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module module moderate

IndisputableMonolith.NavierStokes.FourierExtraction

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The FourierExtraction module composes extraction steps at arbitrary m to force convergence of the first m Fourier columns in a Navier-Stokes setting. Researchers deriving fluid equations from the Recognition forcing chain would cite it when assembling mode-by-mode limits. The module collects a chain of monotonicity and tendsto lemmas to build the extraction inductively.

claimComposed extraction at step $m$ ensures Fourier columns indexed $0$ through $m$ converge.

background

The module lives inside the NavierStokes domain of Recognition Science and imports only Mathlib for analysis. It introduces tendsto_comp_strictMono (composition of strict monotonic maps with limits), strictMono_id_le (identity is strictly monotone), bounded_subseq_tendsto (bounded sequences admit convergent subsequences), and the family CE, CL, LE together with their zero, succ, strictMono and conv_at variants. These supply the inductive scaffolding for column-wise convergence under the Recognition Composition Law.

proof idea

This is a definition module, no proofs. The structure assembles the listed monotonicity and limit lemmas into an inductive extraction that reaches any finite column index m.

why it matters in Recognition Science

The module supplies the convergence engine required by downstream Navier-Stokes claims that apply the unified forcing chain (T0-T8) and the Recognition Composition Law to fluid modes. It closes the gap between the phi-ladder and concrete Fourier extraction without invoking the mass formula or Berry threshold.

scope and limits

declarations in this module (19)