A Structural Algorithmic Model for Physical Systems

Modern physics provides highly accurate mathematical descriptions of natural phenomena, yet often lacks a clear account of the underlying mechanisms that give rise to these equations. This work addresses this gap by introducing a minimal, structurally defined algorithmic framework from which physical regularities can emerge. The model is based on a discrete structured system composed of three element types and a single elementary update operation. System dynamics arise from sequential processing, message-based interactions, and strict movement constraints, without assuming forces, fields, or continuous spacetime at the fundamental level. Time, interaction strength, stability, and persistent structures emerge as consequences of the algorithmic process. Physical concepts such as charge, particle-like entities, wave propagation, and inverse-square interaction behavior are interpreted as higher-level manifestations of repeated discrete reordering steps. Mathematical relations are not postulated but understood as compact descriptions of regular behavior generated by the underlying structure. This document presents the conceptual framework and algorithmic core of the model in a condensed, citable form. Detailed derivations and quantitative applications are reserved for subsequent publications.