OAI/GroupTheory/PolycyclicRecognition/Algebra/GradedGeneratorLimit.lean

GitHub source file

6 declarations, 0 contain sorry, 0 declared as axioms

Generating vectors and group laws survive the graded limit

  1. def OAI.PolycyclicRecognition.gradedGenerator line 19

    Source documentation

    The part of a vector whose coordinate degree equals the prescribed generator degree.

    def gradedGenerator {n : ℕ} (b : Basis (Fin n) ℝ L) (cost : Fin n → ℝ)
        (s : ℝ) (x : L) : Fin n → ℝ :=
    …
  2. theorem OAI.PolycyclicRecognition.rescaled_generator_tendsto line 23
  3. theorem OAI.PolycyclicRecognition.maximizing_word_basis_letter_weight line 45

    Source documentation

    Basis maximality prevents a generator from having a nonzero coordinate of lower degree.

    theorem maximizing_word_basis_letter_weight
        (X : I → L) (S : Finset (FreeMagma I)) (hletters : ∀ i, FreeMagma.of i ∈ S)
        (b₀ : Basis (Fin (finrank ℝ L)) ℝ L) (s : I → ℝ)
        (β : WordBasisSelections X S)
        (hβ : IsMaximizingColumnBasis (wordListCoordinates X S b₀)
          (fun w => bracketWordExponent s w) β.val)
        (i : I) (j : Fin (finrank ℝ L))
        (hnz : (WordBasisSelections.basis X S β).repr (X i) j ≠ 0) :
        s i ≤ bracketWordExponent s (β.val j) := by
    …

    Mentions: OAI.PolycyclicRecognition.WordBasisSelections, OAI.PolycyclicRecognition.IsMaximizingColumnBasis, OAI.PolycyclicRecognition.wordListCoordinates, OAI.PolycyclicRecognition.bracketWordExponent, OAI.PolycyclicRecognition.WordBasisSelections.basis

  4. theorem OAI.PolycyclicRecognition.rescaledLieData_tendsto_graded line 66

    Source documentation

    The actual rescaled bracket and all actual generators converge together.

    theorem rescaledLieData_tendsto_graded
        (X : I → L) {k : ℕ} (hk : lowerCentralSeries ℝ L L k = ⊥)
        (hletters : ∀ i : I, FreeMagma.of i ∈ boundedBracketWords k)
        (b₀ : Basis (Fin (finrank ℝ L)) ℝ L) (s : I → ℝ)
        (β : WordBasisSelections X (boundedBracketWords k))
        (hβ : IsMaximizingColumnBasis (wordListCoordinates X (boundedBracketWords k) b₀)
          (fun w => bracketWordExponent s w) β.val) :
        let b := WordBasisSelections.basis X (boundedBracketWords k) β
    …

    Mentions: OAI.PolycyclicRecognition.boundedBracketWords, OAI.PolycyclicRecognition.WordBasisSelections, OAI.PolycyclicRecognition.IsMaximizingColumnBasis, OAI.PolycyclicRecognition.wordListCoordinates, OAI.PolycyclicRecognition.bracketWordExponent, OAI.PolycyclicRecognition.WordBasisSelections.basis

  5. theorem OAI.PolycyclicRecognition.graded_generators_word_normalization line 88

    Source documentation

    Every selected bracket word still evaluates to its coordinate unit in the graded limit. Thus the limiting generators span the whole Lie algebra under brackets; the limit has not lost any directions.

    theorem graded_generators_word_normalization
        (X : I → L) {k : ℕ} (hk : lowerCentralSeries ℝ L L k = ⊥)
        (hletters : ∀ i : I, FreeMagma.of i ∈ boundedBracketWords k)
        (b₀ : Basis (Fin (finrank ℝ L)) ℝ L) (s : I → ℝ)
        (β : WordBasisSelections X (boundedBracketWords k))
        (hβ : IsMaximizingColumnBasis (wordListCoordinates X (boundedBracketWords k) b₀)
          (fun w => bracketWordExponent s w) β.val) :
        let b := WordBasisSelections.basis X (boundedBracketWords k) β
    …

    Mentions: OAI.PolycyclicRecognition.boundedBracketWords, OAI.PolycyclicRecognition.WordBasisSelections, OAI.PolycyclicRecognition.IsMaximizingColumnBasis, OAI.PolycyclicRecognition.wordListCoordinates, OAI.PolycyclicRecognition.bracketWordExponent, OAI.PolycyclicRecognition.WordBasisSelections.basis

  6. theorem OAI.PolycyclicRecognition.gradedCoordinateBracket_groupLaws line 106

    Source documentation

    The fixed finite Dynkin product retains its exact group and straight-line one-parameter identities in the limiting coordinate law.

    theorem gradedCoordinateBracket_groupLaws
        {G : Type*} [Group G] {n c : ℕ} (b : Basis (Fin n) ℝ L) (cost : Fin n → ℝ)
        (hweight : ∀ i j k, b.repr ⁅b i, b j⁆ k ≠ 0 → cost i + cost j ≤ cost k)
        (Exp : L → G) (hinj : Function.Injective Exp)
        (hzero : Exp 0 = 1) (hneg : ∀ x, Exp (-x) = (Exp x)⁻¹)
        (hadd : ∀ x (s t : ℝ), Exp ((s + t) • x) = Exp (s • x) * Exp (t • x))
        (a : DynkinCoefficients c 2)
        (hm : ∀ x y, Exp (finiteDynkinPolynomial a ![x, y]) = Exp x * Exp y) :
        PolynomialGroupLaws (dynkinProduct a (gradedCoordinateBracket b cost)) :=
    …

    Mentions: OAI.PolycyclicRecognition.DynkinCoefficients, OAI.PolycyclicRecognition.finiteDynkinPolynomial, OAI.PolycyclicRecognition.PolynomialGroupLaws, OAI.PolycyclicRecognition.dynkinProduct, OAI.PolycyclicRecognition.gradedCoordinateBracket