Speaker
Hayden Klassen
(TRIUMF; University of Toronto)
Description
We present an extensible Python-based numerical solver for stiff source-driven reaction-diffusion systems. It is currently being utilized to model the temporal and spatial evolution of liquid-phase N₂-H₂-H₂O radiolysis systems by considering Fickian diffusion, mass-action kinetics, and radiolytic production. The generalized design of the solver also makes it adaptable for modeling molecular cloud astrochemistry, dark matter and neutrino detectors, and electroweak baryogenesis.
| What area of study best describes your talk? | Other (specify below) |
|---|---|
| If you answered 'Other', please provide the study area. | Computational Physics |
Author
Hayden Klassen
(TRIUMF; University of Toronto)
Co-authors
Susan Beale
(SFU)
Prof.
Christopher Charles
(TRIUMF)