PHILIA-SAN: A Toy Model of a Single Artificial Neuron with Recursive Feedback Loop

This paper presents PHILIA-SAN (Single Artificial Neuron), a minimal toy model built on the PHILIA v9 engine. The model consists of a receptor layer (linear normalization) and a single recursive neuron with a closed SR->Phi feedback loop. It is not a biological model and does not claim homeostasis. Passive stability of the neuron was measured under disturbance ratios of 10% to 50% using real physical data from CERN dielectron (99,915 events) and ATLAS Higgs (693,636 events) datasets. All results are from local hardware execution (Intel N100). This is a description, not a proof.