Directional derivatives of tempered distributions #
Mathlib defines the directional derivative of a tempered distribution by duality,
(∂_m f) u = f (-∂_m u). Since directional derivatives of Schwartz functions commute
(SchwartzMap.lineDerivOp_comm), so do those of tempered distributions. On the plane ℂ the
Laplacian of a tempered distribution is then ∂₁² f + ∂₂² f, with ∂₁ and ∂₂ the derivatives
along 1 and I, as for Schwartz functions (SchwartzMap.laplacian_eq_lineDerivOp_one_I). These
are the identities needed to compute compositions of constant-coefficient first-order operators
on tempered distributions. Directional differentiation of the tempered distribution given by a
Schwartz function also commutes with a continuous real-linear map applied to its values.
Main results #
TemperedDistribution.lineDerivOp_comm:∂_v ∂_w f = ∂_w ∂_v f.TemperedDistribution.laplacian_eq_lineDerivOp_one_I:Δ f = ∂₁² f + ∂₂² fonℂ.TemperedDistribution.lineDerivOp_toTemperedDistributionCLM_postcompCLM:∂_v (L ∘ f) = L ∘ ∂_v ffor a Schwartz functionfviewed as a tempered distribution.
Directional derivatives of tempered distributions commute.
The Laplacian on the plane in coordinates: Δ f = ∂₁² f + ∂₂² f for a tempered
distribution f on ℂ, where ∂₁ and ∂₂ differentiate along 1 and I.
Directional differentiation of the tempered distribution given by a Schwartz function commutes with a continuous real-linear map applied to the values of the function.