1. Tracking Photon Conversions

2. Existing Track Seeding From pixels –Widely used, but not useful here From stereo silicon layers –Uses layers 5 and 8 (barrel), not enough acceptance

3. First Question: Inside-Out or Outside-In? Both go into same supercluster Supercluster loses particles: more likely for early conversions, asymmetric, bremming. Need to work outside-in Maybe look for 2 nd track inside-out Might be cleaner to work inside-out in a narrow  -window

4. Outside-In: Finding the starting trajectory state Do separately for each basic cluster –Or should I only do once for each supercluster? Assume the conversion happened 1/3 rd of the way in the tracker –Hand-wavingly Bayesian, since we can’t track the outer conversions Assume the track had the full energy of the cluster Calculate where in  to start the track –From the formula for the intersection of two circles Propagate this trajectory to outer layers and look for consistent hits (  < 0.015,  z consistent with IP spread)

5. Outside-In Completing the Seed Next, create a trajectory state from the calo cluster position, the hit position, and the cluster energy. Propagate inwards and look for second hits in the seed (still optimizing  and z windows) If a second point is found, create a new trajectory from a helix of the two tracker points and the calo cluster point. Use the Kalman Filter Updator to add the points to the trajectory, to get combined errors correct. Send seeds off to Kalman track reconstructor. Demand four-hit tracks, hit   <5, one lost hit

6. Outside-In Seeding Current Results

7. Inside-Out Seeding Look for first hits within a narrow  window (0.006) along the supercluster centroid Once a first hit is found, look for 2 nd hits on the next two layers, assuming the track starts at the first point, and has a curvature of half the supercluster energy If a second point is found, make a seed using the curvature that was found, assuming the track was going radially at the first hit. Try to find tracks If only one track is found, try looser cuts to find a second seed with the same vertex

8. Inside-Out Seeding: Two-Way Trajectory Building? Brem showers degrade the measurement Of the calo cluster  What if the cluster  is mismeasured, so I miss the first few points? Tried to make a TrajectoryBuilder that works In both directions, but isn’t quite working yet

9. Inside-Out Results

10. Next Steps Not nearly enough efficiency from either algorithm. Keep refining/debugging the algorithms Find a final combined algorithm: –Different algorithm depending on calo cluster shape? –Implement an outside-in for the first track, then inside-out for the second –Use stereo silicon seeding for early conversions, inside-out for later ones How to reject  0 s? Track  -matching? Can I get two tracks and get an energy match constraint, or a vertex constraint?