Spacetime as Entropic Capacity: An Information-Theoretic Framework for Emergent Gravity with Empirical Validation

We develop an information-theoretic framework in which spacetime, mass, gravity, and motion emerge from a finite-capacity discrete causal network. Space is identified with addressable storage of a causal information structure, time with monotonic growth of committed history, mass with minimum description length of local subsystems, and gravity with throttling of local update rates when processing demand approaches holographic capacity bounds.

We establish a Law of Entropic Capacity: the maximum information-processing rate available to any bounded region scales with boundary area and is constrained by the Margolus-Levitin quantum speed limit. Using quantum Fisher information to ground emergent geometry, we derive the Einstein field equations as a capacity-response relation via Jacobson's thermodynamic approach. A 1+1D toy model demonstrates how capacity constraints yield metric structure with time-dilation matching Schwarzschild geometry to leading order.

The framework is validated empirically through LogVAMS, an anomaly detection system applying entropic capacity mathematics to software systems. On synthetic log data with 162 injected failures, LogVAMS achieves 35.9 +/- 12.3 observation mean lead time with recall of 1.00 and AUROC of 0.847, significantly outperforming baselines which achieve lead time ~0. Cross-domain validation is provided by the 4MSB experiment testing whether survival signatures match across independent evolutionary populations. We present falsifiable predictions for holographic noise searches (~10^-22 Hz^-1/2 at 1 MHz), complexity-sensitive gravitation (Delta g/g < 10^-15), and gamma-ray burst dispersion bounds (|Delta v|/c < 10^-15 at TeV energies).