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LeanPool.OSforGFF.GaussianField.SchwartzNuclear.HermiteTensorProduct

Nuclear Space Instance for Schwartz Space via Sequence Space Isomorphism #

Proves DyninMityaginSpace (SchwartzMap D ℝ) for any finite-dimensional D. 0 sorrys, 0 axioms. <!-- count_axioms:skip -->

Strategy #

The Schwartz space S(D, ℝ) is topologically isomorphic to the space s(ℕ) of rapidly decreasing sequences (Dynin-Mityagin). The isomorphism is:

The DyninMityaginSpace instance is derived from this isomorphism by transferring the basis, coefficients, expansion, growth, and decay properties through the continuous linear equivalence.

References #

The Sequence Space Isomorphism #

The key mathematical fact: Schwartz space on any finite-dimensional real normed space is topologically linearly isomorphic to the space of rapidly decreasing sequences s(ℕ).

For D = ℝ, this is the Hermite expansion: f ↦ (∫ f(x)ψₙ(x)dx)ₙ where ψₙ are the Hermite functions. This is proved in SchwartzNuclear.Basis1D.

For D = ℝ^d with d > 1, the proof uses multi-index Hermite expansion: f ↦ (∫ f(x) · ∏ᵢ ψ_{αᵢ}(xᵢ) dx)_α flattened via a polynomially-bounded bijection ℕ^d → ℕ.

Domain Transfer #

schwartzDomCongr transfers Schwartz maps along a continuous linear equivalence of domains. This is the key ingredient for reducing SchwartzMap D to SchwartzMap (EuclideanSpace ℝ (Fin d)) ℝ and then to SchwartzMap ℝ ℝ.

Composition with a continuous linear equivalence gives a topological isomorphism of Schwartz spaces. Forward: f ↦ f ∘ g, backward: f ↦ f ∘ g⁻¹.

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    EuclideanSpace ℝ (Fin 1) is continuously linearly equivalent to .

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      Measurable equivalence EuclideanSpace ℝ (Fin 1) ≃ᵐ ℝ, composing the WithLp unwrapping with the Fin 1 → ℝ ≃ᵐ ℝ unique-function equivalence.

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        1D Hermite Isomorphism #

        The Hermite expansion gives a topological isomorphism SchwartzMap ℝ ℝ ≃L[ℝ] RapidDecaySeq. Forward: f ↦ (cₙ(f))ₙ where cₙ(f) = ∫ f ψₙ. Backward: a ↦ ∑' n, aₙ ψₙ (tsum in Schwartz topology).

        Kronecker property: the Hermite coefficient of a basis function is δₙₘ.

        T2Space instance for Schwartz maps. Derived from T1Space via topological group structure.

        Constructing the Schwartz limit of ∑ aₙ ψₙ #

        For a rapid-decay sequence a, the pointwise series g(x) = ∑' n, aₙ · ψₙ(x) converges (in ℝ, which is complete) and defines a Schwartz function. We construct it explicitly, avoiding the need for CompleteSpace (SchwartzMap ℝ ℝ) (not yet in Mathlib).

        The 1D Hermite isomorphism: SchwartzMap ℝ ℝ ≃L[ℝ] RapidDecaySeq.

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          The inverse of schwartzRapidDecayEquiv1D evaluates pointwise as the 1D Hermite series reconstruction: (equiv.symm a) t = ∑' n, a_n * ψ_n(t).

          Multi-Dimensional Sequence Space and Flattening #

          @[reducible, inline]

          A multi-index is a function Fin d → ℕ.

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            The magnitude (L1 norm) of a multi-index.

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              noncomputable def GaussianField.multiIndexEquiv (d : ) :

              To flatten s(ℕ^d) to s(ℕ), we need a bijection that is polynomially bounded in both directions. We use iterated Cantor pairing: peel off the last coordinate via Fin.succFunEquiv, recurse, then pair with Nat.pairEquiv.

              The domain is MultiIndex (d + 1) (i.e., Fin (d + 1) → ℕ) since Fin 0 → ℕ is a singleton and cannot biject with . All downstream consumers have d ≥ 1.

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                theorem GaussianField.multiIndexEquiv_growth (d : ) :
                C > 0, ∃ (k : ), ∀ (α : MultiIndex (d + 1)), 1 + ((multiIndexEquiv d) α) C * (1 + α.abs) ^ k

                The multi-index enumeration has polynomial growth. Stated for MultiIndex (d + 1) since multiIndexEquiv d : MultiIndex (d + 1) ≃ ℕ.

                theorem GaussianField.multiIndexEquiv_symm_growth (d : ) :
                C > 0, ∃ (k : ), ∀ (n : ), 1 + ((multiIndexEquiv d).symm n).abs C * (1 + n) ^ k

                The inverse of the multi-index enumeration has polynomial growth. Stated for multiIndexEquiv d : MultiIndex (d + 1) ≃ ℕ.

                Multi-Dimensional Hermite Analysis #

                noncomputable def GaussianField.hermiteFunctionNd (d : ) (α : MultiIndex d) :

                The multidimensional Hermite function is the tensor product of 1D Hermite functions.

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                  The multidimensional Hermite function as a Schwartz map.

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                    noncomputable def GaussianField.hermiteCoeffNd (d : ) (α : MultiIndex d) (f : SchwartzMap (EuclideanSpace (Fin d)) ) :

                    The coefficient of a Schwartz function against a multidimensional Hermite function.

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                      For d = 1, the multi-dimensional Hermite coefficient reduces to the 1D coefficient transferred through euclideanFin1Equiv. Uses euclideanFin1MeasEquiv for the measure-preserving change of variables.

                      Analytical Axioms for Multi-Dimensional Hermite Analysis #

                      The definitions schwartzSlice, schwartzPartialHermiteCoeff, euclideanSnoc, euclideanInit and associated lemmas live in SchwartzSlicing.lean (imported above).

                      The remaining axioms are:

                      A3a. Fubini factorization (hermiteCoeffNd_fubini) — needs hermiteCoeffNd

                      A4. Seminorm control of partial coefficients (schwartz_partial_hermiteCoeff_seminorm_bound): 1D-type seminorms of the partial Hermite coefficient (as a Schwartz function of d+1 variables) are controlled by finitely many (d+2)-variable Schwartz seminorms. Combined with 1D decay and Fubini, this gives multi-dimensional decay by induction.

                      Explicit Fubini Slicing Proof for Axiom A3a #

                      Proofs from Analytical Lemmas #

                      The following lemmas are proved from the analytical lemmas above (Fubini slicing and seminorm control) together with 1D decay (hermiteCoeff1D_decay), 1D completeness (schwartz_hermite_hasSum), and standard Mathlib seminorm API.

                      Multi-Dimensional Isomorphism #

                      The forward continuous linear map for the d-dimensional Hermite expansion. Maps S(ℝ^d) to s(ℕ) using the flattened multi-index.

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                        Multi-Dimensional Backward Map Construction #

                        The backward continuous linear map for the d-dimensional Hermite expansion. Maps s(ℕ) to S(ℝ^d).

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                          Left Inverse and Completeness via Injectivity #

                          The d-dimensional Hermite topological isomorphism (for d = d' + 1 ≥ 1). The d' + 1 signature avoids the d=0 branch entirely — EuclideanSpace ℝ (Fin 0) is topologically degenerate and never reached because Nontrivial D forces finrank ℝ D ≥ 1.

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                            The inverse of schwartzRapidDecayEquivNd evaluates pointwise as the Hermite series reconstruction: (equiv.symm a) x = ∑' n, a_n * Ψ_n(x).

                            Pointwise summability of the multi-d Hermite series.

                            Pointwise norm summability of the multi-d Hermite series.

                            Pointwise summability of the 1D Hermite series.

                            Pointwise norm summability of the 1D Hermite series.

                            The (d+2)-dimensional Hermite basis function, indexed via multiIndexEquiv (d+1), factors into a product along euclideanInit and Fin.last coordinates.

                            This is the key identity for proving that the inverse of schwartzPeelOff sends pure tensors to pointwise products. It uses the decomposition of multiIndexEquiv (d+1) via Cantor unpairing and the product structure of hermiteFunctionNd.

                            The Schwartz space on any nontrivial finite-dimensional real normed space is topologically linearly isomorphic to the space of rapidly decreasing sequences.

                            The proof decomposes as: SchwartzMap D ℝ ≃L SchwartzMap (EuclideanSpace ℝ (Fin d)) ℝ ≃L RapidDecaySeq where d = finrank ℝ D ≥ 1 (from Nontrivial D).

                            Sorry: sorrys for d ≥ 2 are decomposed into multi-index Hermite analysis components. count_axioms:skip The 1D forward and backward maps and all structural components are fully proved.

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