Differentiate the Solver, Not the Equation: Reverse-Sweep Adjoints for Block Implicit Simulation
Differentiable simulation is a key component in learning, control, and inverse problems, where gradients through nonlinear implicit solvers are required. Existing approaches either rely on unrolled automatic differentiation, whose memory grows with solver depth, or on equation-level implicit differentiation, which asse...