1 / 19

Study of SISCone A Seedless Infrared-Safe Cone jet algorithm

Study of SISCone A Seedless Infrared-Safe Cone jet algorithm. Manoj Jha (Delhi) Anwar Bhatti (Rockfeller) Marek Zielinski (Rochester) Monica Acosta (CERN) 23 rd July, 2007 Jet Algorithm Subgroup. Outline. Cone jet algorithm Infrared-Safety issues Why is this mandatory ?

ryanbennett
Download Presentation

Study of SISCone A Seedless Infrared-Safe Cone jet algorithm

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. Study of SISCone A Seedless Infrared-Safe Cone jet algorithm Manoj Jha (Delhi) Anwar Bhatti (Rockfeller) Marek Zielinski (Rochester) Monica Acosta (CERN) 23rd July, 2007 Jet Algorithm Subgroup

  2. Outline • Cone jet algorithm • Infrared-Safety issues • Why is this mandatory ? • IR unasfety of the midpoint algorithm • SIScone: A pratical solution • Results • High PT jets • Low PT jets • Dark energy towers • Effect of pileup • Conclusion & Next Steps

  3. Cone jet algorithms • Given: set of N particles with their 4-momentum • Goal: clustering those particles into jets • Idea: jets = cones around dominant energy flows for a cone of radius R in the (η,φ) plane, stable cones are such that center of the cone ≡ direction of the total momentum of its particles • Algorithm: Tevatron Run II • StepI: find ALL stable cones of radius R • StepII: run a split-merge procedure with overlap fraction f to deal with overlapping stable cones

  4. Midpoint cone algorithm Usual seeded method to search stable cones: MP cone algorithm • For an initial seed • sum the momenta of all particles within the cone centered on the seed • use the direction of that momentum as new seed • repeat above steps until stable state cone reached • Sets of seeds: • All particles (above a pT thresholds) • Midpoints between stable cones found in 1. Problems: • the pT threshold s is collinear unsafe • seeded approach → stable cones missed → infrared unsafety

  5. Infrared Safety: Why ? IR Safety: Stability upon emission of soft particles, is required for perturbative computation to make sense ! Cancellation of IR divergences between Real and virtual emissions of SOFT gluons. • If Jet clustering is different in both cases, THEN the cancellation is not done and the results, in principle, cannot be compared to pQCD • Stable cones must not change upon addition of soft particles

  6. SISCone: seedless solution • Naive approach: check stability of each subset of particle. Complexity is Ο(N2N) i.e. definitely unrealistic (1017 years for N = 100) Idea: all enclosures are defined by pair of points • Tricks: • Traversal order to avoid recomputation of the cone content • Complexity: • SISCone is Ο(Nn ln n) ( with n ~ N the number pf points in a circle of Radius R • Midpoint standard implementation is Ο(N2n) • For more information: see 0704.0292[hep-ph]

  7. Data Samples • CMSSW_1_5_2 QCD Jets in pT hat 120-135 GeV • Considered Calorimetry jets only • Parameters for SISCone jets SISConeJetParameters = {double cone radius = 0.5 double coneOverlapThreshold = 0.75 int32 maxPasses = 0 double protojetPtMin = 0. } • Parameters MidPoint jets MidPointConeJetParameters = { double coneRadius = 0.5 double overlapThreshold = .75 double seedThreshold = 1.0 double inputPtMin = 0.5 int32 maxPairSize = 2 int32 maxIterations = 100 } • No. of events = 7000

  8. Results

  9. No. of jets for jets PT > 35 GeV MidPoint5 SISCone5 Mean ~ 2.78 Mean ~ 2.76

  10. PT of Jets for PT > 35 GeV MidPoint5 SISCone5 Mean ~ 85.46 Mean ~ 85.27

  11. ΣPT of Jets for PT > 35 GeV MidPoint5 SISCone5 Mean ~ 192.0 Mean ~ 190.5 • Good agreement between midPoint and sisCone algorithm for jets having PT > 35 GeV.

  12. ΣPT of Jets for 0.1 < PT < 5 GeV MidPoint5 SISCone5 Mean ~ 43.45 Mean ~ 95.65

  13. PT of Jets for 0.1 < PT,jet < 5 GeV MidPoint5 SISCone5 Mean ~ 2.78 Mean ~ 1.87

  14. No. of jets for jets 0.1 < PT < 5 GeV MidPoint5 SISCone5 Mean ~ 16.04 Mean ~ 51.06 • SISCone algorithm produces more number of jets in low PT region with respect to midPoint algorithm.

  15. Distribution of dark energy towers MidPoint5 SISCone5 Mean ~ 0.307 Mean ~ 0.216 • Some of the energetic towers are being left by midPoint algorithm. • No problem of dark energy towers in case of sisCone algorithm.

  16. Σ Dark energy towers MidPoint5 SISCone5 Mean ~ 147.5 Mean ~ 106.5 • Midpoint algorithm is around ~28% energy (ET) deficient in comparison to SISCone algorithm.

  17. Effect of Pileup on jet PT MidPoint5 SISCone5 Mean y ~ 0.858 Mean y ~ 0.524

  18. Effect of Pileup on jet PT MidPoint5 SISCone5 Mean y ~ 0.858 Mean y ~ 0.524 • SISCone algorithm is more sensitive to pileup !!! • Effect of pileup is as much as 35 GeV in some of the events.

  19. Conclusions & Next Steps • Good agreement between jets from midpoint and SISCone algorithm for high PT jets > 35 GeV. • SISCone algorithm produces more number of jets in low PTregion with respect to midpoint algorithm. • Some of the energetic towers are being left by midpoint algorithm. • No problem of dark energy towers in case of SISCone algorithm. • Midpoint algorithm is around ~28% energy (ET) deficient in comparison to SISCone algorithm. • SISCone algorithm is more sensitive to pileup. • Effect of pileup is as much as 35 GeV in some of the events. • Need of pileup subtraction . • Next Steps: • Pileup subtraction using jet area • Study hadronic top with and without pileup

More Related