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Anderson4D.Parametrix.IdentityRightKernelSymmetry

Orderwise symmetry of the random parametrix #

The closed detIntegrand is deliberately right-oriented: an extracted interval replaces its right boundary edge. Consequently it is not pointwise invariant under chain reversal. This module instead uses the graded resolvent-word expansion forced by Proposition 3.4. Every word kernel is manifestly transposed by reversing the word and all integration coordinates; reversal is a bijection on compositions of the total order.

Graded resolvent words #

noncomputable def Anderson4D.PartialPairing.renormWordWeight (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (d : ℕ) (z : T4) (ω : M.Ω) :

Vertex weight of a graded resolvent word. A block of size 1 is one mollified-noise insertion. A positive even block is a scalar counterterm insertion; all other block sizes carry zero weight.

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    noncomputable def Anderson4D.PartialPairing.renormWordIntegrandOnTuple (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (word : List ℕ) (xt : Fin (word.length + 2) → T4) (ω : M.Ω) :

    A finite graded word evaluated on a full chain tuple.

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      noncomputable def Anderson4D.PartialPairing.renormWordKernel (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (word : List ℕ) (x y : T4) (ω : M.Ω) :

      The spatial multiple integral attached to one graded word.

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        Reversal of a word's vertex indices, including the harmless cast between the propositionally equal list lengths.

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          Measure-preserving reversal of the integration variables #

          Reverse the integration-variable coordinates of a graded word.

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            Reversing all internal coordinates and swapping the two external points reverses the assembled full chain.

            The left endpoint of a reversed edge is the reversal of the original edge's right endpoint.

            The right endpoint of a reversed edge is the reversal of the original edge's left endpoint.

            Pointwise symmetry of a graded word #

            theorem Anderson4D.PartialPairing.renormWordIntegrandOnTuple_reverse_assemble (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (word : List ℕ) (x y : T4) (v : Fin word.length → T4) (ω : M.Ω) :

            Reversing a word and all chain coordinates transposes its integrand.

            theorem Anderson4D.PartialPairing.renormWordKernel_reverse (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (word : List ℕ) (x y : T4) (ω : M.Ω) :
            renormWordKernel M ρ lam ε word x y ω = renormWordKernel M ρ lam ε word.reverse y x ω

            Every graded resolvent-word kernel is transposed by reversing the word. No integrability hypothesis is needed because the change of variables is measure preserving.

            theorem Anderson4D.PartialPairing.renormWordKernel_nil (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (x y : T4) (ω : M.Ω) :
            renormWordKernel M ρ lam ε [] x y ω = greenFn (x - y)

            The empty graded word is the free Green kernel.

            Composition sum of all graded words #

            noncomputable def Anderson4D.PartialPairing.gradedParametrix (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (n : ℕ) (x y : T4) (ω : M.Ω) :

            Sum of all graded resolvent words of total order n. Positivity of composition blocks excludes a spurious degree-zero vertex.

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              theorem Anderson4D.PartialPairing.gradedParametrix_symmetric (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (n : ℕ) (x y : T4) (ω : M.Ω) :
              gradedParametrix M ρ lam ε n x y ω = gradedParametrix M ρ lam ε n y x ω

              The complete graded-word sum is symmetric: composition reversal is a bijection and transposes every individual word.

              theorem Anderson4D.PartialPairing.gradedParametrix_zero (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (x y : T4) (ω : M.Ω) :
              gradedParametrix M ρ lam ε 0 x y ω = greenFn (x - y)

              The order-zero graded sum is the free Green kernel.

              Head decomposition of graded words #

              theorem Anderson4D.PartialPairing.integral_finSucc_zero {n : ℕ} (f : (Fin (n + 1) → T4) → ℝ) (hf : MeasureTheory.Integrable f (MeasureTheory.Measure.pi fun (x : Fin (n + 1)) => paperMeasure)) :
              (∫ (v : Fin (n + 1) → T4), f v ∂MeasureTheory.Measure.pi fun (x : Fin (n + 1)) => paperMeasure) = ∫ (z : T4), ∫ (v : Fin n → T4), f (Fin.cons z v) ∂MeasureTheory.Measure.pi fun (x : Fin n) => paperMeasure ∂paperMeasure

              Fubini after separating the zero-th coordinate of a finite tuple. Only integrability of the original joint function is assumed; no pointwise integrability of the sections is required.

              The outer integral of the zero-th-coordinate sections is integrable whenever the original joint function is integrable.

              theorem Anderson4D.PartialPairing.assemble_cons_succ (word : List ℕ) (x y z : T4) (v : Fin word.length → T4) (i : Fin (word.length + 2)) :
              assemble x y (Fin.cons z v) i.succ = assemble z y v i

              Dropping the first variable from an assembled nonempty chain turns the old external left point into that first variable.

              theorem Anderson4D.PartialPairing.renormWordIntegrandOnTuple_cons (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (d : ℕ) (word : List ℕ) (x y z : T4) (v : Fin word.length → T4) (ω : M.Ω) :
              renormWordIntegrandOnTuple M ρ lam ε (d :: word) (assemble x y (Fin.cons z v)) ω = greenFn (x - z) * renormWordWeight M ρ lam ε d z ω * renormWordIntegrandOnTuple M ρ lam ε word (assemble z y v) ω

              A nonempty word integrand separates into its first edge, first vertex weight, and the remaining word integrand.

              def Anderson4D.PartialPairing.RenormWordIntegrable (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (word : List ℕ) (x y : T4) (ω : M.Ω) :

              Joint integrability of one flat graded-word kernel. This is the right hypothesis for Fubini: section integrability is then needed only almost everywhere and is supplied by integral_prod.

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                theorem Anderson4D.PartialPairing.renormWordKernel_cons (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (d : ℕ) (word : List ℕ) (x y : T4) (ω : M.Ω) (hflat : RenormWordIntegrable M ρ lam ε (d :: word) x y ω) :
                renormWordKernel M ρ lam ε (d :: word) x y ω = ∫ (z : T4), greenFn (x - z) * renormWordWeight M ρ lam ε d z ω * renormWordKernel M ρ lam ε word z y ω ∂paperMeasure

                A flat nonempty word kernel is its first weighted Green convolution with the remaining word kernel.

                theorem Anderson4D.PartialPairing.integrable_renormWordHeadConvolution (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (d : ℕ) (word : List ℕ) (x y : T4) (ω : M.Ω) (hflat : RenormWordIntegrable M ρ lam ε (d :: word) x y ω) :
                MeasureTheory.Integrable (fun (z : T4) => greenFn (x - z) * renormWordWeight M ρ lam ε d z ω * renormWordKernel M ρ lam ε word z y ω) paperMeasure

                Joint flat-word integrability implies integrability of the first weighted Green convolution with the tail kernel.

                Compositions classified by their first block #

                def Anderson4D.PartialPairing.compositionHeadTail (n : ℕ) :
                Composition (n + 1) → (k : Fin (n + 1)) × Composition (n - ↑k)

                Remove the positive first block from a composition of n+1. The finite index stores that block minus one.

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                  def Anderson4D.PartialPairing.compositionPrepend (n : ℕ) :
                  (k : Fin (n + 1)) × Composition (n - ↑k) → Composition (n + 1)

                  Prepend the block k+1 to a composition of the remaining degree.

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                    Classifying a nonempty composition by its first block is a finite equivalence.

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                      theorem Anderson4D.PartialPairing.gradedParametrix_succ_eq_sum_head (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (n : ℕ) (x y : T4) (ω : M.Ω) :
                      gradedParametrix M ρ lam ε (n + 1) x y ω = ∑ k : Fin (n + 1), ∑ c : Composition (n - ↑k), renormWordKernel M ρ lam ε ((↑k + 1) :: c.blocks) x y ω

                      The order-n+1 graded sum, classified by the size of its first positive block.

                      theorem Anderson4D.PartialPairing.gradedParametrix_succ_eq_headConvolutions (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (n : ℕ) (x y : T4) (ω : M.Ω) (hflat : ∀ (k : Fin (n + 1)) (c : Composition (n - ↑k)), RenormWordIntegrable M ρ lam ε ((↑k + 1) :: c.blocks) x y ω) :
                      gradedParametrix M ρ lam ε (n + 1) x y ω = ∑ k : Fin (n + 1), ∫ (z : T4), greenFn (x - z) * renormWordWeight M ρ lam ε (↑k + 1) z ω * gradedParametrix M ρ lam ε (n - ↑k) z y ω ∂paperMeasure

                      Head-block recurrence for the graded sum. Joint integrability is required only for the finitely many flat words at the new order.

                      Even head blocks #

                      def Anderson4D.PartialPairing.evenHeadIndex (n : ℕ) (q : ↥(Finset.Icc 1 ((n + 1) / 2))) :
                      { k : Fin (n + 1) // Even (↑k + 1) }

                      The even block of order 2q as a head index (block size minus one).

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                        def Anderson4D.PartialPairing.evenHeadOrder (n : ℕ) (k : { k : Fin (n + 1) // Even (↑k + 1) }) :
                        ↥(Finset.Icc 1 ((n + 1) / 2))

                        Recover q from an even positive head block 2q.

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                          def Anderson4D.PartialPairing.evenHeadIndexEquiv (n : ℕ) :
                          ↥(Finset.Icc 1 ((n + 1) / 2)) ≃ { k : Fin (n + 1) // Even (↑k + 1) }

                          Positive even head blocks are in bijection with the paper's counterterm range q ∈ [1, ⌊(n+1)/2⌋].

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                            theorem Anderson4D.PartialPairing.headSelector_sum (n : ℕ) (A : ℝ) (B : ℕ → ℝ) :
                            (∑ k : Fin (n + 1), if ↑k = 0 then A else if Even (↑k + 1) then -B ((↑k + 1) / 2) else 0) = A - ∑ q ∈ Finset.Icc 1 ((n + 1) / 2), B q

                            Summing a head-block selector leaves its degree-one term and the negative contributions of exactly the positive even blocks.

                            Proposition 3.4 recurrence for the graded sum #

                            noncomputable def Anderson4D.PartialPairing.gradedParametrixNoiseSource (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (n : ℕ) (x y : T4) (ω : M.Ω) :

                            Degree-one head contribution for the graded parametrix.

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                              noncomputable def Anderson4D.PartialPairing.gradedCountertermBlock (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (q r : ℕ) (x y : T4) (ω : M.Ω) :

                              Positive even head contribution for the graded parametrix.

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                                noncomputable def Anderson4D.PartialPairing.gradedOrderCountertermSum (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (n : ℕ) (x y : T4) (ω : M.Ω) :

                                Sum of the positive even graded head blocks at order n+1.

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                                  theorem Anderson4D.PartialPairing.gradedParametrix_succ_eq_noise_sub_counterterms (M : NoiseModel) (ρ : SmoothCutoff) (lam ε : ℝ) (n : ℕ) (x y : T4) (ω : M.Ω) (hflat : ∀ (k : Fin (n + 1)) (c : Composition (n - ↑k)), RenormWordIntegrable M ρ lam ε ((↑k + 1) :: c.blocks) x y ω) :
                                  gradedParametrix M ρ lam ε (n + 1) x y ω = gradedParametrixNoiseSource M ρ lam ε n x y ω - gradedOrderCountertermSum M ρ lam ε n x y ω

                                  The graded composition sum satisfies the left recurrence of Proposition 3.4.