Add Confidence Head to Single Track Finder: Proposal A: Stop-or-Go Confidence Head (Event Level)

[anveshmy]

Proposal A: Stop-or-Go Confidence Head (Event Level)

Location:

• QTracker_training/models/TrackFinder.py in dev branch

Add an additional output head to the existing single track finder model that predicts a confidence score indicating whether the current track proposal is valid.

Target Definition:

• Binary confidence indicator:
  • 1: There is at least one valid track present in the event
  • 0: There are no remaining tracks in the event

Training Strategy:

• Update the dataset to support a variable number of ground truth tracks per event (0, 1, 2, ...).
• Ground truth confidence label:
  • 1 if number of GT tracks >= 1
  • 0 if number of GT tracks = 0
• Use Binary Cross Entropy (BCE) loss for the confidence head.
• Carefully weight the confidence loss relative to existing losses to preserve single track reconstruction performance.

Evaluation Requirements:

• Validate that single track performance (residuals, momentum, q-metric) is not degraded.
• Evaluate confidence head quality using:
  • Accuracy
  • Precision and recall
  • Correlation with reconstruction quality and residuals