Superlight as the Missing Substrate: Interpreting CoDEx 2026 and Muon g-2 Through a Unified Coherence Framework

Recent developments in two independent research domains motivate a re‑examination of whether substrate‑level coherence plays an organizing role in physical and informational systems. In particle physics, the Brookhaven–Fermilab muon g‑2 program has shifted from an experimental anomaly to a theory–theory discrepancy: recent computational predictions now agree with the measured anomalous magnetic moment, while data‑driven predictions do not, raising questions about whether current vacuum models fully capture the relevant structure. In parallel, results from the Northwestern University CoDEx 2026 Symposium revealed cross‑domain slow‑mode convergence in AI surrogate modeling, biological signal phrasing, and large‑scale data stability—phenomena not designed to probe fundamental physics, yet all exhibiting behavior consistent with low‑frequency coherence dynamics. This paper examines whether these quantum‑scale and macroscopic developments may be unified by a common substrate‑level field. Within the Superlight framework, such a field acts as a pre‑metric coherence structure that organizes vacuum fluctuations and provides a low‑frequency baseline for complex systems. We show that this interpretation is compatible with existing muon g‑2 measurements and with the CoDEx 2026 observations, without contradicting the Standard Model or any known experimental constraints.