SOURCE-LINKED INTELLIGENCE
Feasibility and Memory Mechanisms of Chern-Simons Context Reservoir Computation
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
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-10T17:45:30.000Z
First collected: 2026-09-20T18:42:18.733Z. This is not the publication date.