Recursive Improvement of a Differentiable Scientific Software Ecosystem

Excerpt

arXiv:2610.04561v1 Announce Type: new Abstract: Differentiable programming connects scientific computation with gradient-based inference, learning and design. Extending these capabilities across a heterogeneous software ecosystem requires specialized effort to implement derivatives, integrate interfaces and evaluate quality. AI coding agents can accelerate this transformation, but translating their capabilities into useful scientific software requires identifying research needs and evaluating ho