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HexLLL.Reduced

The (δ, η)-reducedness predicate isLLLReduced and the short-vector bound short_vector_bound_of_size_bound: a reduced independent basis has a first row no longer than (1 / (δ - η²)) ^ (n - 1) (squared) times any nonzero lattice vector.

def Hex.Internal.LLLCore.basisNormSq {n m : Nat} (basis : Matrix Rat n m) (i : Fin n) :

Recover the squared norm of a Gram-Schmidt basis vector.

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    def Hex.isLLLReduced {n m : Nat} (b : Matrix Int n m) (δ η : Rat) :

    A basis is (δ, η)-LLL-reduced when it is size-reduced with bound η (|μ| ≤ η for every below-diagonal entry of the Gram-Schmidt coefficient matrix) and satisfies the Lovasz condition at every adjacent pair. The size-reduction clause is stored in squared form μ² ≤ η², which is equivalent to |μ| ≤ η exactly when η ≥ 0; every consumer supplies 1/2 ≤ η.

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    • One or more equations did not get rendered due to their size.
    Instances For
      theorem Hex.Internal.LLLCore.basisNormSq_nonneg {n m : Nat} (basis : Matrix Rat n m) (i : Fin n) :
      0 basisNormSq basis i

      The squared norm of any basis row is nonnegative, being a sum of squares of its rational entries.

      theorem Hex.Internal.LLLCore.stepBound {n m : Nat} (b : Matrix Int n m) {δ η : Rat} (hred : isLLLReduced b δ η) (_hδη : η * η < δ) (i : Nat) (hi : i + 1 < n) :

      Adjacent Gram-Schmidt norm bound from size reduction and Lovasz.

      theorem Hex.Internal.LLLCore.stepAlpha {n m : Nat} (b : Matrix Int n m) {δ η : Rat} (hred : isLLLReduced b δ η) (hδη : η * η < δ) (i : Nat) (hi : i + 1 < n) :

      Adjacent Gram-Schmidt norm bound in reciprocal form.

      theorem Hex.Internal.LLLCore.teleBound {n m : Nat} (b : Matrix Int n m) {δ η : Rat} (hred : isLLLReduced b δ η) (hδη : η * η < δ) (i : Nat) (hi : i < n) :

      Telescoped Gram-Schmidt norm bound from the first vector to index i.

      theorem Hex.Internal.LLLCore.basisNormSq_zero {n m : Nat} (b : Matrix Int n m) (hn : 0 < n) :

      First Gram-Schmidt basis vector identity: the 0-th Gram-Schmidt vector coincides with the 0-th input row, so their squared norms agree.

      theorem Hex.short_vector_bound_of_size_bound {n m : Nat} (b : Matrix Int n m) {δ η : Rat} (hli : b.independent) (hred : isLLLReduced b δ η) ( : 1 / 2 η) (hδη : η * η < δ) (hδ' : δ 1) (hn : 1 n) {v : Vector Int m} (hv : b.memLattice v) (hv' : v 0) :
      (b.row 0, ).normSq (1 / (δ - η * η)) ^ (n - 1) * v.normSq

      LLL short-vector core inequality, parameterized by the size-reduction bound η. For a (δ, η)-LLL-reduced basis with 1/2 ≤ η, η² < δ ≤ 1, the squared norm of the first row is at most (1 / (δ - η²)) ^ (n - 1) times the squared norm of any nonzero lattice vector. Combines LLLCore.teleBound with the lower bound on the smallest Gram-Schmidt vector contained in the lattice.

      theorem Hex.Internal.isLLLReduced.mono_η {n m : Nat} (b : Matrix Int n m) {δ η₁ η₂ : Rat} (hη₁ : 0 η₁) (hle : η₁ η₂) (hred : isLLLReduced b δ η₁) :
      isLLLReduced b δ η₂

      Monotonicity of the size-reduction bound: a (δ, η₁)-LLL-reduced basis is also (δ, η₂)-LLL-reduced for any η₂ ≥ η₁ ≥ 0. The Lovász side is unchanged; the size-reduced side relaxes since |μ| ≤ η₁ ≤ η₂ (in squared form, μ² ≤ η₁² ≤ η₂²).