The result
A basis that bounds every coefficient.
Let p be a real homogeneous polynomial of positive even degree d, positive away from zero. Its symmetric multilinear polarization A satisfies A(x, …, x) = p(x).
There is a basis z1, …, zm such that
0 < A(zj1, …, zjd) < 1
for every mixed tuple. Pure tuples have value one. This gives the absolute-value bound asked in Problem 11, printed page 3182, of the 2019 Oberwolfach report.
The proof in three steps
Minimize on a sphere
A sphere-minimizing direction has a strictly positive transverse quadratic slice of the polarization.
Cluster a basis nearby
Take the minimizing vector and small independent transverse perturbations. They form a basis for every nonzero perturbation size.
Compare a polynomial gap
For each mixed tuple, the desired gap has a strictly positive quadratic term. Finitely many tuples share one sufficiently small perturbation.
Check the result
A short proof, with exact checks.
The universal statement follows from the analytic proof. A separate derivation uses positive definite bilinear slices, Cauchy–Schwarz and a finite maximum argument.
The Python companion checks 12 rational examples, covering 120 coefficient classes, with 110 independent polarization cross-checks. It also checks the quadratic identity in degrees 2–24 and rejects two deliberately invalid certificates.
python3 verification/verify.pyPython 3.9+; no extra dependencies. These finite checks are not a formal proof of the universal theorem.
- Three-page paperPDF · complete proof
- Source & verification packageLaTeX, scripts, certificates and audits
- Fresh preprint-readiness reviewsThree independent rounds and documented dispositions
- Verification reportAssumptions, proof map and boundary checks
- Independent Cauchy–Schwarz proofA stronger local cone statement
- Priority auditSources, queries, findings and limits
- Download checksumsSHA-256
Context & attribution
An answer to the stated question.
Brandes's 2015 paper discusses pseudo-diagonal forms and proves the quadratic case. The 2019 problem asks about general positive definite forms after a change of variables.
The literature audit found no earlier full resolution. It cannot rule out unpublished or differently formulated antecedents.
Generative AI supplied the initial candidate and assisted the independent internal checks, research and writing.
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