Borel Complexity of Normal Vectors
- Borel complexity computations are defined by sets that are Pi^0_3-complete, expressed as countable intersections of F_sigma sets with continuous reductions from any such set.
- The study employs recurrence sequences, Pisot bases, and symbolic dynamics to show that normality corresponds to uniform distribution mod 1 and is encoded in bi-infinite subshifts.
- These findings extend classical base‑b normal numbers to higher-dimensional systems, providing deep insights into descriptive set theory and the structure of recurrence relations.
A set in descriptive set theory is -complete if it can be expressed as a countable intersection of (i.e., countable unions of closed sets) subsets, and if every other set can be continuously reduced to it. The Borel complexity of sets of vectors normal for a fixed recurrence sequence provides deep insight into the structure of normality in extended numeration and dynamical regimes, connecting classical normal number sets with higher-dimensional recurrence behavior.
1. Normality in Recurrence Sequences and Companion Polynomials
For a recurrence sequence determined by the companion polynomial (e.g., ), the notion of a vector being "normal" means that the sequence is uniformly distributed modulo $1$: for every interval ,
The set of normal vectors for is (Kaneko et al., 27 Oct 2025). Under mild algebraic hypotheses (notably: no root on the unit circle), this set is Borel and specifically -complete.
2. Statement of Main Complexity Results
The principal theorem ((Kaneko et al., 27 Oct 2025), Theorem 1.1-1.2) states:
- For every and a fixed recurrence polynomial without roots on the unit circle, the set
is -complete in the Polish space parameterizing initial values.
- Special case: If is Pisot ( and all conjugates in modulus), then for
the set is -complete, generalizing classical base- normal numbers (Ki–Linton (Airey et al., 2018)) to all Pisot bases (Kaneko et al., 27 Oct 2025).
3. Methodology: Symbolic Encoding and Subshifts
A central idea is encoding recurrence sequences' fractional parts by infinite words over a suitably chosen alphabet (of size $2B+1$, with depending on 's coefficients). Each sequence can be recovered from
via a convolution kernel explicitly defined in terms of (Kaneko et al., 27 Oct 2025), Propositions 2.1–2.2.
This symbolic correspondence realizes a bi-infinite subshift , encoding all recurrence sequences. Normality (u.d. mod 1) for a vector translates to the genericity of the associated in : every finite block must appear in with the proper "generic" frequency determined by Lebesgue measure.
The subshift arising for is proved to have the right feeble specification property, a minimal form of mixing sufficient to guarantee that the set of generic points is -complete (Airey et al., 2018, Kaneko et al., 27 Oct 2025).
4. Descriptive Complexity and Completeness Arguments
The membership of is shown via cylinder-block frequency conditions:
- For each block and tolerance , the set of whose empirical frequency approaches the limit within is .
- "Normality" requires these block-frequency conditions hold for all and ; thus is a countable intersection of sets, i.e., .
-hardness follows from a Wadge reduction:
- The standard -complete set in the Baire space.
- A continuous coding is constructed so that is normal (in the sense above) if and only if .
- The construction uses concatenations of "good" and "zero" blocks whose lengths depend on ; long "good" blocks drive the sequence towards genericity, while bounded prevent genericity (Kaneko et al., 27 Oct 2025), Lemmas 4.1–4.3.
5. Relation to Classical Normal Numbers and Broader Impact
This work subsumes the Ki–Linton (Airey et al., 2018) result that the set of base- normal numbers is -complete and extends it to:
- Numbers normal in any Pisot base,
- Vectors normal for arbitrary recurrence relations.
For general numeration systems or continued fractions, symbolic codings yield subshifts of specification type, ensuring -completeness of the normal set (Airey et al., 2018).
The methodology applies broadly: any system where normality corresponds to genericity for an invariant measure on a subshift with right feeble specification property will have the normal set -complete.
6. Open Problems and Further Directions
Areas for further research include:
- Extending results to non-Pisot bases (where digit expansions lack specification),
- Joint normality for multiple recurrence sequences, involving higher complexity classes such as ,
- Finer descriptive complexity above for systems lacking strong mixing or with more irregular limiting behavior.
7. Table: Main Normal Sets by Setting
| System | Object(s) | Completeness Level | Reference |
|---|---|---|---|
| Base- normal | -complete | (Airey et al., 2018) | |
| Pisot normal | ( Pisot) | -complete | (Kaneko et al., 27 Oct 2025) |
| Recurrence normal | -complete | (Kaneko et al., 27 Oct 2025) |
References
- H. Kaneko, B. Mance, "Borel Complexity of the set of vectors normal for a fixed recurrence sequence" (Kaneko et al., 27 Oct 2025)
- D. Airey, S. Jackson, D. Kwietniak, B. Mance, "Borel complexity of sets of normal numbers via generic points in subshifts with specification" (Airey et al., 2018)
- H. Ki, T. Linton, "Normal numbers and subsets of with given densities," Fund. Math. 144 (1994), 163–179.
In summary, for broad classes of recurrence and numeration systems—including all Pisot bases—the set of normal vectors or numbers is precisely -complete in the Borel hierarchy, as established by Kaneko–Mance (Kaneko et al., 27 Oct 2025) and related works. This provides a robust uniform answer for normality in analytic and dynamical settings, marking a boundary in the complexity of natural number-theoretic properties.