From the 1 of 5 linked papers with an AI index.
5 papers
Beyond the Edge of Chaos: Stability-Expressivity Transfer in Reservoir Forecasting
Yao Du, Xingang Wang
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 spe…
Evolution-Level Quantum Optimal Control of Single-Qubit Gates with Physics-Informed Neural Networks
Yao Du, Jian-Jian Cheng, Lin Zhang +2
The paper introduces physics-informed neural networks to jointly learn control fields, Bloch-state trajectories, and gate duration for single‑qubit gate synthesis, enabling interpr…
Inferring bifurcation diagrams of two distinct chaotic systems by a single machine
Jianmin Guo, Yao Du, Yizhen Yu +2
We propose a dual-channel reservoir-computing scheme for inferring the dynamics of two distinct chaotic systems with a single machine. By augmenting a standard reservoir with a sys…
Versatile Reservoir Computing for Heterogeneous Complex Networks
Yao Du, Huawei Fan, Xingang Wang
A new machine learning scheme, termed versatile reservoir computing, is proposed for sustaining the dynamics of heterogeneous complex networks. We show that a single, small-scale r…
Sustaining the dynamics of Kuramoto model by adaptable reservoir computer
Haibo Luo, Mengru Wang, Yao Du +3
A scenario frequently encountered in real-world complex systems is the temporary failure of a few components. For systems whose functionality hinges on the collective dynamics of t…