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PandoraPFA and LCFIVertex with GLD data

PandoraPFA and LCFIVertex with GLD data. S. Uozumi (Kobe) Apr-23 th ILD detector optimization WG meeting. PandoraPFA Performance with the GLD. With LDC00 Z-pole + full tracking + PandoraPFA, Mark’s result : JER = 23.5 % (pandora v2-01) My result : = 28.5 % (pandora v2-00)

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PandoraPFA and LCFIVertex with GLD data

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  1. PandoraPFA and LCFIVertexwith GLD data S. Uozumi (Kobe) Apr-23th ILD detector optimization WG meeting

  2. PandoraPFA Performancewith the GLD

  3. With LDC00 Z-pole + full tracking + PandoraPFA, Mark’s result : JER = 23.5 % (pandora v2-01) My result : = 28.5 % (pandora v2-00) Where does 5% difference come from ? • At TILC08 Sendai, Mark told us … • We are more-or-less doing a right thing, there seems to be nothing apparently wrong. • Mark generates events with a pythia setting tuned for LEP experiment, which gives 20% less neutral particles in a jet. It will give ~1.5% effect on JER. • Then Mark gave us his z-pole data (both lcio file after detector simulation and stdhep files) and steering file.

  4. JER with various configurations (Z-pole) • There are still some difference, but JER values are OK (<30%) for • ILD optimization study. • We decided to leave more detailed study to be done sometime • in future, and move ahead on the optimization studies anyway.

  5. Flavour Tagging Performancewith the GLD

  6. Z-pole data & Process for FT study • Jupiter data (GLD) 10k events • Jupiter data converted to lcio • Z -> anything, but leptonic decays (~30%) are rejected • No ISR • Mokka (LDC01_05Sc) 10k events • Told by Sonja, copied from DESY GRID • Z -> qq (q=u,d,s,c,b) events • Flavour tagging by FullTracking + PandoraPFA + LCFIVertex with LDC-tuned neural net parameters. Breakdown with true jet flavours : : : :

  7. Jupiter GLD c-tagging performance uds b c NN output for c-tag Mokka LDC01_05Sc w/ conv uds b c • Result with LDC01+fulltracking doesn’t perfectly reproduce • Sonja’s result. But with cheated result, agreement with Sonja becomes better. • Result with GLD data looks consistent with Sonja’s LDC01_05Sc result anyway.

  8. Jupiter GLD b-tagging performance uds c b NN output for b-tag Mokka LDC01_05Sc w/ conv uds c b NN output for b-tag Results with different configuration are slightly different, but b-tag peformance is almost acceptable with the GLD data.

  9. Summary • We still can not reproduce the Mark’s JER result (~3% worse), but further investigation is kept for future. • Also JER with GLD data is still worse than Mark’s result, but OK for starting analyses of benchmark processes. • FT performance we get with LDC01_05Sc is still slightly different with Sonja. Maybe issue of full tracking ? • FT Performance with GLD data is consistent with Sonja’s result with LDC01_05Sc. • Now we are comparing JER and FT performance among GLD, GLDprime and J4LDC geometries. • Also starting analyses of benchmark processes which use Pandora + LCFIVertex.

  10. Backups

  11. Input variables for flavour tagging with Neural-Net • NumVertices • PTCorrectedMass • RawMomentum • SecondaryVertexProbability • Z0Significance1 • Z0Significance2 • D0Significance1 (zoomed) • D0Significance2 (zoomed) • Z0Significance1 (zoomed) • Z0Significance2 (zoomed) • D0Significance1 • D0Significance2 • DecayLength • DecayLength(SeedToIP) • DecayLengthSignificance • JointProbRPhi • JointProbZ • Momentum1 • Momentum2 • NumTracksInVertices

  12. Black … GLD Red … LDC01_05Sc b-jet events (any number of vertices) DecayLength Significance D0Significance1 D0Significance2 DecayLength DecayLength (SeedtoIP) JointProbZ NumTracks InVertices JointProbRPhi Momentum1 Momentum2 NumVertices SecVertexProb Z0Significance1 PTCorrectedMass RawMomentum D0Significance1 (zoom) D0Significance2 (zoom) Z0Significance1 (zoom) Z0Significance2 (zoom) Z0Significance2

  13. Black … GLD Red … LDC01_05Sc c-jet events (any number of vertices) DecayLength Significance D0Significance1 D0Significance2 DecayLength DecayLength (SeedtoIP) JointProbZ NumTracks InVertices JointProbRPhi Momentum1 Momentum2 NumVertices SecVertexProb Z0Significance1 PTCorrectedMass RawMomentum D0Significance1 (zoom) D0Significance2 (zoom) Z0Significance1 (zoom) Z0Significance2 (zoom) Z0Significance2

  14. Black … GLD Red … LDC01_05Sc uds-jet events (any num. of vertices) DecayLength Significance D0Significance1 D0Significance2 DecayLength DecayLength (SeedtoIP) JointProbZ NumTracks InVertices JointProbRPhi Momentum1 Momentum2 NumVertices SecVertexProb Z0Significance1 PTCorrectedMass RawMomentum D0Significance1 (zoom) D0Significance2 (zoom) Z0Significance1 (zoom) Z0Significance2 (zoom) Z0Significance2

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