A series of papers (superposition graph and the currently read quantum graph paper) have lead me to start exploring different quantum state representations in graphs. Specifically hypergraphs, and superpositions of them - i.e graphs of nodes and edges where each edge can connect any number of nodes, where a sum over different hypernode configurations for a superposition of graphs. The supergraph space is explored by reinforcement learning, where different metrics are used to guide the selection of certain hypergraph compositions to optimize the ansatz with respect to certain goals. This approach has then been used conceptually to explore different usecases (Paths below).

The Ansatz

Firstly, a primer on the theory involved for the ansatz.

The Error Code Path

The Emergent Time Path