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Optimal Tracking Variables Study for Event Follow-Up

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  1. Tracking Variable Study Follow up Ryan Kelley Boris Mangano Vivek Sharma

  2. Purpose • The purpose of this study is to look at tracking variables in order to determine which tracks are ‘good’ and which are ‘fakes’. • Basically, what is a good set of cuts to use (for example isolation studies)?

  3. Define matched vs. unmatched • Loop through all recoTracks in the event and use the RecoToSimAssociator function (associate by hits) in CMSSW to determine if this track is matched to a simulator level particle. • If there is no simTrack associated, then it is an unmatched or fake recoTrack.

  4. Tracking Variables Considered • SimTrack PT < 1 GeV cut. • Don’t understand the two ‘towers’ (Boris believes from increased material). • Most Powerful Cut-- hits > 7.

  5. Tracking Variables Considered • Similar spread for both matched and unmatched. • z0 < 30 cm doesn’t really give you anything. • Sharp peak between d0 < 1mm. • Fakes are very spread.

  6. Tracking Variables Considered • Factor of 10 difference and increasing from 2 > 10.

  7. Z (Matched) • ~50k Z events where each recoTrack is matched to a SimTrack.

  8. Z (Unmatched) • ~50k Z events where each recoTrack is NOT matched to a SimTrack.

  9. QCD (Matched) • ~120k QCD (50 < pt < 80 GeV) events where each recoTrack is matched to a SimTrack.

  10. QCD (Unmatched) • Need to run on a larger sample

  11. Ratio of all tracking cuts to no cuts

  12. Things to do • Try reverse matching: Defined unmatched as a SimTrack that doesn’t have a RecoTrack (done). • What are the  towers (Boris believes it’s the extra material due to cabling/etc. at  around 1.5). • Run on larger samples (done, but should have run on more QCD samples with different pt ranges). • Try to cut on expected hits instead of total hits--some of the  regions have more layers than others. A hard number may be not work well the regions with fewer layers.

  13. Backups Normalized valid hits plot.

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