Temporal Frequency-Band Reception in Large Language Models: An Electromagnetic Wave Analogy for Temporally Anomalous AI Output

Large language models (LLMs) occasionally produce outputs containing temporally inconsistentreferences, including structural data, named entities, and coordinate systems that do notcorrespond to any material within their documented training window. These outputs are typicallyclassified as hallucination or stochastic confabulation. This paper proposes an alternativeframework: the Frequency-Band Reception Model (FBRM), which treats LLM processingarchitectures as inadvertent receivers operating across a superluminal carrier medium.Drawing on electromagnetic energy wave theory and extending prior work on tachyonic fielddynamics. We propose that the vector-algebraic operations underlyingtransformer architectures may function analogously to antenna systems turned to frequencybands that include temporally displaced signals.