Multi-target quantum compilation algorithm

In quantum computing, quantum compilation involves transforming information from a target unitary into a trainable unitary represented by a quantum circuit. Traditional quantum compilation optimizes circuits for a single target. However, many quantum systems require simultaneous optimization of multiple targets, such as simulating systems with varying parameters and preparing multi-component quantum states. To address this, we develop a multi-target quantum compilation algorithm to enhance the performance and flexibility of simulating multiple quantum systems. Through our benchmarks and case studies, we demonstrate the algorithm's effectiveness, highlighting the significance of multi-target optimization in the advancement of quantum computing. This work establishes the groundwork for further development, implementation, and evaluation of multi-target quantum compilation algorithms.