Augmenting momentum resolution with well tuned probability distributions
  The realistic probability distributions of a previous article are applied to the reconstruction of tracks in constant magnetic field. The complete forms and their schematic approximations produce excellent momentum estimations, drastically better than standard fits. A simplified derivation of one of our probability distributions is illustrated. The momentum reconstructions are compared with standard fits (least squares) with two different position algorithms: the eta-algorithm and the two-strip center of gravity. The quality of our results are expressed as the increase of the magnetic field and signal-to-noise ratio that overlap the standard fit reconstructions with ours best distributions. The data and the simulations are tuned on the tracker of a running experiment and its double sided microstrip detectors, here each detector side is simulated to measure the magnetic bending. To overlap with our best distributions, the magnetic field must be increased by a factor 1.5 for the least squares based on the eta-algorithm and 1.8 for the two-strip center of gravity for the low noise side, and 1.8 and 2.0 for the high noise side. The signal-to-noise ratio must be increased by 1.6 for the low noise side and 2.2 for the high noise side (eta-algorithms). The fits, built on the positioning with the center of gravity, are not modified by a reduction of the signal-to-noise ratio.} 
Gregorio Landi, Giovanni E. Landi
physics.ins-det