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· 2022 · arXiv 1885.357196

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cs.CE 1

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2026 1

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UNVERDICTED 1

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Robust Matrix-Free Newton-Krylov Solvers via Automatic Differentiation

cs.CE · 2026-05-13 · unverdicted · novelty 6.0

Forward-mode automatic differentiation replaces finite-difference approximations for Jacobian-vector products in JFNK solvers, delivering 2-3 orders of magnitude speedup and lifting minimum solver completion from 42% to 95% across Burgers, radiation diffusion, reaction-diffusion, and nonlinear time-

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  • Robust Matrix-Free Newton-Krylov Solvers via Automatic Differentiation cs.CE · 2026-05-13 · unverdicted · none · ref 20

    Forward-mode automatic differentiation replaces finite-difference approximations for Jacobian-vector products in JFNK solvers, delivering 2-3 orders of magnitude speedup and lifting minimum solver completion from 42% to 95% across Burgers, radiation diffusion, reaction-diffusion, and nonlinear time-