Quantum computation and natural language processing

In this thesis, a novel approach to natural language understanding inspired by quantum mechanical principle is proposed. It is based on an analogy between the physical objects at the quantum level and human’s mental states. In this way, the physical and the mental phenomena are to be understood within the same framework. It is also proposed that the apparent differences between mind and matter do not lie in the fundamental differences of their properties, but in the different manifestation of macroscopic matter and macroscopic mind owing to their different composition of pure quantum eigenstates. The apparent differences are therefore quantitative rather than qualitative. Specifically, symbols in various cognitive functions are to be treated as eigenstates with respect to a particular quantum experimental arrangement. Moreover, I claim that reasoning and inference can be treated as transformations of semiosis with symbols being the eigenstates of a particular formulation operator. The operator is the counterpart of an observable in quantum mechanics. A state of affairs (a superposition of these eigenstates) does not have well-defined physical properties until it is actually measured. Consequently the classical semantics (as classical symbols’ referring to the classical physical reality) is also not well-defined and may be a misleading idea. Different from classical semantics, meaning in the quantum mechanical framework should be treated as an active measurement done on a state of affair. Moreover, the ill-definedness also manifests itself in the cognition internal to a person if we regard memory as a language-like representational system. Nevertheless, memory, treated as a specific language system, is a largely quasi-classical phenomenon in that the