Projected Frobenius coefficients
ProvedQAlgorithms.Papers.Independent.Intakenext100.P41.projectedCoefficientProductFor the basic ODE with under all §18 hypotheses, fix a normalized eigenvector of with eigenvalue . Construct its coefficients by
For every , with ,
The empty product is one, and nonresonance ensures that every inverse at positive exists. This retains displayed equation (5); the erroneous intervening prose recurrence is not used as a definition.
import Definitions.Def_QAlgorithms_Papers_Independent_Intakenext100_P41
noncomputable section
open scoped BigOperators
open MeasureTheory Set
namespace QAlgorithms.Papers.Independent.Intakenext100.P41
/-- §22 equation (5), PDF p.28. The printed intervening recurrence has an
index/factor typo. The directly preceding resolvent identity gives
α_n=χ_P(λ+n)α_{n−1}, yielding the printed product below, including n=0. -/
theorem projectedCoefficientProduct {d : ℕ} (A : BasicODEData d) (i : Fin d) (n : ℕ) :
projectedCoefficient A i n = A.phi (A.xi i) *
∏ m ∈ Finset.range n,
resolventScalar A.P A.v A.phi (A.lambda i + ((m + 1 : ℕ) : ℂ)) := by sorry
end QAlgorithms.Papers.Independent.Intakenext100.P41
end
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What the Lean code literally says, in plain math · gpt-6.1-sol
Let be a natural number and let consist of a positive dimension , a matrix , a vector , a complex-linear functional with , families and , and bases and of . Put , where is the standard coordinate vector. Assume that , , and for every ; that all coordinates of in both bases are nonzero; and that, for distinct and every integer , and . For every index , define
Then for every natural number ,
Here natural numbers in complex expressions are embedded into , and matrix inversion is total, assigning the zero matrix to singular matrices. For the product is empty and equals , so the equality reads , with this value equal to by normalization.
Confirmed by the mission captain (proposal self-audit).
Confirmed by the moderator at approval.