Bobrowski–Skraba strong universality conjecture
For every admissible random point-cloud sampling model, ambient dimension , homological degree , and filtration type, let be the persistence pairs with , and define the empirical measure of log-log persistence ratios by . The strong universality conjecture asserts that, after the prescribed data-dependent additive centering , the centered measures converge weakly to one and the same universal limiting probability law, independently of the sampling model, , , and the filtration; the conjectured universal law is a left-skewed Gumbel distribution.
References
Primary source
Additional references
Progress summary
An unrefereed preprint claims to refute the conjecture by showing that the proposed universal law differs between the square and cube, but the claim has not been independently verified.
Bobrowski and Skraba proposed a strong universality principle for persistence-ratio distributions in random point-cloud filtrations. It predicts universality beyond the fixed dimension, homological degree, and filtration covered by the weaker conjecture.
Known results
- The 2022 formulation presented strong universality as a conjecture supported by experiments.
- A 2024 paper claims the weaker result: for fixed dimension , degree , and filtration type, iid point processes have a universal limiting empirical distribution.
October 2026 counterexample
On October 6, 2026, a report summarized Eunwoo Heo's preprint as showing that degree-one Čech persistence has limiting quantities for the square and for the cube, forcing different limiting laws and hence contradicting strong universality. A separate 2026 preprint claims a broader universality theorem but does not address these quantities.
Current status (as of October 2026): the weaker fixed-parameter universality result is claimed in the literature, while strong universality is claimed refuted by Heo's counterexample, whose proof remains unverified.
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