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EF with simple multi-particle states. Vishnu V. Zutshi NIU/NICADD. Hadron Position Resolution. Since Eflow invariably involves associating clusters near an extrapolated track … How to do this in a digital calorimeter ? Study this using charged pions
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EF with simple multi-particle states Vishnu V. Zutshi NIU/NICADD
Hadron Position Resolution • Since Eflow invariably involves associating clusters near an extrapolated track … • How to do this in a digital calorimeter ? • Study this using charged pions • Resolution is defined w.r.t. the MC extrapolated position
10 GeV charged pions Energy weighted unweighted Density weighted
“Density” • Need a hierarchy in the absence of an energy measurement • Clumpiness of the surrounding • A simple-minded realization of this used here: di = S (1/dRij) where dRij is the angular distance between cell ‘i’ and cell ‘j’
10 GeV p unweighted Measured relative to the energy weighted resolutions Cell area at first layer=0.64cm2 Density weighted
10 GeV p unweighted Measured relative to the energy weighted resolutions Cell area at first layer=4cm2 Density weighted
10 GeV p unweighted Measured relative to the energy weighted resolutions Cell area at first layer=6cm2 Density weighted
10 GeV p unweighted Measured relative to the energy weighted resolutions Cell area at first layer=9cm2 Density weighted
10 GeV p unweighted Measured relative to the energy weighted resolutions Cell area at first layer=12cm2 Density weighted
10 GeV p unweighted Measured relative to the energy weighted resolutions Cell area at first layer=16cm2 Density weighted
2GeV Photons maxima maxima maxima
Clustering • Local ‘density’ maxima chosen as seed clusters • Membership of each cell in the seed clusters decided with a distance function • Calculate centroids • Iterate steps 2 and 3 till distortion is below some threshold Could be unique or shared
Parameters • Cell thresholds • How many layers to lump together • Neighborhood for maxima search • Minimum no. of layers hit • Neighborhood for membership • Proto-cluster definition • Uniqueness of membership
10 GeV p0 Density weighted q-f High asymmetry
10 GeV p0 Density weighted q-f Medium asymmetry
10 GeV p0 Density weighted q-f Low asymmetry
10 GeV p0 Density weighted q-f Low asymmetry
10 GeV p0 Recon. energy Recon. mass 18%
10 GeV p0 Recon. energy Recon. mass
Energy asymmetry A = abs(Eg1 – Eg2)/(Eg1 + Eg2)
S+ pp0 p Density weighted q-f p0
S+ pp0 p Density weighted q-f
S+ pp0 Eflow Cal only E/Egen
S+ np+ p+ EMCal n HCal p
S+ np+ n EMCal p HCal
S+ np+ Not reliable due to noncompensation recE (p) genE (p)
S+ np+ • Get the e/pi for the SD detector • Scale the MC truth with that function • Take the ratio of the reconstructed pion energy with the scaled MC truth • This should have a mean of 1.0 (with an atrocious resolution) if things are working ok
Summary/Outlook • A first pass clustering/track association algorithm exists applicable to EM/HAD, both analog/digital • Encouraging results for multiparticle events • More detailed study to expand and enhance (for instance particle id) • Move to jets • Feedback into calorimeter design