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import OAI.Computability.UniqueGames.PCP.ZigzagGraphsLemmas
namespace OAI
section
namespace UniqueGamesTheorem.Foundations.PCP.ExpanderTables
open PoweringWalks SpectralReturn
def rowIndex (v d : Nat) : Fin v × Fin d ≃ Fin (v * d) := finProdFinEquiv
theorem rowIndex_val (v d : Nat) (x : Fin v × Fin d) :
(rowIndex v d x).val = x.2.val + d * x.1.val := rfl
/-- Stored reverse-dart indices, with a proof of the finite involution law. -/
structure Table (v d : Nat) where
rows : Vector (Fin (v * d)) (v * d)
involutive : Function.Involutive (fun i : Fin (v * d) => rows[i])
def reverseIndex {v d : Nat} (table : Table v d) (i : Fin (v * d)) : Fin (v * d) :=
table.rows[i]
def lookup {v d : Nat} (table : Table v d) (x : Fin v × Fin d) : Fin v × Fin d :=
(rowIndex v d).symm (reverseIndex table (rowIndex v d x))
theorem lookup_involutive {v d : Nat} (table : Table v d) :
Function.Involutive (lookup table) := by
intro x
simp only [lookup, Equiv.apply_symm_apply]
exact (congrArg (rowIndex v d).symm (table.involutive (rowIndex v d x))).trans
((rowIndex v d).symm_apply_apply x)
def graph {v d : Nat} (table : Table v d) : PortGraph (Fin v) (Fin d) where
rot := ZigzagGraphs.involutionEquiv (lookup table) (lookup_involutive table)
rot_involutive := lookup_involutive table
@[simp] theorem graph_rot {v d : Nat} (table : Table v d) (x : Fin v × Fin d) :
(graph table).rot x = lookup table x := rfl
def ofGraph {v d : Nat} (G : PortGraph (Fin v) (Fin d)) : Table v d where
rows := Vector.ofFn (fun i => rowIndex v d (G.rot ((rowIndex v d).symm i)))
involutive := by
intro i
simp only [Fin.getElem_fin, Vector.getElem_ofFn, Fin.eta, Equiv.symm_apply_apply]
exact (congrArg (rowIndex v d) (G.rot_involutive ((rowIndex v d).symm i))).trans
((rowIndex v d).apply_symm_apply i)
@[simp] theorem lookup_ofGraph {v d : Nat} (G : PortGraph (Fin v) (Fin d))
(x : Fin v × Fin d) : lookup (ofGraph G) x = G.rot x := by
simp only [lookup, reverseIndex, ofGraph, Fin.getElem_fin, Vector.getElem_ofFn, Fin.eta,
Equiv.symm_apply_apply]
private theorem graph_ext {V D : Type*} {G H : PortGraph V D}
(h : ∀ x, G.rot x = H.rot x) : G = H := by
have hr : G.rot = H.rot := Equiv.ext h
cases G
cases H
cases hr
rfl
@[simp] theorem graph_ofGraph {v d : Nat} (G : PortGraph (Fin v) (Fin d)) :
graph (ofGraph G) = G := graph_ext (lookup_ofGraph G)
theorem row_count {v d : Nat} (table : Table v d) : table.rows.toList.length = v * d := by
simp
/-- Explicit mixed-radix vertex coordinates for one square/zigzag step. -/
def vertexIndex (v q : Nat) : Fin v × (Fin q × Fin q) ≃ Fin (v * (q * q)) :=
(Equiv.prodCongr (Equiv.refl _) (rowIndex q q)).trans (rowIndex v (q * q))
/-- The actual square/zigzag graph, expressed in the table's integer coordinates. -/
def stepGraph {v d : Nat} (G : Table v (d * d))
(H : Table ((d * d) * (d * d)) d) :
PortGraph (Fin (v * ((d * d) * (d * d)))) (Fin (d * d)) :=
GraphTransport.reindex
(ZigzagGraphs.zigzag (ZigzagGraphs.square (graph G))
(GraphTransport.reindex (graph H) (rowIndex (d * d) (d * d)).symm (Equiv.refl _)))
(vertexIndex v (d * d)) (rowIndex d d)
/-- Materialize every row of the next table in the declared order. -/
def step {v d : Nat} (G : Table v (d * d))
(H : Table ((d * d) * (d * d)) d) :
Table (v * ((d * d) * (d * d))) (d * d) := ofGraph (stepGraph G H)
/-- A row uses exactly the displayed four lookups in already stored tables. -/
def stepLookup {v d : Nat} (G : Table v (d * d))
(H : Table ((d * d) * (d * d)) d)
(x : Fin (v * ((d * d) * (d * d))) × Fin (d * d)) :
Fin (v * ((d * d) * (d * d))) × Fin (d * d) :=
let vc := (rowIndex v ((d * d) * (d * d))).symm x.1
let ports := (rowIndex d d).symm x.2
let first := lookup H (vc.2, ports.1)
let squarePorts := (rowIndex (d * d) (d * d)).symm first.1
let outerFirst := lookup G (vc.1, squarePorts.1)
let outerSecond := lookup G (outerFirst.1, squarePorts.2)
let last := lookup H (rowIndex (d * d) (d * d) (outerSecond.2, outerFirst.2), ports.2)
(rowIndex v ((d * d) * (d * d)) (outerSecond.1, last.1),
rowIndex d d (last.2, first.2))
theorem lookup_step {v d : Nat} (G : Table v (d * d))
(H : Table ((d * d) * (d * d)) d)
(x : Fin (v * ((d * d) * (d * d))) × Fin (d * d)) :
lookup (step G H) x = stepLookup G H x := by
simp [step, stepGraph, GraphTransport.reindex,
Equiv.trans_apply, Equiv.prodCongr_apply,
Equiv.prodCongr_symm, Equiv.refl_apply, vertexIndex, Equiv.apply_symm_apply,
ZigzagGraphs.zigzag, ZigzagGraphs.square, ZigzagGraphs.involutionEquiv,
ZigzagGraphs.cloudFirst, ZigzagGraphs.crossCloud, graph_rot,
stepLookup, Prod.map, Equiv.symm_symm]
all_goals repeat' constructor
theorem step_certificate {v d : Nat} [NeZero v] [NeZero d]
(G : Table v (d * d)) (H : Table ((d * d) * (d * d)) d)
(hG : SpectralCertificate (graph G) (1 / 2 : ℝ))
(hH : SpectralCertificate (graph H) (1 / 100 : ℝ)) :
SpectralCertificate (graph (step G H)) (1 / 2 : ℝ) := by
rw [step, graph_ofGraph]
apply GraphTransport.reindex_spectralCertificate
apply ZigzagSpectral.square_zigzag_halfCertificate
· exact hG
· exact GraphTransport.reindex_spectralCertificate _ _ _ _ hH
def initial (d : Nat) : Table 1 (d * d) :=
ofGraph { rot := Equiv.refl _, rot_involutive := fun _ => rfl }
theorem initial_certificate (d : Nat) :
SpectralCertificate (graph (initial d)) (1 / 2 : ℝ) := by
refine ⟨by norm_num, by norm_num, ?_⟩
intro f hf
have hfun : f = fun _ => f 0 := funext (fun x => congrArg f (Subsingleton.elim x 0))
have hm : mean f = f 0 := (congrArg mean hfun).trans (mean_const _)
have hz : f 0 = 0 := hm.symm.trans hf
rw [hfun, hz]
simp [energy, mean, averagingOperator]
def vertexCount (q : Nat) : Nat → Nat
| 0 => 1
| n + 1 => vertexCount q n * (q * q)
theorem vertexCount_eq (q n : Nat) : vertexCount q n = (q * q) ^ n := by
induction n with
| zero => rfl
| succ n ih => simp only [vertexCount, ih, pow_succ]
theorem vertexCount_positive {q : Nat} (hq : 0 < q) (n : Nat) :
0 < vertexCount q n := by
rw [vertexCount_eq]
exact Nat.pow_pos (Nat.mul_pos hq hq)
/-- A bottom-up vector of rotation rows. The recursive result is passed once
to `step`, whose row formula reads only that already materialized table. -/
def family {d : Nat} (H : Table ((d * d) * (d * d)) d) :
(n : Nat) → Table (vertexCount (d * d) n) (d * d)
| 0 => initial d
| n + 1 => step (family H n) H
theorem family_certificate {d : Nat} [NeZero d]
(H : Table ((d * d) * (d * d)) d)
(hH : SpectralCertificate (graph H) (1 / 100 : ℝ)) (n : Nat) :
SpectralCertificate (graph (family H n)) (1 / 2 : ℝ) := by
induction n with
| zero => exact initial_certificate d
| succ n ih =>
let : NeZero (vertexCount (d * d) n) :=
⟨Nat.ne_of_gt (vertexCount_positive (Nat.mul_pos (NeZero.pos d) (NeZero.pos d)) n)⟩
exact step_certificate _ _ ih hH
theorem family_row_count {d : Nat} (H : Table ((d * d) * (d * d)) d) (n : Nat) :
(family H n).rows.toList.length = ((d * d) * (d * d)) ^ n * (d * d) := by
rw [row_count, vertexCount_eq]
/-- The only selected data is one fixed finite table, independent of the input. -/
theorem exists_base_table : ∃ H : Table
((Expanders.baseDegree * Expanders.baseDegree) *
(Expanders.baseDegree * Expanders.baseDegree)) Expanders.baseDegree,
SpectralCertificate (graph H) (1 / 100 : ℝ) := by
classical
have hv : Fintype.card ExpanderFamily.CloudPort =
(Expanders.baseDegree * Expanders.baseDegree) *
(Expanders.baseDegree * Expanders.baseDegree) := by
rw [ExpanderFamily.card_cloudPort]
unfold ExpanderFamily.growth
ring
let vertices := Fintype.equivFinOfCardEq hv
let ports := Fintype.equivFinOfCardEq Expanders.card_basePort
let G := GraphTransport.reindex ExpanderFamily.baseOnCloud vertices ports
refine ⟨ofGraph G, ?_⟩
rw [graph_ofGraph]
exact GraphTransport.reindex_spectralCertificate _ _ _ _
ExpanderFamily.baseOnCloud_certificate
end UniqueGamesTheorem.Foundations.PCP.ExpanderTables
end
end OAI
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