7_SQ 0.117701 0.919628 L1_DoubleMu0er1p5_SQ_OS_dR_Max1p4 0.395483 0.999874 L1_DoubleMu18er2p1 0.0187654 1 L1_DoubleMu_15_7 0.132635 1 L1_DoubleMu_15_5_SQ 0.168136 1 L1_DoubleMu4p5er2p0_SQ_OS_Mass7to18 0.176602 1 L1_DoubleMu0er1p4_SQ_OS_dR_Max1p4 0.327869 1 L1_DoubleMu4p5_SQ_OS_dR_Max1p2 0.550969 1

In 2018, the DST path collected the total integrated luminosity of 61.3 fb−1. The L1 seeds L1 DoubleMu 12 5, L1 DoubleMu 12 8, L1 DoubleMu 13 6, L1 DoubleMu 15 5 were inactive and only L1 DoubleMu 15 7 was present. The following never pre-scaled and never disabled L1 seeds are considered only:

  • L1 DoubleMu4p5 SQ OS dR Max1p2 OR
  • L1 DoubleMu4p5er2p0 SQ OS Mass7to18 OR
  • L1 DoubleMu 15 7

⚫ I don’t understand the claim about

DoubleMu_15_5 being inactive, since I see it was firing and unprescaled for the whole dataset

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SLIDE 11

⚫ Consider only events with a displacement >1cm ⚫ Separate into "near" and "away" based on simple

rectangular rho-z regions to cut out pixel layers

Pixel volumes

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SLIDE 12 ⚫ Try to look for pixel hits between the beamspot and the DV ⚫ No hitpatterns, so start with a simple case looking at the displacement and nValidPixelHits for nearly transverse muons in the barrel
  • Plot distribution of valid pixel hits for leading muon with DV rho within one of 3 bins between the first 3 layers
  • Leading muon |𝜃|<0.5, DV |z| < 20cm, cos(𝜚)>0.95
⚫ MC peaks where we expect ⚫ Removing low pT muons cleans up data a little bit

Pixel hits before vertex

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1-2cm 4-6cm 8-10cm

# valid pixel hits

MC data data

pT>25GeV

  • verlaps?
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SLIDE 13

⚫ Sample

  • MC with c𝜐=50mm and mZd=20GeV
  • Gen-level denominator requirements: ≥2 muons with pT>4GeV, |𝜃|<2.4, vertex displacement 𝜍<11cm

⚫ For the L1 seeds marked in blue on the previous slide, calculate the efficiency of each seed wrt the

denominator above

  • For the 3 seeds with 𝜃 requirements, also add a column with |𝜃|<1.4/1.5/2.1 in the denominator instead

⚫ Best combination of 4 L1s is (DoubleMu0er1p5_SQ_OS_dR_Max1p4 || DoubleMu9_SQ ||

DoubleMu_15_5_SQ || DoubleMu_15_7) which gives an efficiency of 88.7%

  • If we remove DoubleMu9 and DoubleMu10, then we get (DoubleMu0er1p5_SQ_OS_dR_Max1p4 ||

DoubleMu0_15_5_SQ || DoubleMu0_15_7) and an efficiency of 87.6%

  • If we also remove eta-restricted seeds, then we get (DoubleMu4p5_SQ_OS_dR_Max1p2 ||

DoubleMu_15_5_SQ || DoubleMu_15_7) and an efficiency of 86.7%

L1 triggers (MC efficiency)

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eff eff w/ |𝜃| DoubleMu18er2p1 0.342 0.378 DoubleMu0er1p4_SQ_OS_dR_Max1p4 0.463 0.753 DoubleMu0er1p5_SQ_OS_dR_Max1p4 0.497 0.751 DoubleMu4p5_SQ_OS_dR_Max1p2 0.621 DoubleMu10_SQ 0.647 DoubleMu9_SQ 0.682 DoubleMu_15_7_SQ 0.762 DoubleMu_15_7 0.782 DoubleMu_15_5_SQ 0.842

"SQ" uses tighter quality requirements from SingleMuon seeds (L1 details here and here)

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SLIDE 14

⚫ MC sample

  • H(125)→ZdZd→2𝜈+2X
  • c𝜐=50mm and mZd=20GeV
  • SM Z BRs — 98.2% (1.8%) of events are 2𝜈 (4𝜈)

⚫ At least 2 gen muons must pass each cut

Gen cutflows

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N-1 cut yield fraction wrt inclusive all 1.00 pT>4GeV 0.81 pT>5GeV 0.76 |𝜃|<2.1 0.70 |𝜃|<2.4 0.77 𝜍<11cm 0.61 cumulative cut yield fraction wrt inclusive 𝜍<11cm 0.61 pT>4GeV 0.49 |𝜃|<2.4 0.38

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SLIDE 15

Track isolation vs displacement

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