This lists some of its unique abilities: https://docs.sciml.ai/DiffEqDocs/stable/ https://docs.sciml.ai/DiffEqDocs/stable/ The routines are sufficiently gener

This lists some of its unique abilities: https://docs.sciml.ai/DiffEqDocs/stable/ https://docs.sciml.ai/DiffEqDocs/stable/ The routines are sufficiently generic, with regard to Julia’s type system, to allow the solvers to automatically compose with other packages and to seamlessly use types other than Numbers. For example, instead of handling just functions Number→Number, you can define your ODE in terms of quantities with physical dimensions, uncertainties, quaternions, etc., and it will just work (for example, propagating uncertainties correctly to the solution¹). Recent developments involve research into the automated selection of solution routines based on the properties of the ODE, something that seems really next-level to me. [1] https://lwn.net/Articles/834571/ https://lwn.net/Articles/834571/