DevelopmentswiththeConeAlgorithminRunII.pptVIP

Developments with the Cone Algorithm in Run II John Krane Iowa State University Lost Jets and Search Cones CDF: Matthais Toennesmann D?: John Krane Cones can iteratate away from “small” Energy clusters There is a reason I’m showing the CDF image Best Description of Procedure Use a small cone to find jets and iterate locations Expand cone size to full 0.7 and save Find midpoints Iterate 0.7 size midpoint jets Wanted to check CDF’s solution and provide feedback Results on selected sample (45 evts) Seed tracking on a sample of 45 suspicious events Distance of nearestfound jet from original seed Symmetric in y-f, so just use R... Drift distance for 0.7 cones, pT15 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 R=0.5 Cones Same comments apply... R=0.3 cones Again... Normalize drift distances by R R=0.5 cones,scaled distance CPU Requirements Conclusions for Search Cones 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 in D? data) Search cones can limit drift as much as we like R/2 works well (almost perfectly) R Suggestions for Future Work 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 Inclusive Jet and Dijet Mass Integrated Luminosity for Moriond Current Jet Triggers Future Jet Triggers John Krane -- D? * * MC Workshop Oct. 4 2002, Fermilab Part I: Data vs MC, interpreted as physics Part II: Data vs MC, interpretedas a tuning problem Abs y drift Abs f drift Each point was a seed x-axes have suppressed zero John Krane -- D? *