论文标题
数据驱动的系统识别线性量子系统与时变相干输入相连
Data-Driven System Identification of Linear Quantum Systems Coupled to Time-Varying Coherent Inputs
论文作者
论文摘要
在本文中，我们开发了一种系统识别算法，以基于经验的单杆连续同型测量数据，以确定由时变相干状态驱动的未知线性量子系统的模型。所提出的算法确定了满足线性量子系统物理可相实际条件的模型，这是在经典（非量词）线性系统识别中未遇到的挑战约束。提供了多输入多输出光腔模型上的数值示例，以说明识别算法的应用。
In this paper, we develop a system identification algorithm to identify a model for unknown linear quantum systems driven by time-varying coherent states, based on empirical single-shot continuous homodyne measurement data of the system's output. The proposed algorithm identifies a model that satisfies the physical realizability conditions for linear quantum systems, challenging constraints not encountered in classical (non-quantum) linear system identification. Numerical examples on a multiple-input multiple-output optical cavity model are presented to illustrate an application of the identification algorithm.
