Beyond the Edge of Chaos: Stability-Expressivity Transfer in Reservoir Forecasting
The edge-of-chaos heuristic has long served as a guiding principle for designing reservoir computers, yet its relevance to machine performance remains elusive. Here, taking the spectral radius of the reservoir network as the control parameter, we show that the radius yielding the best forecasting performance does not coincide with the Lyapunov edge of the isolated, teacher-forced, or closed-loop generative reservoir. By analyzing the collective dynamics of the teacher-forced reservoir, we find that the target dynamics are represented mainly by stable Lyapunov modes whose finite-time stability is strongly modulated by the input. This finding motivates a stability-expressivity transfer inde...
| Authors | Yao Du, Xingang Wang |
|---|---|
| Primary category | nlin.CD |
| Published | 20 July 2026 |
| Last updated at source | 20 July 2026 |
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