Orthonormal Basis Expansion of a Multilinear Form
ProvedFunctionalInequalities.Analysis.Tensor.apply_eq_sum_coordTensor_readablefunctional-inequalitieskls-conjecturekls-modularkls-readablelog-concave
This is the coordinate expansion of a real continuous multilinear form.
Let be a real inner-product space, let be an orthonormal basis indexed by , let be a continuous -linear map, and let . Then
The formula expresses a multilinear form through its coordinate tensor in an orthonormal basis.
Original Lean declaration header
Within namespace FunctionalInequalities.Analysis.Tensor. Shown in its original module context. Proof omitted.
theorem apply_eq_sum_coordTensor {n k : ℕ} (b : OrthonormalBasis (Fin n) ℝ E)
(Φ : ContinuousMultilinearMap ℝ (fun _ : Fin k => E) ℝ) (h : Fin k → E) :
Φ h = ∑ i : Fin k → Fin n, coordTensor b Φ i * ∏ j, ⟪b (i j), h j⟫
Module navigation
Module: Analysis/Tensor/Coefficients.
Next: norm_coordTensor_le.
Source excerpt, lines 108–110 · Frozen source 408915f.
Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Analysis_Tensor_Coefficients
open scoped RealInnerProductSpace
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
Formal statement
theorem FunctionalInequalities.Analysis.Tensor.apply_eq_sum_coordTensor_readable {n k : ℕ} (b : OrthonormalBasis (Fin n) ℝ E)
(Φ : ContinuousMultilinearMap ℝ (fun _ : Fin k => E) ℝ) (h : Fin k → E) :
Φ h = ∑ i : Fin k → Fin n, coordTensor b Φ i * ∏ j, ⟪b (i j), h j⟫ := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Analysis/Tensor/Coefficients.lean#L107-L125 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Analysis.Tensor.Coefficients`, declaration `FunctionalInequalities.Analysis.Tensor.apply_eq_sum_coordTensor`; the repository is private at upload time).