Results with new neural network that incudes raster x and y input neurons. Have not yet incuded a z-position reconstruction using the tracker. This introduces a tracker geometry dependence and I still do not understand why I have to move the tracker close to get consistent results.
It is worth noting that the delta-Y target does not use the tracker. It only uses bigcal and a track-propagator, however, it seems to be able to see a positron peak. The red curv in the "positron_id2" plots is a cut on the tracker delta-Y while the blue is a cut on the target delta-Y (which does not use tracker).
The positron_id6 animatied gifs show the improvement in the tracker delta-Y when the detector is moved forward. The best position is somewhere around 49.5 cm. At this position the peaks in delta_Y tracker are aligned and the peak moves to the left with increasing energy.
In the tracker cut there remains a problem with rastered beam in that the spread at the tracker becomes large.
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To do: