AIIC AI Intelligence Centre

SOURCE-LINKED INTELLIGENCE

Feasibility and Memory Mechanisms of Chern-Simons Context Reservoir Computation

arXiv · AI, language, vision and robotics · article · Sep 10, 2026 · UTC

We investigate whether a Chern-Simons (CS) context reservoir is a viable computational substrate and whether evolving its gauge connection provides a benefit beyond simpler mechanisms. The reservoir state is a density fluctuation on a two-dimensional context manifold, whose drift is generated by a density-sourced connection. To separate generic reservoir behavior from gauge-specific effects, we compare four matched models: reciprocal transport, instantaneous transverse reconstruction, local nonlinear feedback, and fully coupled conserved-current CS dynamics. Across ten random seeds, the fully

Read original source ↗ Open in workspace

recordType
paper
region
Global

Evidence & attribution

First collected: 2026-09-20T18:42:18.733Z. This is not the publication date.