Data driven approach to uncertainties #2
Description
Goal: studying optimal uncertainties sigma_R and sigma_Z directly from track fits.
- Generate mono-energetic electrons and reconstruct their trajectories. (ideally using both tracking algos)
- For each track and its each tracker hit, study the distance between the fitted track and the closest point on the track to the tracker hit: Plot the distributions of vertical distances and horizontal distances.
- Compare the distributions obtained from new tracking vs from TrackFit.
- Can the distribution even be approximated using Normal distribution? If so try to estimate sigma_R and sigma_Z
- Study how energy of the electron changes sigma_R and sigma_Z
- Try to study different data dependencies (track length, energy, position of tracker hit on the track...)