We are developing coupled oscillator arrays for closed-loop perception and control. The same dynamical model is tested first in simulation and room-temperature analog hardware, with a roadmap toward cryogenic and superconducting implementations.
That is active inference, expressed here as a physical control loop. A pumped oscillator provides a controllable nonlinear substrate; the coupling matrix encodes priors, constraints, and action paths. The current work compares the same mathematical model across simulation, room-temperature analog hardware, and a cryogenic fabrication roadmap.
The goal is not zero error. A system at zero error has stopped listening. The goal is useful error: structured, causal, and reafferent. It is the same region a musician lives in when a take has feel, predictions good enough to hold coherence, wrong enough to create momentum.
Prototype model: N equals sixteen coupled parametric oscillators. The coupling matrix can be complex valued: the real part dissipative, the imaginary part reactive. In simulation, learned topologies are stored as candidate coupling matrices for hardware evaluation.
In this benchmark, greedy and structured ablations do not beat passive. Cut the action channel and the improvement collapses, pointing to the closed-loop contribution.
The action variable is the homodyne readout phase, selected by expected information gain. Scrambling the action-to-sensation link degrades convergence, matching the causal signature seen in the classical loop.
If you are a musician, a lab, an investor, or a builder who reads this and recognises something useful, write to us.