Quantum Eigenstate Dynamics for Artificial General Intelligence Synthesis (Expanded version)

This is the expanded version of our previous publication. Let H denote a Hilbert space of cognitive operators. We construct AGI states |ΨAGI⟩ as superpositions of quantum eigenstates |ψi⟩ enabling simultaneous resolution of binary logic via eigenvalue collapse. Classical bits (0,1) are subsumed by qubit states α|0⟩ + β |1⟩ where |α|2 + |β|2 = 1. Introduction The central idea is to propose a model for Artificial General Intelligence (AGI). This work suggests constructing AGI states as superpositions of quantum eigenstates. This model is designed to allow for the simultaneous resolution of binary logic through a process called eigenvalue collapse. Our work explains that classical bits (0, 1) are encompassed by qubit states α|0⟩ + β |1⟩. Key aspects of the model include: • Quantum Cognitive Basis: The AGI’s overall cognitive framework is a combination of subcognitive modules, such as sensory and reasoning. • Logic via Eigenstate Collapse: Our work notes a contrast between quantum logic gates and classical deterministic ones, stating that quantum logic gates can generate entangled states. This entanglement allows for the parallel evaluation of ”yes” and ”no”. When a qubit is measured, the outcome is a probabilistic ”yes” or ”no”. • AGI Dynamics: The total system’s Hamiltonian induces transitions between different eigenstates, which enables adaptive decisions. • Binary Logic Generalization: We claim that while classical true/false states map to specific eigenstates, qubits encode uncertainty. This paper concludes that quantum cognition operates in a complex space, whereas classical cognition operates in a binary space. The AGI eigenstates will collapse to a ”yes” or ”no” decision upon measurement, but they can maintain a superposition for unresolved states. This allows ”yes” and ”no” to coexist until a measurement is performed, moving beyond the constraints of classical binary logic