openAI-math-dataset / lean /OAI /GroupTheory /Thompson /MeanApproximation.lean
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import OAI.GroupTheory.Thompson.InvariantMean
import OAI.GroupTheory.Thompson.ProbabilityDefects
import Mathlib.Analysis.LocallyConvex.Separation
import Mathlib.Analysis.LocallyConvex.WithSeminorms
import Mathlib.Analysis.Convex.Topology
namespace OAI
/-!
# Finite probabilities approximately invariant under a finite set
The usual positive normalized invariant mean forces zero to lie in the
closure of the actual finite-probability defect set. The separation argument
uses bounded coordinate functions of a continuous linear functional on ℓ¹;
no identification of the full dual of ℓ¹ is assumed.
-/
noncomputable section
open scoped ENNReal BigOperators
universe uG
namespace ThompsonNonamenability
variable {G : Type uG} [Group G] [DecidableEq G]
local instance : Fact (1 ≤ (1 : ℝ≥0∞)) := ⟨le_rfl⟩
/-- A separator gives one bounded real function for each translation. -/
def separatorCoordinate {S : Finset G} (ell : DefectSpace S →L[ℝ] ℝ)
(h : {h : G // h ∈ S}) : BoundedReal G :=
⟨fun g => ell (lp.single 1 (h, g) 1), memℓp_infty ⟨‖ell‖, by
rintro y ⟨g, rfl⟩
have hb := ell.le_opNorm (lp.single 1 (h, g) 1)
simpa only [lp.norm_single (by norm_num : 0 < (1 : ℝ≥0∞)),
norm_one, mul_one] using hb⟩⟩
omit [Group G] in
@[simp]
theorem separatorCoordinate_apply [Group G] {S : Finset G}
(ell : DefectSpace S →L[ℝ] ℝ) (h : {h : G // h ∈ S}) (g : G) :
separatorCoordinate ell h g = ell (lp.single 1 (h, g) 1) := rfl
/-- The finite sum whose mean vanishes by left invariance. -/
def separatorDefect {S : Finset G} (ell : DefectSpace S →L[ℝ] ℝ) : BoundedReal G :=
∑ h : {h : G // h ∈ S},
(leftPull h.val (separatorCoordinate ell h) - separatorCoordinate ell h)
theorem separatorDefect_apply {S : Finset G} (ell : DefectSpace S →L[ℝ] ℝ)
(g : G) : separatorDefect ell g = ell (diracDefect S g) := by
classical
cases Subsingleton.elim (inferInstance : DecidableEq G) (Classical.decEq G)
simp only [separatorDefect, lp.coeFn_sum, Finset.sum_apply,
lp.coeFn_sub, Pi.sub_apply, leftPull_apply, separatorCoordinate_apply,
diracDefect, map_sum, map_sub]
theorem InvariantMean.separatorDefect_eq_zero (M : InvariantMean G)
{S : Finset G} (ell : DefectSpace S →L[ℝ] ℝ) : M (separatorDefect ell) = 0 := by
classical
change M.toLinearMap (∑ h : {h : G // h ∈ S},
(leftPull h.val (separatorCoordinate ell h) - separatorCoordinate ell h)) = 0
simp only [map_sum, map_sub, M.left_invariant, sub_self, Finset.sum_const_zero]
/-- Separation contradicts the existence of a positive normalized invariant mean. -/
theorem InvariantMean.zero_mem_closure_defectSet (M : InvariantMean G)
(S : Finset G) : (0 : DefectSpace S) ∈ closure (defectSet S) := by
classical
by_contra hout
obtain ⟨ell, c, hc, hsep⟩ := geometric_hahn_banach_point_closed
(convex_defectSet S).closure isClosed_closure hout
have hcpos : 0 < c := by simpa only [ell.map_zero] using hc
have hpoint (g : G) : c ≤ separatorDefect ell g := by
rw [separatorDefect_apply]
apply le_of_lt
apply hsep
apply subset_closure
exact diracDefect_mem_defectSet S g
have hmean : c ≤ M (separatorDefect ell) := by
simpa only [InvariantMean.map_const] using
M.mono (f := c • (1 : BoundedReal G)) (g := separatorDefect ell)
(fun g => by simpa only [BoundedReal.smul_one_apply] using hpoint g)
rw [M.separatorDefect_eq_zero] at hmean
exact (not_le_of_gt hcpos) hmean
/-- Actual nonnegative finite probabilities with arbitrarily small total defect. -/
theorem InvariantMean.exists_probability_small_defect (M : InvariantMean G)
(S : Finset G) {ε : ℝ} (hε : 0 < ε) :
∃ p : G →₀ ℝ, IsProbabilityWeights p ∧ ‖defectMap S p‖ < ε := by
classical
obtain ⟨v, hv, hvsmall⟩ := Metric.mem_closure_iff.mp
(M.zero_mem_closure_defectSet S) ε hε
obtain ⟨p, hp, rfl⟩ := hv
refine ⟨p, hp, ?_⟩
simpa only [dist_zero_left] using hvsmall
end ThompsonNonamenability
end
end OAI