GPT Simulation Checklist

Checklist for GPT simulations

Done

Initial electron bunch simulation - centering electron bunch through 1.5m
Ion production rate benchmarked
Maxwellian distribution for ion energies implemented. Initial tests result in ion energy histograms having the correct shape.
Secondary electron energy distribution (from SEDCS) implemented. Initial tests result in SE energy histograms with the correct shape.
Gas species H2, He, CO, and CH4 implemented. H2 and He have the correct SEDCS, CO and CH4 are assumed to have the same SEDCS as H2.
GPT writeremove custom element has been implemented and tested to produce correct output.
Created simulation of "DC" beam pulses that include space charge, the T-cathode electric field, and secondary electron production for H2 gas. "DC" implies the simulation consists of a very long electron (macro-particle) bunch with a user-defined total charge that is uniformly distributed to all electron macro-particles.

The spacecharge3D routine is being benchmarked against analytical theory. An initially stationary ion a certain distance away from a DC electron beam will oscillate about the electron beam due to the electric field of the electron beam. At the same time, the ion will circle the wire due to the magnetic field generated by the electron current.
The secondary electron and ion energy routines are being benchmarked against theory. Although both have been correctly implemented and histograms of secondary electron and ion energies appear to have the correct shape, an analytical calculation to determine whether these histograms are indeed correct and consistent with the probability distribution equations needs to be done.
GPT simulations of DC and pulsed electron beams are being created to show whether ions can remain trapped within the electron beam potential. The total simulation time will need to be rather long to show ions moving within the beam potential
Creating color coding custom element for color coding simulation particles by type.

Create a new custom element that will allow GPT to import vacuum data to use as the local gas density for ionization calculations instead of assuming a constant gas density throughout the simulation.
Derive an approximation for SEDCS for CO and CH4. Kim (et. al.) provide a way to approximate the SEDCS using the so-called Binary Encounter Bethe Model, as the differential oscillator strengths necessary for calculating the SEDCS for CO and CH4 are not available.