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Examples

Download notebookView on GitHubRun when the site was built.

Jupyter notebooks in this section are executed when the documentation is built. Download a notebook from its page to run it yourself.

  • Optimising an einzel lens finds the voltage, gap and aperture of an einzel lens with beamtracer.optimization, against a scan and the thin-lens estimate.
  • Optimising a negative-ion beamlet searches the extraction voltage, the EG aperture and the PG-EG gap of an H⁻ beamlet for the smallest divergence, on a coarse mesh checked against the example’s.
  • The duct traces the neutrals from the end of the traced region through the duct to the port with beamtracer.beamline: the walls hit, the footprint at the port, the reionization in the duct gas, against the closed forms.
  • The grid turns a beamlet traced in 2D into 3D markers with beamline.beamlet_markers and copies it over an aperture grid with its aiming (ApertureGrid): the footprints of a flat and a curved grid along the beamline.
  • The dump pushes the ions left after the neutralizer through the residual-ion dump onto its plates with beamline.FieldRegion, and bends the ions reionized in the duct onto its walls in the stray field.
  • The calorimeter records the power map of a beamlet group on a calorimeter with beamline.Calorimeter and infers the beam’s width and divergence from it as the experiments do, against the markers’ own divergence.
  • The beamline puts the pieces of beamtracer.beamline in a row, from an aimed group of beamlets through the dump and the duct to the port: where the power goes, the footprint at the port, and the neutral markers handed on to freeofcharge.
  • Scripts are complete Python scripts with their plots.
  • Building the docs explains how to add an example and control its output.