This paper presents an operational model for the concept of informational invariance, proposed in previous work (Vidal Porto, 2026a, 2026b). The model quantifies pattern persistence through a probabilistic score I'(x) = (Pcorr - Padv)/(Pcorr + Padv + ε), where Pcorr is the frequency of an element in correlated (preserved) versions and Padv its frequency in adversarial (attacked) versions. Three adversarial scenarios are defined: upper bound (attack on the original), realistic (attack on the correlated version), and baseline (blind attack). From these scenarios, we define Trans-Lesional Regenerative Capacity Cr = lim(Simorig → 0) (Simrec - Simorig)/(1 - Simorig) and Invariant Robustness Rinv = Cr(Realistic) / Cr(Upper Bound). Binary grid simulations show Cr(Realistic) = 68.3%, Cr(Upper Bound) = 51.7%, and Rinv = 1.32. Validation on the MNIST dataset of handwritten digits yields Cr(Realistic) = 6.1%, Cr(Upper Bound) = 0.1%, and Rinv = 75.63, demonstrating that the invariant is substantially more robust in realistic scenarios. The results confirm the hypotheses of previous work and provide a testable foundation for future applications in medical imaging and biological systems.
Fernando Vidal Porto (Thu,) studied this question.