Phase Drift: A Cross-Domain Failure Mode in Coordinated Systems

This paper introduces Phase Drift as a diagnostic condition in coordinated systems, defined by the degradation of alignment (Phase) under continued accumulation or output (Scalar). While prior work in the Tang Papers distinguishes between scalar magnitude and phase coordination, a consistent failure pattern emerges across domains when these dimensions diverge under sustained activity.

Phase Drift is not proposed as a universal explanation of system failure, but as a specific and recurring condition observable in artificial intelligence systems, human communication, biological coordination, and organizational dynamics.

Naming this condition enables cross-domain pattern recognition in cases where scalar measurement alone fails to detect loss of coherence. The framework provides a representational diagnostic for identifying when systems remain active and well-formed while underlying coordination has degraded.

In artificial intelligence, this condition corresponds to fluent but ungrounded outputs (commonly referred to as hallucination), reframed here as a coordination failure rather than a purely statistical error.