This work introduces Quantum–Emotional Field Theory (QEFT), a unified informational framework in which quantum state evolution, cognitive dynamics, and artificial intelligence instability are interpreted as manifestations of a common underlying structure governed by contextual informational fields. Within this model, the standard quantum formalism is extended by a contextual modulation term representing informational salience gradients of the environment. These gradients are not interpreted as subjective emotions, but as objective parameters that regulate state accessibility, compression, and effective coherence. The framework builds on Informational State Dynamics (ISD) and integrates concepts from predictive processing, free-energy minimization, and computational instability in large-scale generative models. Cognitive and artificial systems are modeled as observer-relative compression operators acting on a shared informational state space. A central contribution is the formalization of an informational production–integration balance, which determines system stability across scales. When production of informational states exceeds integration capacity, systems undergo a transition to unstable regimes characterized by loss of coherence, increased variability, and emergent structural fragmentation. This mechanism is proposed as a unifying explanation for quantum decoherence patterns, cognitive overload phenomena, and large language model hallucination regimes. QEFT remains empirically compatible with standard quantum mechanics while providing a higher-order interpretational layer that connects physical, cognitive, and computational domains through a single informational principle.
Giuseppe Junior Greco (Sat,) studied this question.
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