Beamline neural network reconstruction training #171
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This was referenced Jun 25, 2025
veprbl
reviewed
Jul 4, 2025
Co-authored-by: Dmitry Kalinkin <dmitry.kalinkin@gmail.com>
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Briefly, what does this PR introduce?
Trains a neural network to reproduce the momentum of the particle at the origin based on the position and direction that it exits the B2eR magnet into the Tagger drift volume.
Produces plots which demonstrate the reconstruction limits from the beam divergence and optics without worrying about the effects of the detector reconstruction. This might introduce some systematic error in the reconstruction later.
Shares the simulation from #167
Replacing the previous onnx training #123 which relied on reconstructed tagger tracks.
What kind of change does this PR introduce?
Please check if this PR fulfills the following:
Does this PR introduce breaking changes? What changes might users need to make to their code?
No
Does this PR change default behavior?
Adds a new benchmark to train a new onnx neural network to reconstruct electron momentum through beamline magnetic optics.