Theoretical framework demonstrates the endogenous emergence of spacetime and fundamental physical parameters from discrete causal networks, indicating a unified foundation for physics.
We propose Causal Set Gauge-Flow Theory (CSGFT), a foundational framework in which physical quantities are not externally imposed labels but topologically invariant quantities endogenously emergent from a discrete causal-gauge structure. The Standard Model treats electric charge, color charge, mass, coupling constants, and vacuum expectation values as experimental input parameters without explaining their origin. CSGFT departs from five axioms and demonstrates that these quantities acquire ontological explanation from the gauge-flow topological structure on a causal network: (1) electric charge is the phase winding number of closed causal paths, and the discrete Chern number theorem establishes charge quantization as a necessary consequence of the topological monodromy condition; (2) spacetime volume is the count of causal elements, and the coarse-grained volume element shows that the continuous spacetime volume element measures the number of causal elements in a region; (3) gravity is the macroscopic projection of the gauge-flow density gradient, and in the effective Einstein field equations, the gravitational constant is an emergent coupling parameter measuring the microscopic correlation between gauge-flow density fluctuations and spacetime curvature; (4) the number of fermion generations is determined by topological stability, and three generations are not experimental input but a natural consequence of energy functional minimization. The theory yields falsifiable quantitative predictions: lepton mass ratios with deviations from PDG 2024 measurements below 0.04%; no stable fourth-generation fermion; dark energy equation-of-state parameter w_a not equal to 0; and photon dispersion with coefficient xi = 4pi/3. This paper is strictly positioned as a framework-founding work; rigorously proven results, conditional conclusions, and constructive hypotheses are explicitly delineated throughout.
No takes yet. Share an insight, caveat, or question.
Yunquan Liu (2026) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: