openAI-math-dataset / lean /OAI /Probability /FreeIsing /Trees /ConnectedPercolation.lean
roseking's picture
Add lean source and binary files (part 122)
b317718 verified
Raw History Blame Contribute Delete
6.81 kB
import OAI.Probability.FreeIsing.Trees.Parents
namespace OAI
noncomputable section
namespace Problem367.ConnectedPercolation
def deepestVertexOr {d : ℕ} (r : TreeVertex d) (S : Finset (TreeVertex d)) : TreeVertex d :=
if h : S.Nonempty then
Classical.choose (S.exists_max_image (fun v => v.1.length) h)
else r
lemma deepestVertexOr_mem {d : ℕ} (r : TreeVertex d) (S : Finset (TreeVertex d))
(h : S.Nonempty) : deepestVertexOr r S ∈ S := by
rw [deepestVertexOr, dite_eq_left h]
exact (Classical.choose_spec (S.exists_max_image (fun v => v.1.length) h)).1
lemma le_deepestVertexOr_length {d : ℕ} (r : TreeVertex d)
(S : Finset (TreeVertex d)) (h : S.Nonempty)
{v : TreeVertex d} (hv : v ∈ S) : v.1.length ≤ (deepestVertexOr r S).1.length := by
rw [deepestVertexOr, dite_eq_left h]
exact (Classical.choose_spec (S.exists_max_image (fun v => v.1.length) h)).2 v hv
def prefixCandidates {d : ℕ} (D : Finset (TreeVertex d)) (x : TreeVertex d) :
Finset (TreeVertex d) := by
classical
exact D.filter (fun v => v.1 <+: x.1)
@[simp] lemma mem_prefixCandidates {d : ℕ} (D : Finset (TreeVertex d))
(x v : TreeVertex d) : v ∈ prefixCandidates D x ↔ v ∈ D ∧ v.1 <+: x.1 := by
classical
simp [prefixCandidates]
def gate {d : ℕ} (D : Finset (TreeVertex d)) (r x : TreeVertex d) : TreeVertex d :=
deepestVertexOr r (prefixCandidates D x)
lemma gate_of_mem {d : ℕ} {D : Finset (TreeVertex d)} (r : TreeVertex d)
{x : TreeVertex d} (hx : x ∈ D) : gate D r x = x := by
have hx' : x ∈ prefixCandidates D x :=
(mem_prefixCandidates D x x).mpr ⟨hx, List.prefix_refl _⟩
have hne : (prefixCandidates D x).Nonempty := ⟨x, hx'⟩
have hmem := (mem_prefixCandidates D x _).mp
(deepestVertexOr_mem r (prefixCandidates D x) hne)
exact Subtype.ext (hmem.2.eq_of_length_le
(le_deepestVertexOr_length r (prefixCandidates D x) hne hx'))
lemma gate_of_no_prefix {d : ℕ} {D : Finset (TreeVertex d)} (r x : TreeVertex d)
(h : ∀ v ∈ D, ¬v.1 <+: x.1) : gate D r x = r := by
have hempty : prefixCandidates D x = ∅ := by
apply Finset.eq_empty_iff_forall_notMem.mpr
intro v hv
obtain ⟨hvD, hvx⟩ := (mem_prefixCandidates D x v).mp hv
exact h v hvD hvx
simp [gate, hempty, deepestVertexOr]
lemma prefixCandidates_append_of_not_mem {d : ℕ} (D : Finset (TreeVertex d))
{x y : TreeVertex d} {c : Fin d} (hxy : y.1 = x.1 ++ [c]) (hy : y ∉ D) :
prefixCandidates D x = prefixCandidates D y := by
classical
ext v
simp only [mem_prefixCandidates]
constructor
· rintro ⟨hv, hvx⟩
refine ⟨hv, hvx.trans ?_⟩
rw [hxy]
exact List.prefix_append _ _
· rintro ⟨hv, hvy⟩
refine ⟨hv, ?_⟩
have hne : v ≠ y := fun h => hy (h ▸ hv)
have hlt : v.1.length < y.1.length := by
have hle := hvy.length_le
have hneq : v.1.length ≠ y.1.length :=
fun h => hne (Subtype.ext (hvy.eq_of_length h))
omega
apply List.prefix_of_prefix_length_le hvy
· rw [hxy]
exact List.prefix_append _ _
· have hlen : y.1.length = x.1.length + 1 := by simp [hxy]
omega
lemma gate_append_cases {d : ℕ} {D : Finset (TreeVertex d)}
(hD : ConnectedFinset D) {r : TreeVertex d} (hr : r ∈ D)
(hmin : ∀ w ∈ D, r.1.length ≤ w.1.length)
{x y : TreeVertex d} {c : Fin d} (hxy : y.1 = x.1 ++ [c]) :
(x ∈ D ∧ y ∈ D) ∨ gate D r x = gate D r y := by
classical
by_cases hy : y ∈ D
· by_cases hx : x ∈ D
· exact Or.inl ⟨hx, hy⟩
· right
have hp : parentVertex y = x := by
apply Subtype.ext
simp [parentVertex, hxy]
have hyr : y = r := by
by_contra hne
exact hx (hp ▸ hD.parent_mem_of_ne_min hr hmin hy hne)
rw [gate_of_mem r hy, hyr]
apply gate_of_no_prefix
intro v hv hvx
have hlen : r.1.length = x.1.length + 1 := by rw [← hyr]; simp [hxy]
have hvlen := hvx.length_le
have hrlen := hmin v hv
omega
· right
unfold gate
rw [prefixCandidates_append_of_not_mem D hxy hy]
lemma gate_adj_cases {d : ℕ} {D : Finset (TreeVertex d)}
(hD : ConnectedFinset D) {r : TreeVertex d} (hr : r ∈ D)
(hmin : ∀ w ∈ D, r.1.length ≤ w.1.length)
{x y : TreeVertex d} (hxy : treeAdj x y) :
(x ∈ D ∧ y ∈ D) ∨ gate D r x = gate D r y := by
rcases hxy with ⟨c, hc⟩ | ⟨c, hc⟩
· exact gate_append_cases hD hr hmin hc
· rcases gate_append_cases hD hr hmin hc with h | h
· exact Or.inl h.symm
· exact Or.inr h.symm
end Problem367.ConnectedPercolation
namespace Problem367
theorem ConnectedFinset.reflTransGen_restrict_iff {d : ℕ}
{D : Finset (TreeVertex d)} (hD : ConnectedFinset D)
{R : TreeVertex d → TreeVertex d → Prop}
(hR : ∀ ⦃x y⦄, R x y → treeAdj x y)
{u v : TreeVertex d} (hu : u ∈ D) (hv : v ∈ D) :
Relation.ReflTransGen R u v ↔
Relation.ReflTransGen (fun x y => x ∈ D ∧ y ∈ D ∧ R x y) u v := by
constructor
· intro h
obtain ⟨r, hr, hmin⟩ := D.exists_min_image (fun w => w.1.length) hD.1
let π := ConnectedPercolation.gate D r
have hmap : ∀ ⦃x y⦄, Relation.ReflTransGen R x y →
Relation.ReflTransGen (fun a b => a ∈ D ∧ b ∈ D ∧ R a b) (π x) (π y) := by
intro x y hxy
induction hxy with
| refl => exact .refl
| @tail y z hxy hyz ih =>
rcases ConnectedPercolation.gate_adj_cases hD hr hmin (hR hyz) with hmem | heq
· have hπy : π y = y := ConnectedPercolation.gate_of_mem r hmem.1
have hπz : π z = z := ConnectedPercolation.gate_of_mem r hmem.2
rw [hπy] at ih
rw [hπz]
exact ih.tail ⟨hmem.1, hmem.2, hyz⟩
· change π y = π z at heq
exact heq ▸ ih
simpa only [π, ConnectedPercolation.gate_of_mem r hu,
ConnectedPercolation.gate_of_mem r hv] using hmap h
· intro h
exact Relation.ReflTransGen.mono
(fun x y (h : x ∈ D ∧ y ∈ D ∧ R x y) => h.2.2) u v h
theorem ConnectedFinset.cluster_inter_eq {d : ℕ}
{D : Finset (TreeVertex d)} (hD : ConnectedFinset D)
{R : TreeVertex d → TreeVertex d → Prop}
(hR : ∀ ⦃x y⦄, R x y → treeAdj x y)
{u : TreeVertex d} (hu : u ∈ D) :
{v | Relation.ReflTransGen R u v} ∩ (D : Set (TreeVertex d)) =
{v | Relation.ReflTransGen (fun x y => x ∈ D ∧ y ∈ D ∧ R x y) u v} := by
ext v
constructor
· rintro ⟨hp, hv⟩
exact (hD.reflTransGen_restrict_iff hR hu hv).mp hp
· intro hp
have hv : v ∈ D := by
induction hp with
| refl => exact hu
| tail _ h _ => exact h.2.1
exact ⟨(hD.reflTransGen_restrict_iff hR hu hv).mpr hp, hv⟩
end Problem367
end
end OAI