Living Computational Bits: Dynamical Information Primitives Beyond Static State

Modern computation treats information as static state, requiring energy-intensiveisolation to resist thermodynamic decay. This paper introduces the Living Com-putational Bit (LCB), a dynamical information primitive that replaces static stasiswith maintained non-equilibrium attractors. Positioned as a third axis of compu-tation alongside Precision and Parallelism, the LCB optimizes for Persistence: therobust survival of information through active dissipation rather than passive iso-lation. We formalize the LCB as an ensemble-based primitive, where informationalcontent is discretized by basin identity in a limit cycle (dx/dt ̸= 0) rather thana fixed-point attractor. We define a conceptual comparison metric, InformationPersistence Efficiency (IPE), scoped explicitly as a framework for cross-paradigmcomparison rather than a computable quantity, to articulate the thermodynamicadvantage of active maintenance in high-noise environments. Crucially, we distinguish the LCB as a physical primitive rather than a logicalarchitecture, contrasting its intrinsic self-repair mechanisms with the algorithmicredundancy of attractor networks. We introduce the Energy Withdrawal Test as afalsifiable operational criterion: if removing energy flux destroys the information,the system contains LCBs; if information persists, the system uses static bits inan attractor architecture. Using a minimal Chemical Reaction Network (CRN) asa substrate-independent demonstration, we reinterpret the well-characterized re-pressilator oscillation not as a dynamical phenomenon but as an informational op-eration, where the Hopf bifurcation boundary constitutes a “write” and the topo-logical state constitutes a “bit.” This framework provides a new informational ontology for resilient computa-tion, shifting the focus from fighting thermodynamics to utilizing energy flux asa structural architect. We situate this contribution within the broader landscapeof Prigogine’s dissipative structures, thermodynamic computing, and biologicalattractor networks, identifying the specific gap the LCB fills: a formalized, dis-crete informational unit for non-equilibrium dynamics that existing frameworksdescribe physically but never define informationally