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subK_preserved

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Analysts of discrete fluid equations cite this result to show that the sub-Kolmogorov bound on the gradient maximum survives a single time step of the lattice Navier-Stokes evolution under the stated update inequality. The theorem removes one external hypothesis from the regularity induction on the RS lattice. Its term proof applies the gradient-nonincreasing property and order transitivity after parameter rewriting.

claimLet $data$ be a one-step datum with positive viscosity $nu$, lattice spacing $h$, time step $dt$, nonnegative gradient maximum $G$, and advection bound $A$. Suppose the sub-Kolmogorov condition holds for $data$. Let $G'$ satisfy $G' ≤ G · (1 + dt · (A - nu/h²)). Let $data'$ be a one-step datum with the same viscous rate $nu/h²$ and gradient maximum $G'$. Then $data'$ satisfies the sub-Kolmogorov condition.

background

OneStepData packages the parameters for a single discrete Navier-Stokes time step on a finite lattice: positive viscosity $nu$, spacing $h$, time step $dt$, current gradient maximum, and advection bound. The sub-Kolmogorov condition is the predicate on this datum that the module shows is self-improving. The module documentation states: 'This module proves that the sub-Kolmogorov condition is self-improving under the discrete Navier--Stokes evolution on the RS lattice, eliminating it as an external hypothesis and making the lattice regularity result fully unconditional.'

proof idea

The proof is a one-line term-mode wrapper. It unfolds the subKolmogorov predicate on the new datum, rewrites the gradient maximum and viscous rate via the supplied equalities, then applies the gradient_nonincreasing lemma to obtain the bound on the updated maximum and composes it with the original hypothesis via le_trans.

why it matters in Recognition Science

This supplies the one-step preservation needed for the inductive propagation of the sub-Kolmogorov condition over arbitrary time steps, removing it as an external hypothesis in the lattice regularity theorem. It advances the discrete maximum principle for Navier-Stokes on the RS lattice and aligns with the self-improving regularity developed in the module. The surrounding documentation references the spectral gap from Proposition III.1 in Thapa & Washburn (GCIC, J. Math. Phys. 2026).

scope and limits

formal statement (Lean)

  98theorem subK_preserved (data : OneStepData)
  99    (hsubK : data.subKolmogorov)
 100    (newGradMax : ℝ)
 101    (h_update : newGradMax ≤
 102      data.gradMax * (1 + data.dt * (data.advectionBound - data.viscousRate)))
 103    (newData : OneStepData)
 104    (h_same_params : newData.viscousRate = data.viscousRate)
 105    (h_new_grad : newData.gradMax = newGradMax) :
 106    newData.subKolmogorov := by

proof body

Term-mode proof.

 107  unfold OneStepData.subKolmogorov
 108  rw [h_new_grad, h_same_params]
 109  exact le_trans (gradient_nonincreasing data hsubK newGradMax h_update) hsubK
 110
 111/-! ## Inductive Propagation -/
 112
 113/-- The sub-Kolmogorov condition propagates through arbitrarily many
 114time steps by induction. -/

depends on (6)

Lean names referenced from this declaration's body.