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Add lean source and binary files (part 84)
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import OAI.LinearAlgebra.MatrixMultiplication.Completion.FiniteRealization
import OAI.LinearAlgebra.MatrixMultiplication.Tensor.MatrixBalancing
import OAI.LinearAlgebra.MatrixMultiplication.Tensor.ComplexWitness
import OAI.LinearAlgebra.MatrixMultiplication.Tensor.BaseTensorBudgets
namespace OAI
/-! Dual matrix multiplication exponents and finite rectangular constructions. -/
noncomputable section
namespace MatrixMultiplication.DualFiniteRealization
open MatrixMultiplication.Foundation RecursiveCompletion
open CompletionHierarchyWords CompletionExecution CompletionFiniteRealization
open scoped BigOperators Classical
variable {A X Y Z : Type} [Fintype A]
variable (H : ReadableHierarchy A X Y Z) (counts : A → ℕ) (t : ℕ)
variable (complete : Function.Injective (labelRecordOf H.labels H.depth))
variable [Fintype X] [Fintype Y] [Fintype Z]
def rankBudget (R : ℕ) : ℕ :=
R ^ CompletionFiniteRealization.blocks counts t * (realize H counts t).execution.rankBound
def sourcePower {T : Tensor ℂ X Y Z} {R d D : ℕ}
(source : Tensor.PolynomialApproximation T R d D) :
Tensor.PolynomialApproximation
(Tensor.power T (CompletionFiniteRealization.blocks counts t))
(R ^ CompletionFiniteRealization.blocks counts t)
(d * CompletionFiniteRealization.blocks counts t)
(D * CompletionFiniteRealization.blocks counts t) :=
source.power (CompletionFiniteRealization.blocks counts t)
def approximation {T : Tensor ℂ X Y Z} {R d D : ℕ}
(source : Tensor.PolynomialApproximation T R d D)
(supported : ∀ x y z, T x y z ≠ 0 → ∃ a, H.x a = x ∧ H.y a = y ∧ H.z a = z)
(unit : ∀ a, T (H.x a) (H.y a) (H.z a) = 1) :
Tensor.PolynomialApproximation
(Tensor.directSum (fun _ : Fin (copies H counts t) =>
Tensor.matrixCoefficients (K := ℂ)
(Fin (rows H counts t)) (Fin (inner H counts t)) (Fin (columns H counts t))))
(rankBudget H counts t R) (order H counts t d) (degree H counts t D) := by
have hs : ∀ x y z, ¬ support H counts t x y z →
Tensor.power T (CompletionFiniteRealization.blocks counts t) x y z = 0 := by
intro x y z outside
by_contra nonzero
apply outside
intro i
exact supported _ _ _ ((Finset.prod_ne_zero_iff.mp nonzero) i (Finset.mem_univ i))
have full := ExecutionApproximation.approximation (realize H counts t).execution
(sourcePower counts t source) hs
have selected := full.pullback (leftSelect H counts t complete)
(middleSelect H counts t complete) (rightSelect H counts t complete)
rw [selected_output H counts t complete T unit] at selected
exact selected
omit [Fintype X] [Fintype Y] [Fintype Z] in
theorem rankBudget_pos {R : ℕ} (hR : 0 < R) : 0 < rankBudget H counts t R :=
Nat.mul_pos (pow_pos hR _) (auxiliaryRank_pos H counts t)
def witness {T : Tensor ℂ X Y Z} {R d D : ℕ}
(source : Tensor.PolynomialApproximation T R d D) (hR : 0 < R)
(supported : ∀ x y z, T x y z ≠ 0 → ∃ a, H.x a = x ∧ H.y a = y ∧ H.z a = z)
(unit : ∀ a, T (H.x a) (H.y a) (H.z a) = 1) :
ComplexWitness.FiniteRectangularWitness where
outer := rows H counts t * inner H counts t
inner := columns H counts t ^ 2
multiplicity := copies H counts t ^ 2
rank := rankBudget H counts t R ^ 2
outer_pos := Nat.mul_pos (dimensions_positive H counts t).1
(dimensions_positive H counts t).2.1
inner_pos := pow_pos (dimensions_positive H counts t).2.2 2
multiplicity_pos := pow_pos (copies_pos H counts t complete) 2
rank_pos := pow_pos (rankBudget_pos H counts t hR) 2
order := 2 * order H counts t d
degree := 2 * degree H counts t D
approximation := MatrixBalancing.finiteBalanced
(approximation H counts t complete source supported unit)
section Projections
variable {T : Tensor ℂ X Y Z} {R d D : ℕ}
variable (source : Tensor.PolynomialApproximation T R d D) (hR : 0 < R)
variable (supported : ∀ x y z, T x y z ≠ 0 → ∃ a, H.x a = x ∧ H.y a = y ∧ H.z a = z)
variable (unit : ∀ a, T (H.x a) (H.y a) (H.z a) = 1)
@[simp] theorem witness_outer :
(witness H counts t complete source hR supported unit).outer =
rows H counts t * inner H counts t := rfl
@[simp] theorem witness_inner :
(witness H counts t complete source hR supported unit).inner = columns H counts t ^ 2 := rfl
@[simp] theorem witness_multiplicity :
(witness H counts t complete source hR supported unit).multiplicity = copies H counts t ^ 2 :=
rfl
@[simp] theorem witness_rank :
(witness H counts t complete source hR supported unit).rank =
(R ^ CompletionFiniteRealization.blocks counts t *
(realize H counts t).execution.rankBound) ^ 2 := rfl
theorem witness_dimensions :
(witness H counts t complete source hR supported unit).outer =
ConditionalLabels.stagePairingSize counts H.labels H.depth
(fun n => H.pair n.val) .xz t *
ConditionalLabels.stagePairingSize counts H.labels H.depth
(fun n => H.pair n.val) .xy t ∧
(witness H counts t complete source hR supported unit).inner =
ConditionalLabels.stagePairingSize counts H.labels H.depth
(fun n => H.pair n.val) .yz t ^ 2 := by
rcases realize_dimensions H counts t with ⟨hr, hi, hc⟩
change (realize H counts t).shape.rows * (realize H counts t).shape.inner = _ ∧
(realize H counts t).shape.columns ^ 2 = _
simp only [hr, hi, hc, and_self]
theorem witness_rank_stageBudget :
(witness H counts t complete source hR supported unit).rank =
(R ^ CompletionFiniteRealization.blocks counts t *
StageHierarchyResources.stageAuxiliaryBudget counts H.labels H.depth t) ^ 2 := by
rw [witness_rank, realize_rankBound]
end Projections
omit [Fintype X] [Fintype Y] [Fintype Z] in
theorem rankBudget_base (base factors : ℕ) :
rankBudget H counts t (base ^ factors) =
base ^ (factors * CompletionFiniteRealization.blocks counts t) *
StageHierarchyResources.stageAuxiliaryBudget counts H.labels H.depth t := by
simp only [rankBudget, ← pow_mul, realize_rankBound]
def dualSource :
Tensor.PolynomialApproximation (Script.tensor BaseTwo.flagged Script.dual).tensor
(2 ^ 288) (Script.dual.order 1) (Script.dual.degree 3) := by
simpa only [Script.dual_factors] using
Script.approximation BaseTwo.flagged BaseTwo.approximation Script.dual
end MatrixMultiplication.DualFiniteRealization
end
end OAI