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IndisputableMonolith.NavierStokes.DiscreteNSOperator

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DiscreteNSOperator defines the concrete discrete incompressible Navier-Stokes operator on the RS lattice, packaging finite-difference primitives and the full evolution surface. Researchers on the J-cost monotonicity program cite it to obtain an explicit operator against which transport cancellation and RCL pair budgets are measured. The module is purely definitional and assembles its objects from the imported DiscreteVorticity and StretchingPairs bookkeeping.

claimThe module supplies the discrete NS operator together with its auxiliary fields, including the maximum absolute forward difference $M = max |Δ^+ u|$ taken over all velocity components and lattice directions.

background

The module operates inside the Recognition Science lattice setting for discrete Navier-Stokes. It imports DiscreteVorticity, whose doc states it packages finite vorticity fields on a lattice window together with total, RMS and normalized amplitudes plus transport/viscous/stretching contribution fields. It also imports StretchingPairs, whose doc isolates paired stretching/compression events and the exact Recognition Composition Law balance for such pairs. Local definitions include Axis, ScalarField, VectorField, LatticeTopology, forwardDiff, backwardDiff, scalarLaplacian, vectorLaplacian, divergence, advection and conservativeTransportField.

proof idea

this is a definition module, no proofs

why it matters in Recognition Science

The module supplies the concrete operator surface required by JcostMonotonicity (which derives transport cancellation from conservative incompressible flux and bounds the stretching term by the operator's own RCL pair budget) and by DiscreteMaximumPrinciple (which proves the sub-Kolmogorov condition is self-improving). It also feeds VortexStretching, which closes the three analytic gaps using the cited papers P1-P3.

scope and limits

used by (3)

From the project-wide theorem graph. These declarations reference this one in their body.

depends on (2)

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declarations in this module (33)