Experimental Observation of Hidden Multistability in Nonlinear Systems
Kun Zhang, Qicheng Zhang, Shuaishuai Tong, Wenquan Wu, Xiling Feng, and Chunyin Qiu

TL;DR
This paper reports the first experimental observation of hidden multistability in nonlinear systems, revealing stable states that are normally undetectable and controllable via pulsed excitation, with potential applications in information technology.
Contribution
It demonstrates the experimental realization and control of hidden multistability in a nonlinear acoustic system, expanding understanding of multistable states beyond traditional detection methods.
Findings
Observation of semi- and fully-hidden tristabilities
Control of hidden states through pulsed excitation
Potential applications in information storage and encryption
Abstract
Multistability, the coexistence of multiple stable states, is a cornerstone of nonlinear dynamical systems, governing their equilibrium, tunability, and emergent complexity. Recently, the concept of hidden multistability, where certain stable states evade detection via conventional continuous parameter sweeping, has garnered increasing attention due to its elusive nature and promising applications. In this Letter, we present the first experimental observation of hidden multistability using a programmable acoustic coupled-cavity platform that integrates competing self-focusing and self-defocusing Kerr nonlinearities. Beyond established bistability, we demonstrate semi- and fully-hidden tristabilities by precisely programming system parameters. Crucially, the hidden stable states, typically inaccessible via the traditional protocol, are unambiguously revealed and dynamically controlled…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsMechanical and Optical Resonators · Neural Networks and Reservoir Computing · Nonlinear Dynamics and Pattern Formation
