Natural Information Attractors: A Unified Symbolic, Mathematical, Psychological, and Philosophical Framework

Abstract This paper introduces the concept of Natural Information Attractors (NIAs): recurrent patterns of meaning, structure, and coherence that emerge spontaneously across cognitive, symbolic, mathematical, and physical domains. Drawing from systems theory, dynamical systems mathematics, depth psychology, philosophy of mind, and contemporary theories of information, we present a coherent framework for understanding how certain symbols, narratives, numerical structures, and conceptual forms repeatedly arise and stabilize across independent observers and contexts. We argue that NIAs function analogously to attractors in dynamical systems: they constrain trajectories of interpretation, stabilize meaning, and enable shared understanding without requiring centralized coordination. This framework is designed to translate symbolic and experiential findings into language accessible to interdisciplinary audiences, without requiring metaphysical commitments. Keywords: information attractors, dynamical systems, symbolism, consciousness, recursion, coherence, meaning