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Algorithmic randomness in harmonic analysis

Published: January 6, 2026 | arXiv ID: 2601.03239v1

By: Johanna N. Y. Franklin, Lucas E. Rodriguez, Diego A. Rojas

Potential Business Impact:

Makes math patterns predictable using randomness.

Business Areas:
A/B Testing Data and Analytics

Within the last fifteen years, a program of establishing relationships between algorithmic randomness and almost-everywhere theorems in analysis and ergodic theory has developed. In harmonic analysis, Franklin, McNicholl, and Rute characterized Schnorr randomness using an effective version of Carleson's Theorem. We show here that, for computable $1<p<\infty$, the reals at which the Fourier series of a weakly computable vector in $L^p[-π,π]$ converges are precisely the Martin-Löf random reals. Furthermore, we show that radial limits of the Poisson integral of an $L^1(\mathbb{R})$-computable function coincide with the values of the function at exactly the Schnorr random reals and that radial limits of the Poisson integral of a weakly $L^1(\mathbb{R})$-computable function coincide with the values of the function at exactly the Martin-Löf random reals.

Page Count
16 pages

Category
Mathematics:
Logic