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Mar 20, 2026 · Artificial Intelligence

Spectral Division of Labor: How HINTS Blends Jacobi and DeepONet for Uniform PDE Convergence

The HINTS framework exploits the complementary spectral biases of classical Jacobi/Gauss‑Seidel relaxations and DeepONet neural operators, alternating them at a fixed ratio to achieve fast, uniform convergence for both positive‑definite and indefinite PDE systems, and integrates seamlessly with multigrid and Krylov solvers.