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Add lean source and binary files (part 64)
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import Mathlib.Algebra.Polynomial.Eval.Defs
import OAI.Computability.UniqueGames.Reduction.CanonicalBodyTemplateLemmas
import OAI.Computability.UniqueGames.Reduction.GameEncodingSizeLemmas
import OAI.Computability.UniqueGames.Reduction.OuterCompletenessLemmas
namespace OAI
section
/-!
# Polynomial encoded length of the actual output
The encoder is the foundations team's unary, delimited forward-permutation
format. The instance is the actual list-based reduction, including canonical
body deduplication and every repeated edge occurrence. The polynomial's
coefficients depend only on the fixed gadget table and tuple dimensions.
These are output-length theorems. They do not assert a machine running-time
certificate for canonicalization, enumeration, or serialization.
-/
namespace UniqueGamesTheorem.Reduction.OutputSize
open ActualSource
open UniqueGamesTheorem.Integration
open UniqueGamesTheorem.Foundations
variable {n s d : Nat}
theorem explicitBodies_length_le (S : Source) (k s d : Nat) :
(ActualGame.explicitBodies S k s d).length ≤
S.occurrences ^ k * 2 ^ ((s + d) * (2 * k + 1)) := by
let := ActualGame.orbitBodyDecidableEq S k s d
exact (Encoding.imageVertices_length_le
(ActualEnumeration.queries S.occurrences k s d)
(ActualOrbit.body (ActualGame.canonical S k s d))).trans_eq
(ActualEnumeration.length_queries S.occurrences k s d)
def vertexCoefficient (k s d : Nat) : Nat :=
2 * CloneGap.distinctTriples.length ^ k * 2 ^ ((s + d) * (2 * k + 1))
def edgeCoefficient (k : Nat) (T : NoiseTables.Table s d) : Nat :=
CloneGap.distinctTriples.length ^ k *
2 ^ ((2 * k + 1) * (s + d + 1)) * T.vectors.length
private theorem collect_vertex_coefficient (m D k b : Nat) :
2 * ((m * D) ^ k * b) = (2 * D ^ k * b) * m ^ k := by
rw [Nat.mul_pow]
ac_rfl
private theorem collect_edge_coefficient (m D k b p : Nat) :
(m * D) ^ k * b * p = (D ^ k * b * p) * m ^ k := by
rw [Nat.mul_pow]
ac_rfl
theorem output_vertices_le (es : List (CloneGap.Equation (Fin n))) (hne : es ≠ [])
(k : Nat) (T : NoiseTables.Table s d) :
(UniformReduction.output es hne k T).vertices ≤
vertexCoefficient k s d * es.length ^ k := by
rw [UniformReduction.output_vertex_count]
have h := Nat.mul_le_mul_left 2
(explicitBodies_length_le (UniformReduction.source es hne) k s d)
calc
_ ≤ 2 * ((UniformReduction.source es hne).occurrences ^ k *
2 ^ ((s + d) * (2 * k + 1))) := h
_ = 2 * ((es.length * CloneGap.distinctTriples.length) ^ k *
2 ^ ((s + d) * (2 * k + 1))) := by rw [UniformReduction.source_occurrences]
_ = _ := collect_vertex_coefficient _ _ _ _
theorem output_constraints_eq (es : List (CloneGap.Equation (Fin n))) (hne : es ≠ [])
(k : Nat) (T : NoiseTables.Table s d) :
(UniformReduction.output es hne k T).constraints.length =
edgeCoefficient k T * es.length ^ k := by
rw [UniformReduction.output_constraint_count]
exact collect_edge_coefficient _ _ _ _ _
def sizeBound (vertexCoeff edgeCoeff alphabet tupleLength inputLength : Nat) : Nat :=
vertexCoeff * inputLength ^ tupleLength + alphabet +
edgeCoeff * inputLength ^ tupleLength + 3 +
edgeCoeff * inputLength ^ tupleLength *
(2 * (vertexCoeff * inputLength ^ tupleLength) + alphabet * (alphabet + 1))
theorem sizeBound_mono (vertexCoeff edgeCoeff alphabet tupleLength : Nat)
{a b : Nat} (hab : a ≤ b) :
sizeBound vertexCoeff edgeCoeff alphabet tupleLength a ≤
sizeBound vertexCoeff edgeCoeff alphabet tupleLength b := by
have hp := Nat.pow_le_pow_left hab tupleLength
have hv := Nat.mul_le_mul_left vertexCoeff hp
have he := Nat.mul_le_mul_left edgeCoeff hp
unfold sizeBound
exact Nat.add_le_add
(Nat.add_le_add_right (Nat.add_le_add (Nat.add_le_add_right hv alphabet) he) 3)
(Nat.mul_le_mul he (Nat.add_le_add_right (Nat.mul_le_mul_left 2 hv) _))
theorem output_bits_length_le (es : List (CloneGap.Equation (Fin n))) (hne : es ≠ [])
(k : Nat) (T : NoiseTables.Table s d) :
(Complexity.gameBits (UniformReduction.output es hne k T)).length ≤
sizeBound (vertexCoefficient k s d) (edgeCoefficient k T) (2 ^ s) k es.length := by
have h := GameEncodingSize.gameBits_length_le (UniformReduction.output es hne k T)
have hv := output_vertices_le es hne k T
rw [output_constraints_eq] at h
apply h.trans
unfold sizeBound
exact Nat.add_le_add
(Nat.add_le_add_right
(Nat.add_le_add_right (Nat.add_le_add_right hv _) _) 3)
(Nat.mul_le_mul_left _ (Nat.add_le_add_right (Nat.mul_le_mul_left 2 hv) _))
/-- An explicit polynomial for the actual serialized game. -/
noncomputable def outputPolynomial (k : Nat) (T : NoiseTables.Table s d) : Polynomial Nat :=
let V := Polynomial.C (vertexCoefficient k s d) * Polynomial.X ^ k
let E := Polynomial.C (edgeCoefficient k T) * Polynomial.X ^ k
V + Polynomial.C (2 ^ s) + E + Polynomial.C 3 +
E * (Polynomial.C 2 * V + Polynomial.C ((2 ^ s) * (2 ^ s + 1)))
theorem outputPolynomial_eval (k : Nat) (T : NoiseTables.Table s d) (m : Nat) :
(outputPolynomial k T).eval m =
sizeBound (vertexCoefficient k s d) (edgeCoefficient k T) (2 ^ s) k m := by
simp [outputPolynomial, sizeBound]
theorem output_bits_polynomial_in_occurrences
(es : List (CloneGap.Equation (Fin n))) (hne : es ≠ [])
(k : Nat) (T : NoiseTables.Table s d) :
(Complexity.gameBits (UniformReduction.output es hne k T)).length ≤
(outputPolynomial k T).eval es.length := by
rw [outputPolynomial_eval]
exact output_bits_length_le es hne k T
theorem output_bits_polynomial_in_input (input : SourceEncoding.Input)
(k : Nat) (T : NoiseTables.Table s d) :
(Complexity.gameBits
(UniformReduction.output input.equations input.nonempty k T)).length ≤
(outputPolynomial k T).eval (SourceEncoding.inputBits input).length := by
rw [outputPolynomial_eval]
exact (output_bits_length_le input.equations input.nonempty k T).trans
(sizeBound_mono _ _ _ _ (SourceEncoding.inputBits_length_ge_equations input))
/-- Fixed reduction parameters give one polynomial for every encoded input. -/
theorem fixed_parameters_output_size (k : Nat) (T : NoiseTables.Table s d) :
∃ p : Polynomial Nat, ∀ input : SourceEncoding.Input,
(Complexity.gameBits
(UniformReduction.output input.equations input.nonempty k T)).length ≤
p.eval (SourceEncoding.inputBits input).length :=
⟨outputPolynomial k T, fun input => output_bits_polynomial_in_input input k T⟩
end UniqueGamesTheorem.Reduction.OutputSize
end
end OAI