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Performant numerical solving of differential equations is required forlarge-scale scientific modeling. In this manuscript we focus on two questions:(1) how can researchers empirically verify theoretical advances andconsistently compare methods in production software settings and (2) how canusers (scientific domain experts) keep up with the state-of-the-art methods toselect those which are most appropriate? Here we describe how the confederatedmodular API of DifferentialEquations.jl addresses these concerns. We detail thepackage-free API which allows numerical methods researchers to readily utilizeand benchmark any compatible method directly in full-scale scientificapplications. In addition, we describe how the complexity of the method choicesis abstracted via a polyalgorithm. We show how scientific tooling built on topof DifferentialEquations.jl, such as packages for dynamical systemsquantification and quantum optics simulation, both benefit from this structureand provide themselves as convenient benchmarking tools.

Confederated Modular Differential Equation APIs for Accelerated Algorithm Development and Benchmarking