This paper develops the concept of quantum distinction structures within the Theory of Consciousness (TC). TC posits consciousness as the sole ontological ground of reality, with distinctions serving as its quanta — inseparable from consciousness and non-existent outside it. The paper introduces the concept of a quantum distinction as the minimal possible act of distinguishing (yes/no, this/not-this), and the concept of a knowledge particle — the minimal stable structure of quantum distinctions constituting a unit of knowledge in consciousness. Formally, a knowledge particle is described as a metric-free simplicial complex organised by the principle of Harmony. A particle passport is proposed. Two topological invariants — the number of quantum distinctions and the number of independent closed cycles — fully determine the type of knowledge independently of the specific content of the distinctions. The structural stability of a particle increases monotonically with the number of independent closed cycles. The dynamics of quantum distinction structures is described through three ontological events: emergence, modification, and dissolution, each generating a light of consciousness with distinct topological content. An ontological asymmetry is established: quantum distinctions are primary and return to the potential upon dissolution; connections are secondary and vanish without trace. The law of hierarchy is established: knowledge structures are built from lower-level knowledge structures according to the same laws of harmony, yielding a self-similar multilevel architecture of consciousness. The results demonstrate that the ontology of consciousness admits a rigorous topological formalisation that reproduces the key features of knowledge organisation: discreteness, stability, periodicity, and hierarchy.
Building similarity graph...
Analyzing shared references across papers
Loading...
Oleksandr Savinykh (Tue,) studied this question.
www.synapsesocial.com/papers/69d894ec6c1944d70ce05e2d — DOI: https://doi.org/10.5281/zenodo.19456878
Oleksandr Savinykh
Building similarity graph...
Analyzing shared references across papers
Loading...