Holomorphic certification on real subspaces
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Abstract
We study when a nonnegative Hermitian quartic enters the hierarchy of holomorphic squared-norm certificates obtained by multiplication by powers of its squared norm. Deciding eventual membership is coNP-hard even for integer quartics with polynomially bounded coefficients and exactly one negative coefficient eigenvalue. A sign-cube criterion on complexifications of real subspaces supplies the reduction: avoiding the sign cube gives stabilization, while a sign vector excludes every intrinsic nonzero polynomial multiplier. We also quantify the degree cost near this geometric boundary. For bounded real matrices imposing soft linear constraints, the least degree grows uniformly as the inverse square of the smallest signed constraint residual. A logarithmic curvature obstruction gives the lower bound, matched by quantitative classical stabilization. On a weighted two-dimensional hyperplane family, complete finite-matrix bounds determine the exact leading constant. These results connect a restricted computational decision with both a uniform boundary scale and a sharp fixed-dimensional example.
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- holomorphic-certification-on-real-subspaces.pdf120.5 KiB · pdf
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Available editions
- Edition 1 · 2026-10-30 · public
Research details
- Subjects
- Mathematics · Computer Science & Software Systems · Linear Algebra and Matrix Theory · Complex Analysis · Algorithms and Complexity
- Keywords
- Hermitian forms, holomorphic squared norms, certificate complexity, stabilization degree, positive polynomials
- Manuscript date
- 2026-10-27
- Reader reuse
- none
Scope
Sign-cube classification, restricted computational hardness and uniform and sharp boundary degree laws for holomorphic squared-norm certification.
Disclosures
OpenAI tools assisted mathematical exploration, proof checks, literature comparison, code and manuscript preparation. The author takes responsibility for the contents.
Reproduction
The 13-page paper, editable LaTeX source, bibliography, reader instructions and reproduction code are supplied. Analytic proofs establish the general theorems; the accompanying programs provide finite reproducible examples.