Sharp complex coordinate Hlawka constant for p ≥ 90
OpenHlawkaSchatten.DiagonalCutoff.cutoff90For a real exponent and a vector , the coordinate norm is
For any three vectors in the same space, their triple deficit is
and their pair-deficit sum is
A real constant is uniformly admissible when for every triple and every finite dimension.
For , define
This cyclic constant is exactly the foundation's cyclicConstant.
It comes from the three vectors .
The fixed compact interval and the absolute value in are part of
the definition and remain unchanged in this task.
Cyclic definitions
For every real , the theorem asks for
This includes admissibility and uniform optimality, with all unequal-norm and zero triples allowed. Dimension zero is included. The supplied analytic proof has this scope; the Lean goal remains open.
import Definitions.Def_HlawkaSchatten_DiagonalConstruction_Basic import Definitions.Def_HlawkaSchatten_DiagonalConstruction_Cyclic import Definitions.Def_HlawkaSchatten_GapComparison open HlawkaSchatten HlawkaSchatten.DiagonalConstruction
theorem HlawkaSchatten.DiagonalCutoff.cutoff90 :
∀ p : ℝ, 90 ≤ p →
IsLeast {C : ℝ | ∀ n : ℕ,
HasHlawkaConstant (lpNorm p : (Fin n → ℂ) → ℝ) C}
(cyclicConstant p) := by sorry
Read-back
What the Lean code literally says, in plain math · GPT-6
For every real number satisfying , define, for each natural number and each function ,
where is the complex modulus, and define the real number
All powers in these formulas are real powers; both endpoints and are included. For the stipulated range , the denominator in this scalar formula is strictly positive throughout the interval, and its set of values is nonempty and bounded, so this is the ordinary real supremum. The declaration asserts that is the least real number such that, simultaneously for every natural number and every three functions , one has
with vector addition taken coordinate by coordinate in . Explicitly, this inequality holds with for every such , and every real number for which it holds for every such satisfies . The candidate has no separate sign restriction and must be the same constant for all dimensions and all triples, for the given . The boundary value is included. The dimension is also included: its coordinate set is empty, each vector is the unique empty function, the empty sum is , and the positive exponent gives , reducing the inequality to for every real . In every dimension the vectors may be zero or have zero coordinates; there are no normalization or nonzero hypotheses.
Confirmed by the mission captain (proposal self-audit).