The Extremum Stack is a Minimal Sucient Statistic for Rate-Independent Functionals: A Kolmogorov Complexity Characterisation
Abstract
We prove that the extremum stack Π_n of a discrete sequence u_{0:n} ∈ G_L^{n+1} is a minimal sufficient statistic for the class R of all computable, causal, rate-independent functionals, in the sense of Kolmogorov complexity. Specifically, we establish: K(Π_n) − O(1) ≤ K_R(u_{0:n}) ≤ K(Π_n) + O(1), where K_R(u_{0:n}) is the length of the shortest program answering every query in R, and the O(1) overhead is independent of both the sequence length n and the stack depth k. Sufficiency follows from the classical wiping property of the Preisach hysteresis operator. Minimality is established via a finite indicator family whose rate-independence is verified explicitly. Any compression of a hysteresis-driven stream that preserves the full class R must therefore retain at least K(Π_n) − O(1) bits; the stack-based compression algorithm implied by the result carries a Kolmogorov optimality guarantee absent from standard time-series compression methods. Submitted to Information Processing Letters (Elsevier).
Fields of Study & Subjects
Computability
Logic
AI Algorithms
Machine Learning and Algorithms
Algorithms and Data Compression
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 16 May 2026
- Language
- EN
- Document type
- Preprint