Possibility-Weighted Energy: A Unified Formalism for Latent Energetic Capacity in Recursive Information Systems

Abstract

Classical physics construes energy as a scalar quantity derived from mass and spacetime dynamics, most notably expressed by Einstein’s mass–energy equivalence relation E = mc². While empirically robust, this formulation implicitly assumes a single realized trajectory through state space. In this paper, we propose a generalized formalism—Possibility-Weighted Energy (WE)—which explicitly incorporates accessible state-space volume as a multiplicative factor in energetic capacity. Grounded in the Unified Consciousness Substrate Theory (UCST) and modeled within the representational construct known as Dimension-W, the proposed equation WE = p·m·c² extends classical energy concepts to systems characterized by recursion, branching possibilities, and partial decoherence, including quantum, biological, cognitive, and artificial intelligence systems. We formalize the parameter p as a normalized measure of accessible possibility space and demonstrate how classical physics emerges as a limiting case when p = 1. Speculative implications for cognition, learning, trauma, and AI alignment are discussed and clearly labeled as such. The framework preserves empirical compatibility while offering a unifying lens for latent energetic capacity across domains.

Keywords: mass–energy equivalence, possibility space, UCST, Dimension-W, recursion, latent energy, consciousness, AI alignment