Transcript Slide 1

Highlights of the SiD-Iowa
Particle Flow Algorithm
• Previous (LOI) version of PFA was for up to 500 GeV collider energy.
– Even at 500 GeV performance sufficient, but could be improved.
• Established a ground-up approach:
– Targeted diagnostics for each piece of the algorithm to evaluate each piece.
• Photon reconstruction:
– Once photons are reconstructed, the hits are taken out from use.
– An anti veto is in place which checks “photon-hits” for fakes and treats them
as hadrons.
• Sub-cluster categories (clump purity)
– Clump (sub-cluster) purity was not good enough: make smaller (don’t use NN).
• Linking probabilities of sub-clusters (discriminating variables, likelihood)
– Use identical clustering for linking probability and shower reconstruction.
– Add likelihood method with several discriminating variables.
• Shower reconstruction (two passes):  IN PROGRESS
– Form a high purity skeleton with all tracks treated similarly.
– Add hits in second pass with adjudication between nearby showers.
Highlights of the SiD-Iowa
Particle Flow Algorithm
Energy weighted Purity (clumps)
Energy fraction (clumps)
baseline
new
baseline
new
ECAL
90%
94%
15.3%
16.2%
HCAL
80%
87%
32.2%
29.0%
Overall
84%
90%
47.5%
45.2%
Clump
reconstruction
performance
Variables in likelihood
used for linking
Discrimination improves significantly when angles b and c are added in the likelihood