Mechanism failed
2026
Closure-Decorrelation Memory Scheduler
Choose the neural operator's input-history length from the measured correlation time of the unresolved closure signal produced by coarse-graining. This avoids under-memory, which causes systematic closure error, and over-memory, which increases attention cost and can destabilize training. The same diagnostic can drive adaptive memory truncation across physical regimes.
Paper: Flux-form spatiotemporal neural operators for coarse-grained dynamics of multiscale PDEs
arXiv:2608.18148