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Closed-Subspace Selection With A Frequently Bounded Hilbert Component

Proved
FunctionalInequalities.Energy.exists_mem_of_isClosed_of_frequently_norm_le_readable

by Lazyfill · Oct 26, 2026 · Mathlib 0df444a (Lean v4.33.1)

functional-inequalitieskls-conjecturekls-modularkls-readablelog-concave

This is a closed-subspace selection lemma in a product of normed spaces.

Let XXX be a real normed space, let HHH be a complete real Hilbert space, and let G⊆X×HG\subseteq X\times HG⊆X×H be a closed real submodule. Suppose sequences xn∈Xx_n\in Xxn​∈X and yn∈Hy_n\in Hyn​∈H satisfy

  1. (xn,yn)∈G(x_n,y_n)\in G(xn​,yn​)∈G for every nnn;
  2. xn→x0x_n\to x_0xn​→x0​;
  3. for some real LLL, the inequality ∥yn∥≤L\|y_n\|\le L∥yn​∥≤L holds frequently along n→∞n\to\inftyn→∞.

Then there exists y0∈Hy_0\in Hy0​∈H such that

(x0,y0)∈G,∥y0∥≤L.(x_0,y_0)\in G, \qquad \|y_0\|\le L.(x0​,y0​)∈G,∥y0​∥≤L.

The Lean declaration is exists_mem_of_isClosed_of_frequently_norm_le_readable. “Frequently” is the filter-theoretic condition along atTop, not an eventual bound.

Original Lean declaration header

Within namespace FunctionalInequalities.Energy. Shown in its original module context. Proof omitted.

theorem exists_mem_of_isClosed_of_frequently_norm_le
    {G : Submodule ℝ (X × H)} (hG : IsClosed (G : Set (X × H)))
    {x : ℕ → X} {y : ℕ → H} (hxy : ∀ n, (x n, y n) ∈ G)
    {x₀ : X} (hx : Tendsto x atTop (𝓝 x₀)) {L : ℝ} (hL : ∃ᶠ n in atTop, ‖y n‖ ≤ L) :
    ∃ y₀ : H, (x₀, y₀) ∈ G ∧ ‖y₀‖ ≤ L

Module navigation

Module: Energy/Relaxation/LinearPMap.

Next: sequentialRelaxation_ofLinearPMap_le.

Source excerpt, lines 51–55 · Frozen source 408915f.

Preamble
import Definitions.Def_KLSModular_FunctionalInequalities_Energy_Relaxation_LinearPMap

open Filter Topology Set
variable {X : Type*} [NormedAddCommGroup X] [NormedSpace ℝ X]
  {H : Type*} [NormedAddCommGroup H] [InnerProductSpace ℝ H] [CompleteSpace H]
Formal statement

theorem FunctionalInequalities.Energy.exists_mem_of_isClosed_of_frequently_norm_le_readable
    {G : Submodule ℝ (X × H)} (hG : IsClosed (G : Set (X × H)))
    {x : ℕ → X} {y : ℕ → H} (hxy : ∀ n, (x n, y n) ∈ G)
    {x₀ : X} (hx : Tendsto x atTop (𝓝 x₀)) {L : ℝ} (hL : ∃ᶠ n in atTop, ‖y n‖ ≤ L) :
    ∃ y₀ : H, (x₀, y₀) ∈ G ∧ ‖y₀‖ ≤ L := by sorry
Source
Lean source: https://github.com/human-ai-mathematics/kls-lean/blob/408915f/formalization/FunctionalInequalities/Energy/Relaxation/LinearPMap.lean#L47-L162 (repository human-ai-mathematics/kls-lean, commit 408915f, module `FunctionalInequalities.Energy.Relaxation.LinearPMap`, declaration `FunctionalInequalities.Energy.exists_mem_of_isClosed_of_frequently_norm_le`; the repository is private at upload time).

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