openAI-math-dataset / lean /OAI /Probability /SKGap /Localization /AttractionBasinIUnion.lean
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import Mathlib
import OAI.Probability.SKGap.Localization.TapPotential
namespace OAI
section
noncomputable section
open scoped BigOperators
open Real Matrix Set Filter Function
open scoped Topology
namespace SKGap
section Basins
variable {X : Type*} [TopologicalSpace X] (T : X → X)
lemma attractionBasin_eq_iUnion {p : X} {U : Set X} (hU : IsOpen U) (hp : p ∈ U)
(hatt : U ⊆ attractionBasin T p) :
attractionBasin T p = ⋃ k : ℕ, (T^[k]) ⁻¹' U := by
ext x
constructor
· intro hx
have h := hx.eventually (hU.mem_nhds hp)
obtain ⟨k, hk⟩ := h.exists
exact mem_iUnion.mpr ⟨k, hk⟩
· intro hx
obtain ⟨k, hk⟩ := mem_iUnion.mp hx
exact (mem_attractionBasin_iterate_iff T p x k).mp (hatt hk)
lemma isOpen_attractionBasin (hT : Continuous T) {p : X} {U : Set X}
(hU : IsOpen U) (hp : p ∈ U) (hatt : U ⊆ attractionBasin T p) :
IsOpen (attractionBasin T p) := by
rw [attractionBasin_eq_iUnion T hU hp hatt]
exact isOpen_iUnion (fun k => hU.preimage (hT.iterate k))
lemma disjoint_attractionBasins [T2Space X] {p q : X} (hpq : p ≠ q) :
Disjoint (attractionBasin T p) (attractionBasin T q) := by
rw [disjoint_left]
intro x hx hy
exact hpq (tendsto_nhds_unique hx hy)
end Basins
theorem lyapunov_unique_fixed_point {X : Type*} [TopologicalSpace X] [CompactSpace X]
[ConnectedSpace X] [T2Space X]
(T : X → X) (hT : Continuous T) (φ : X → ℝ) (hφ : Continuous φ)
(hstrict : ∀ x, T x ≠ x → φ (T x) < φ x)
(hattract : ∀ p, T p = p → ∃ U : Set X, IsOpen U ∧ p ∈ U ∧
U ⊆ attractionBasin T p) : ∃! p, T p = p := by
have hopen (p) (hp : T p = p) : IsOpen (attractionBasin T p) := by
obtain ⟨U, hU, hpU, hatt⟩ := hattract p hp
exact isOpen_attractionBasin T hT hU hpU hatt
have hcover (x : X) : ∃ p, T p = p ∧ x ∈ attractionBasin T p := by
let U := ⋃ p : {p // T p = p}, attractionBasin T p.val
have hU : IsOpen U := isOpen_iUnion (fun p => hopen p.val p.property)
have hfixed (p) (hp : T p = p) : p ∈ U :=
mem_iUnion.mpr ⟨⟨p, hp⟩, fixed_mem_attractionBasin T hp⟩
obtain ⟨k, hk⟩ := lyapunov_eventually_hits T hT φ hφ hstrict hU hfixed x
obtain ⟨p, hp⟩ := mem_iUnion.mp hk
exact ⟨p.val, p.property, (mem_attractionBasin_iterate_iff T p.val x k).mp hp⟩
obtain ⟨p, hp⟩ := lyapunov_fixed_point T φ hφ hstrict
refine ⟨p, hp, fun q hq => ?_⟩
by_contra hqp
let V := ⋃ q : {q // T q = q ∧ q ≠ p}, attractionBasin T q.val
have hV : IsOpen V := isOpen_iUnion (fun q => hopen q.val q.property.1)
have hdisj : Disjoint (attractionBasin T p) V := by
rw [disjoint_iUnion_right]
intro q
exact disjoint_attractionBasins T q.property.2.symm
have hcov : (univ : Set X) ⊆ attractionBasin T p ∪ V := by
intro x _
obtain ⟨r, hr, hx⟩ := hcover x
by_cases he : r = p
· subst r
exact Or.inl hx
· exact Or.inr (mem_iUnion.mpr ⟨⟨r, hr, he⟩, hx⟩)
have hconn := IsPreconnected.subset_or_subset (hopen p hp) hV hdisj hcov
isPreconnected_univ
rcases hconn with hconn | hconn
· have hqp' := tendsto_nhds_unique (hconn (mem_univ q))
(fixed_mem_attractionBasin T hq)
exact hqp hqp'.symm
· exact disjoint_left.mp hdisj (fixed_mem_attractionBasin T hp) (hconn (mem_univ p))
theorem local_contraction_attracts {X : Type*} [MetricSpace X]
{T : X → X} {p : X} (hp : T p = p) {K : NNReal} (hK : K < 1)
{U : Set X} (hU : U ∈ 𝓝 p) (hlip : LipschitzOnWith K T U) :
∃ V : Set X, IsOpen V ∧ p ∈ V ∧ V ⊆ attractionBasin T p := by
obtain ⟨ε, hε, hball⟩ := Metric.mem_nhds_iff.mp hU
have hpU : p ∈ U := hball (Metric.mem_ball_self hε)
have hmaps : MapsTo T (Metric.ball p ε) (Metric.ball p ε) := by
intro x hx
have h := hlip.dist_le_mul x (hball hx) p hpU
rw [hp] at h
exact h.trans_lt ((mul_le_of_le_one_left (dist_nonneg : 0 ≤ dist x p)
(show (K:ℝ) ≤ 1 by exact_mod_cast hK.le)).trans_lt hx)
refine ⟨Metric.ball p ε, Metric.isOpen_ball, Metric.mem_ball_self hε, ?_⟩
intro x hx
have hbd (n : ℕ) : dist (T^[n] x) p ≤ (K:ℝ)^n * dist x p := by
induction n with
| zero => simp
| succ n ih =>
rw [iterate_succ_apply']
have h := hlip.dist_le_mul (T^[n] x) (hball (hmaps.iterate n hx)) p hpU
rw [hp] at h
exact h.trans (by simpa only [pow_succ', mul_assoc] using
mul_le_mul_of_nonneg_left ih K.coe_nonneg)
have ht := (tendsto_pow_atTop_nhds_zero_of_lt_one K.coe_nonneg
(show (K:ℝ) < 1 by exact_mod_cast hK)).mul_const (dist x p)
rw [zero_mul] at ht
exact Metric.tendsto_atTop.mpr (fun δ hδ => by
obtain ⟨N, hN⟩ := eventually_atTop.mp (ht.eventually (gt_mem_nhds hδ))
exact ⟨N, fun n hn => (hbd n).trans_lt (hN n hn)⟩)
theorem strict_derivative_attracts {E : Type*} [NormedAddCommGroup E] [NormedSpace ℝ E]
{T : E → E} {p : E} {D : E →L[ℝ] E}
(hp : T p = p) (hD : HasStrictFDerivAt T D p) (hnorm : ‖D‖ < 1) :
∃ U : Set E, IsOpen U ∧ p ∈ U ∧ U ⊆ attractionBasin T p := by
have hn : ‖D‖₊ < 1 := by exact_mod_cast hnorm
obtain ⟨K, hDK, hK⟩ := exists_between hn
obtain ⟨U, hU, hlip⟩ := hD.exists_lipschitzOnWith_of_nnnorm_lt K hDK
exact local_contraction_attracts hp hK hU hlip
end SKGap
noncomputable section
open Set Function Real
open scoped Topology NNReal
namespace SKGap
section GradientDescent
variable {E : Type*} [NormedAddCommGroup E] [InnerProductSpace ℝ E]
theorem lipschitz_gradient_remainder {φ : E → ℝ} {G : E → E} {s : Set E}
(hs : Convex ℝ s) (hgrad : ∀ x ∈ s, HasFDerivAt φ (innerSL ℝ (G x)) x)
{L : ℝ≥0} (hG : LipschitzOnWith L G s) {x y : E} (hx : x ∈ s) (hy : y ∈ s) :
|φ y - φ x - inner ℝ (G x) (y-x)| ≤ (L:ℝ)*‖y-x‖^2 := by
let d := y-x
let ℓ : ℝ →ᵃ[ℝ] E := AffineMap.lineMap x y
let f := fun t : ℝ => φ (ℓ t) - t * inner ℝ (G x) d
let f' := fun t : ℝ => inner ℝ (G (ℓ t) - G x) d
have hℓ (t : ℝ) : ℓ t = x + t • d := by
simp only [ℓ, d, AffineMap.lineMap_apply_module]
module
have hmem (t : ℝ) (ht : t ∈ Icc (0:ℝ) 1) : ℓ t ∈ s :=
hs.mapsTo_lineMap hx hy ht
have hf (t : ℝ) (ht : t ∈ Icc (0:ℝ) 1) :
HasDerivWithinAt f (f' t) (Icc (0:ℝ) 1) t := by
have hd := ((hgrad (ℓ t) (hmem t ht)).comp_hasDerivAt t
AffineMap.hasDerivAt_lineMap).sub
((hasDerivAt_id t).mul_const (inner ℝ (G x) d))
convert! (hd.hasDerivWithinAt (s := Icc (0:ℝ) 1)) using 1
simp only [f', innerSL_apply_apply, inner_sub_left, d, one_mul]
have hb (t : ℝ) (ht : t ∈ Ico (0:ℝ) 1) :
‖f' t‖ ≤ (L:ℝ)*‖d‖^2 := by
have hdiff : ‖ℓ t-x‖ ≤ ‖d‖ := by
rw [hℓ, add_sub_cancel_left, norm_smul, Real.norm_eq_abs, abs_of_nonneg ht.1]
exact mul_le_of_le_one_left (norm_nonneg _) ht.2.le
have h := (hG.norm_sub_le (hmem t ⟨ht.1, ht.2.le⟩) hx).trans
(mul_le_mul_of_nonneg_left hdiff L.coe_nonneg)
calc
‖f' t‖ ≤ ‖G (ℓ t)-G x‖*‖d‖ := norm_inner_le_norm _ _
_ ≤ ((L:ℝ)*‖d‖)*‖d‖ := mul_le_mul_of_nonneg_right h (norm_nonneg d)
_ = _ := by ring
have h := norm_image_sub_le_of_norm_deriv_le_segment_01' hf hb
simpa only [f, ℓ, AffineMap.lineMap_apply_zero, AffineMap.lineMap_apply_one,
zero_mul, sub_zero, one_mul, Real.norm_eq_abs, d, sub_right_comm] using h
theorem gradient_step_strict_descent {φ : E → ℝ} {G : E → E} {s : Set E}
(hs : Convex ℝ s) (hgrad : ∀ x ∈ s, HasFDerivAt φ (innerSL ℝ (G x)) x)
{L : ℝ≥0} (hG : LipschitzOnWith L G s) {ε : ℝ} (hε : 0 < ε)
(hsmall : (L:ℝ)*ε < 1) {x : E} (hx : x ∈ s) (hstep : x-ε • G x ∈ s)
(hGx : G x ≠ 0) : φ (x-ε • G x) < φ x := by
have h := (le_abs_self _).trans (lipschitz_gradient_remainder hs hgrad hG hx hstep)
have he : x-ε • G x-x = -ε • G x := by module
rw [he, inner_smul_right, real_inner_self_eq_norm_sq,
norm_smul, Real.norm_eq_abs, abs_of_neg (neg_neg_of_pos hε)] at h
have hn : 0 < ‖G x‖^2 := sq_pos_of_pos (norm_pos_iff.mpr hGx)
have hc : 0 < ε*(1-(L:ℝ)*ε)*‖G x‖^2 := by positivity
nlinarith only [h, hc]
theorem gradient_step_derivative_sq_bound {D : E →L[ℝ] E} {c M ε : ℝ}
(_hc : 0 ≤ c) (_hM : 0 ≤ M) (hε : 0 ≤ ε)
(hcoercive : ∀ v, c*‖v‖^2 ≤ inner ℝ v (D v)) (hbound : ‖D‖ ≤ M)
(v : E) :
‖v-ε • D v‖^2 ≤ (1-2*ε*c+ε^2*M^2)*‖v‖^2 := by
have hD : ‖D v‖ ≤ M*‖v‖ := D.le_of_opNorm_le hbound v
have hD2 : ‖D v‖^2 ≤ M^2*‖v‖^2 := by
nlinarith [norm_nonneg (D v), mul_nonneg _hM (norm_nonneg v)]
have h := mul_le_mul_of_nonneg_left (hcoercive v) (show 0 ≤ 2*ε by positivity)
have h' := mul_le_mul_of_nonneg_left hD2 (sq_nonneg ε)
rw [norm_sub_sq_real, inner_smul_right, norm_smul, Real.norm_eq_abs,
abs_of_nonneg hε]
nlinarith only [h, h']
end GradientDescent
end SKGap
end
end
end
end OAI