CasEm: A Cascade Architecture for Long-Horizon Neural Emulation
A finite-horizon error bound is derived that clarifies three factors and use empirical diagnostics to guide subsystem selection in Cascaded Emulation, a one-way rollout architecture that augments an existing full-state backbone with an independently evolving model of physically specified aggregates.