Abstract
The purpose of this work was to investigate the accuracy and efficiency of electron transport in GEANT4 with and without a magnetic field present. Fano cavity simulations were performed in GEANT4 version 10.02 and 10.04.p01 using two multiple scattering (MSC) algorithms for two slab and one pseudo-ion chamber geometries. An iterative approach was used to optimize the transport parameters to obtain agreement with theory. Similar to previous works, the step lengths had to be severely restricted to obtain agreement with theory when using the Urban MSC model in GEANT4 v10.02. Using the Goudsmit–Saunderson MSC model with the UseSafetyPlus MSC step limitation in GEANT4 v10.04.p01 limited the maximum discrepancy from theory to 0.5%. Minor adjustments to the transport parameters were needed to obtain agreement within 0.16% of theory for all simulation configurations without a magnetic field present. The maximum deviation from theory was within 2% for all simulation configurations in the presence of a magnetic field except for two setups that exhibited discrepancies of up to 10.8%. This anomalous behavior was mitigated by forcing single scattering within the detector gas volume. Further adjustments to the transport parameters resulted in agreement with theory at the 0.21% level. Agreement with theory in the absence of a magnetic field can be obtained without significantly restricting the step size if the Goudsmit–Saunderson MSC model is used with the UseSafetyPlus MSC step limitation in GEANT4 v10.04.p01. The large discrepancies from theory observed for two simulation setups with a magnetic field present were attributed to an issue with energy loss sampling over a step when strict magnetic field transport parameters are used. This problem can be corrected by forcing single scattering within the detector gas volume; however, more work is needed to identify the cause of this anomalous behavior. This work has shown that GEANT4 can perform accurate electron transport with and without a magnetic field present without applying significant step-size reductions.
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