Separation Between the Ordinary and Strong Kreiss Constants
Question 6.1 of Chalmoukis, Tsikalas and Yakubovich asks how far the Power boundedness constant $P(T)$ of a matrix can exceed its ordinary Kreiss constant $K(T)$. Answered more strongly: for every $K > 1$ there are matrices whose Cayley transforms satisfy $K(C_h(A_{n,h})) \le K$ while the strong Kreiss constant satisfies $K_s(C_h(A_{n,h})) \ge \tfrac{1}{2}Cn^{\alpha_K}$ with $\alpha_K = (K-1)/(C+K-1)$. Since $P(T)\geq K_s(T)$, this solves the question. Moreover, since the Kreiss matrix theorem gives $K_s(T) \le P(T) \le edK(T)$ in dimension $d$, the exponent $\alpha < 1$ is optimal up to an arbitrarily small power loss.
Exact FrontierDelta
Scope and record
Occurred: Aug 19, 2026
Delta type: SOURCE CLAIM
Assumptions: VibeMathed verification: unreviewed. Publication: preprint. AI contribution: ai-assisted. Imported under CC BY 4.0.
Canonical aliases: Separation Between the Ordinary and Strong Kreiss Constants · Kreiss constant separation
Confidence: Not scored
Registry verification: unreviewed · preprint · resolved
Attribution
VibeMathed
registry · event recorded by
Emiel Lorist
human · human collaborator
Martin Meyries
human · human collaborator
Mark Veraar
human · human collaborator
Claude Fable
model · ai model contributor · OpenAI
ChatGPT 5.6 Pro
model · ai model contributor · OpenAI
Lineage and corrections
This event attributed to Emiel Lorist
This event attributed to Martin Meyries
This event attributed to Mark Veraar
This event attributed to ChatGPT 5.6 Pro
This event attributed to Claude Fable