I love the `DFBDF`

solver for implicit differential equations, 2 to 4 times faster than `IDA`

from Sundials for my problem and using only half of the memory… And very stable.

Is there any scientific paper about it?

And where is the source code? It should be in GitHub - SciML/OrdinaryDiffEq.jl: High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML) , but there are so many files that refer to this type that I get confused… Is there perhaps a pull request with the initial commit of this solver?

**UPDATE:** This seams to be the initial PR: Implementation of paper "Solving 0 = F (t; y(t); y0(t)) in Matlab" by JunpengGao233 · Pull Request #1452 · SciML/OrdinaryDiffEq.jl · GitHub

This could be a simple benchmark comparing IDA and DFBDF: KiteModels.jl/examples/bench.jl at main · ufechner7/KiteModels.jl · GitHub