Geometric Sampling Does Not Determine Regularized R-Diagonal Laws
Manuscript 14 October 2026 · Online 14 October 2026
Abstract
For every \(s_0\gt 0\), \(q\gt 1\) and finite integer \(K\geq 1\), we construct a continuum of distinct affiliated \(R\)-diagonal laws with identical joint star-moments and identical first \(K\) alternating cumulants of \(c(1+s c^*c)^{-1/2}\) at every scale \(s=s_0q^k\), \(k\in\mathbb{Z}\). All absolute moments are finite.
A finite combination of classical lognormal Stieltjes perturbations gives an explicit resolvent difference with prescribed finite-order zeros on the grid and an exact higher separating cumulant. A Blaschke-Jensen argument gives a sufficient uniqueness condition for other sample sets. This is a complete scoped reconstruction counterexample, not a new radial analytic \(R\)-transform or closure of the entire AIM question. Classical inputs are credited. The preprint is self-audited, unrefereed and AI-assisted; independent review, formal verification and absolute priority are not claimed.
Record
- Affiliation
- Mercury Software GmbH
- Contact
- [email protected] · GitHub
- Result
- Complete scoped counterexample
- Categories
- math.PR · math.OA · math.CV
- Manuscript
- 14 October 2026
- Online release
- 14 October 2026
- Version
- 1.0
- License
- Creative Commons Attribution 4.0 International
Files and verification
The PDF is the canonical reading copy. The source archive contains the LaTeX manuscript, bibliography, reproducibility material, and audit documents without build artefacts.
Citation
Alper Ferudun, “Geometric Sampling Does Not Determine Regularized R-Diagonal Laws,” EulerSolve Research Papers, AIM-PROBABILITY-0133, 2026. https://doi.org/10.5281/zenodo.23362668.
BibTeX
@misc{ferudun2026rdiagonalsampling,
author = {Ferudun, Alper},
title = {Geometric Sampling Does Not Determine Regularized R-Diagonal Laws},
year = {2026},
howpublished = {EulerSolve Research Papers},
url = {https://eulersolve.org/papers/aim-probability-0133/},
doi = {10.5281/zenodo.23362668},
note = {AIM-PROBABILITY-0133; unrefereed preprint}
}