English
The frontier of a convex set in a finite-dimensional Real vector space has zero Haar measure.
Русский
Граница выпуклого множества в конечномерном вещественном векторном пространстве имеет нулевую Хаарову меру.
LaTeX
$$$\\mu(\\operatorname{frontier}(s))=0$ при $s$ выпукло и конечномерное Real пространства.$$
Lean4
/-- Haar measure of the frontier of a convex set is zero. -/
theorem addHaar_frontier (hs : Convex ℝ s) : μ (frontier s) = 0 := by
/- If `s` is included in a hyperplane, then `frontier s ⊆ closure s` is included in the same
hyperplane, hence it has measure zero. -/
rcases ne_or_eq (affineSpan ℝ s) ⊤ with hspan | hspan
· refine measure_mono_null ?_ (addHaar_affineSubspace _ _ hspan)
exact
frontier_subset_closure.trans
(closure_minimal (subset_affineSpan _ _) (affineSpan ℝ s).closed_of_finiteDimensional)
rw [← hs.interior_nonempty_iff_affineSpan_eq_top] at hspan
rcases hspan with
⟨x, hx⟩
/- Without loss of generality, `s` is bounded. Indeed, `∂s ⊆ ⋃ n, ∂(s ∩ ball x (n + 1))`, hence it
suffices to prove that `∀ n, μ (s ∩ ball x (n + 1)) = 0`; the latter set is bounded.
-/
suffices H : ∀ t : Set E, Convex ℝ t → x ∈ interior t → IsBounded t → μ (frontier t) = 0
by
let B : ℕ → Set E := fun n => ball x (n + 1)
have : μ (⋃ n : ℕ, frontier (s ∩ B n)) = 0 :=
by
refine measure_iUnion_null fun n => H _ (hs.inter (convex_ball _ _)) ?_ (isBounded_ball.subset inter_subset_right)
rw [interior_inter, isOpen_ball.interior_eq]
exact ⟨hx, mem_ball_self (add_pos_of_nonneg_of_pos n.cast_nonneg zero_lt_one)⟩
refine measure_mono_null (fun y hy => ?_) this; clear this
set N : ℕ := ⌊dist y x⌋₊
refine mem_iUnion.2 ⟨N, ?_⟩
have hN : y ∈ B N := by simp [B, N, Nat.lt_floor_add_one]
suffices y ∈ frontier (s ∩ B N) ∩ B N from this.1
rw [frontier_inter_open_inter isOpen_ball]
exact ⟨hy, hN⟩
intro s hs hx hb
replace hb : μ (interior s) ≠ ∞ := (hb.subset interior_subset).measure_lt_top.ne
suffices μ (closure s) ≤ μ (interior s) by
rwa [frontier, measure_diff interior_subset_closure isOpen_interior.nullMeasurableSet hb, tsub_eq_zero_iff_le]
/- Due to `Convex.closure_subset_image_homothety_interior_of_one_lt`, for any `r > 1` we have
`closure s ⊆ homothety x r '' interior s`, hence `μ (closure s) ≤ r ^ d * μ (interior s)`,
where `d = finrank ℝ E`. -/
set d : ℕ := Module.finrank ℝ E
have : ∀ r : ℝ≥0, 1 < r → μ (closure s) ≤ ↑(r ^ d) * μ (interior s) := fun r hr ↦
by
refine (measure_mono <| hs.closure_subset_image_homothety_interior_of_one_lt hx r hr).trans_eq ?_
rw [addHaar_image_homothety, ← NNReal.coe_pow, NNReal.abs_eq, ENNReal.ofReal_coe_nnreal]
have : ∀ᶠ (r : ℝ≥0) in 𝓝[>] 1, μ (closure s) ≤ ↑(r ^ d) * μ (interior s) := mem_of_superset self_mem_nhdsWithin this
refine ge_of_tendsto ?_ this
refine
(((ENNReal.continuous_mul_const hb).comp (ENNReal.continuous_coe.comp (continuous_pow d))).tendsto' _ _
?_).mono_left
nhdsWithin_le_nhds
simp
