Understanding the training dynamics of quantum neural networks is a fundamental task in quantum information science. Here, the authors show how these follow generalized Lotka-Volterra equations, revealing a transition between frozen-kernel, critical point and frozen-error dynamics. Theoretical findings, validated on IBM devices, provide insight to cost function design.
- Bingzhi Zhang
- Junyu Liu
- Quntao Zhuang