1 / 16

MuGirl: Muon Identification Package for Improved Particle Tracking

MuGirl is a new package designed to identify muon particles in high-energy physics experiments. It utilizes advanced algorithms to improve muon tracking by extrapolating tracks, collecting hit and segment information, and selecting muon candidates based on machine learning. MuGirl enhances the identification process by combining various program outputs using artificial neural networks, leading to a more efficient and accurate muon identification system.

candaced
Download Presentation

MuGirl: Muon Identification Package for Improved Particle Tracking

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. MuGirl – a muon identification package S. Tarem1,2,Z. Tarem2, N. Panikashvili1,3 , D. Primor4 1Technion, 2CERN, 3U. of Michigan, 4Tel Aviv U.

  2. Algorithm flow • Initialize Muon candidate from ID track parameters • Extrapolate track to Muon Spectrometer chambers • Look for hits in a road around the track extrapolation • Make segments from hits • Improve extrapolation by using segment information • Collect hit & segment information to identify muon • ANN to create one figure of merit • Select “muon like” candidates • Cut values on lowest pT & ANN output are job options

  3. Replacing the MuidLowPt algorithm • A new package is under development • Run independently of MOORE/Muid • Improved extrapolation • TGC/RPC segments • MDT segments using Hough transform – D. Primor • CSC segments using Hough transform – D. Primor & N. Amram • ANN used to combine program outputs into one optimal discriminator • Radically improved SW design • Component based, modular, reusable, documented…. • Uses new Muon EDM • Will replace program MuidLowPt from release 12

  4. Where to look for hits • Extrapolation from ID, chamber selection, extrapolate to chamber RegionSelector RegionSelector

  5. Segment making (TGC) • TGC has • 2 layers in the inner station – can measure a point • Only partial geometric coverage • 7/6 layers in the middle station – can measure a segment • Nothing in the outer station • TGC segments made using hits with 2<10 • Interpolation from TGC segments to MDT • If too few points for segment, the measured position is used with direction taken from extrapolated ID track • Improvement in road width

  6. Hits and extrapolations

  7. Roads from ID vs roads from TGC • Δη between extrapolated position and hit MDT tube • Inner station Middle station Outer station • extrapolated • from middle 6 6 20 20 20

  8. Barrel ID vs MDT segment • Δη between extrapolated position and hit MDT tube • Inner station Middle station 20

  9. Segment making (MDT) • Use Didi’s Hough transform segment maker • Interface sends RIO_OnTrack in 2 vectors (chambers) • Will return lower quality segment if just one multilayer • Modified interface to send also road parameters • Get back MuonSegment – quality factor more than just 2

  10. Preliminary performance • We ran on DC3 validation files of • H4 • Some single muons • BsJ/Ψ(μ3μ6) φ • bbμ6 X • A few selections attempted • efficiency/fake-rate calculated pT Fake rate η efficiency

  11. Number of MDT segments per candidate

  12. Performance for J/Ψ(μ3μ6) • Right – MuidLowPt • Bottom – MuGirl • Background bbμ6 X • Low background statistics J/Ψ μ+μ- μ-fake

  13. Plans • Complete unfinished features from slide 3 • RPC segments • CSC segments using Hough transform • ANN used to combine program outputs into one optimal discriminator • Make a thorough test of performance with cavern background etc. • Try it on more Physics samples • RTT • New package structure

  14. Backup

  15. More on fakes • Do we have fakes from k/pi decays? How can we eliminate them • We looked at the change of direction (in eta for now) from the ID track to the TGC segment for muons and fakes Muons fakes

  16. μ μ Recall MuidLowPt – our old program • Running after MOORE & Muid, using Muon hits  MDTRPC/TGC + + + + + + + + + + +  + + + + + + + + + + + +

More Related