Gradient estimate for the heat flow:
ProvedNavierStokes.lintegral_gradNormSq_heatFlow_leanalysisheat-equationnavier-stokespartial-differential-equations
Let , , and let be measurable. Then the Jacobian of the heat flow satisfies the smoothing estimate
where is NavierStokes.gradNormSq and both sides are lower Lebesgue integrals in (trivially true if ). In semigroup language this is , the basic parabolic smoothing estimate used in Kato's contraction argument (Kato 1984, §2). The proof: (differentiation under the integral, justified by Gaussian domination), the pointwise Jensen inequality , Tonelli, and the bound obtained from and the Gaussian integral. The constant is not optimal. Formalization note. gradNormSq is built from Mathlib's fderiv, which is where a function is not differentiable; the theorem is nevertheless a genuine estimate because is differentiable for .
Preamble
import Definitions.Def_NavierStokes_Mild import Mathlib open MeasureTheory Real
Formal statement
namespace NavierStokes
theorem lintegral_gradNormSq_heatFlow_le {ν t : ℝ} (hν : 0 < ν) (ht : 0 < t) (f : Vec 3 → Vec 3)
(hf : AEStronglyMeasurable f volume) :
∫⁻ x, ENNReal.ofReal (gradNormSq (heatFlow ν t f) x) ≤
ENNReal.ofReal (24 / (ν * t)) * ∫⁻ x, ‖f x‖ₑ ^ 2 := by sorry
end NavierStokesSource
Standard heat-kernel facts on ℝ³; see e.g. L. C. Evans, Partial Differential Equations, 2nd ed., AMS GSM 19 (2010), §2.3.1 (fundamental solution, Lemma p. 46: unit mass) and §2.3.3; for the Kato route: T. Kato, Math. Z. 187 (1984), §2 eq. (2.1)–(2.3) (semigroup estimates ‖∇e^{tΔ}f‖₂ ≤ C t^{-1/2}‖f‖₂). Mission context: Prove2Me mission 'Formalize Navier-Stokes', child NavierStokes.exists_mildSolutionOn_Ico (Kato local existence).