1 / 12

Lost Jet Update

Lost Jet Update. John Krane Iowa State University jet/MET Meeting 8/29/02. reminder of problem performance metric parameter choice. CDF Physics groups are not using Run II algorithm. Problem: unclustered event energy. CDF: Matthais Toennesmann DØ: me, Vishnu Z., Bob H.

damia
Download Presentation

Lost Jet Update

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. Lost Jet Update John Krane Iowa State University jet/MET Meeting 8/29/02 • reminder of problem • performance metric • parameter choice

  2. CDF Physics groups are not using Run II algorithm Problem: unclustered event energy • CDF: Matthais Toennesmann • DØ: me, Vishnu Z., Bob H. Cones can iteratate away from “small” Energy clusters • The Run I algorithm did this too... John Krane -- Iowa State University

  3. Modified Cone Algorithm CDF’s “search cones” • Use a small cone to find jets and iterate locations • Expand cone size to full 0.7 and save • Find midpoints found a phi-wrap bug; using pT-weight not 4vec? • Iterate 0.7 size midpoint jets John Krane -- Iowa State University

  4. I never found a lost jet, but they must exist... Results on selected sample (45 evts) Each point was a seed Seed tracking Plot shown in OK workshop Symmetric in y-f, so just use R... p11’ Abs f drift Abs y drift John Krane -- Iowa State University

  5. Drift distance for 0.7 cones, pT>15 GeV • If a seed is too close (R/2) to existing jet, ignore it • Standard cones can drift very long distances! • Search cone R/2 limits drift to R... John Krane -- Iowa State University

  6. R=0.5 Cones Same comments apply... John Krane -- Iowa State University

  7. R=0.3 cones Again... John Krane -- Iowa State University

  8. Normalize drift distances by R • R=0.5 cones,scaled distance John Krane -- Iowa State University

  9. x-axes have suppressed zero John Krane -- Iowa State University

  10. Conclusions • Cones can drift quite far from the seed, even for reasonably high-pT Jets >15 GeV • This doesn’t mean a jet is “lost” every time this happens (I have yet to find a lost jet) • Search cones can limit drift as much as we like • R/2 works well (almost perfectly) "R John Krane -- Iowa State University

  11. Suggestions for Future Work • Implement my rcp-driven code (but not necessarily a search cone setting just yet) • Search_Factor=1.0 means no search cone • Search_Factor=0.5 eventually... • Run full Reco tests for CPU time and consistency • Consult CDF and try to converge on a parameter • Informally, Joey Huston thinks R/2 works well • Would like permission to show this talk externally John Krane -- Iowa State University

  12. Files altered for Search Cone mod energycluster/ILConeAlgorithm.hpp(Constructor allows search_cone argument,midpoint calculation fixed for phi-wrap,is_stable() need not iterate,min jet pT reduced during search phase) calreco/CalClusterReco.cpp(Read and pass Search_Factor from rcp) calreco/rcp/CalILCone07.rcp calreco/rcp/CalPreSCILCone07.rcp calreco/rcp/CalPreSCILCone05.rcp calreco/rcp/CalPreSCILCone03.rcp John Krane -- Iowa State University

More Related