Ultrametric Structures and Norm-Based p-Adic Operations for Hierarchical and Robust Information Processing

In this article, we propose a non-archimedean framework for information processing based on the arithmetic and geometry of p-adic numbers. Exploiting the ultrametric structure of Qp, we introduce norm-based p-adic operations inspired by classical logical connectives that exhibit strong stability under perturbations. The non-archimedean nature of the p-adic norm induces natural scale separation and clustering properties, leading to robust information encoding and spectral localization. Using p-adic Fourier analysis, we show that hierarchical signals decompose into disjoint frequency bands, enabling multiscale information processing with reduced interference. These results provide a mathematical foundation for robust and hierarchical information architectures, with potential applications in signal processing, error-tolerant computation, and non-classical information systems.

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Publication Details

Journal
Mathematics
Published
2026-04-13
DOI
https://doi.org/10.3390/math14081284
Primary Topic
advanced mathematical theories
Type
article
Field-Weighted Citation Impact
0.00

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article

Ultrametric Structures and Norm-Based p-Adic Operations for Hierarchical and Robust Information Processing

Anselmo Torresblanca-Badillo
Mathematics
advanced mathematical theories
article

Ultrametric Structures and Norm-Based p-Adic Operations for Hierarchical and Robust Information Processing

Anselmo Torresblanca-Badillo
article en

Abstract

In this article, we propose a non-archimedean framework for information processing based on the arithmetic and geometry of p-adic numbers. Exploiting the ultrametric structure of Qp, we introduce norm-based p-adic operations inspired by classical logical connectives that exhibit strong stability under perturbations. The non-archimedean nature of the p-adic norm induces natural scale separation and clustering properties, leading to robust information encoding and spectral localization. Using p-adic Fourier analysis, we show that hierarchical signals decompose into disjoint frequency bands, enabling multiscale information processing with reduced interference. These results provide a mathematical foundation for robust and hierarchical information architectures, with potential applications in signal processing, error-tolerant computation, and non-classical information systems.

MathematicsVol. 14(8)
Universidad del Norte (CO)
Universidad del Norte
Openalex Percentile: Top 18%
advanced mathematical theories
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