quantum circuit classification (classical ML)

Classifying quantum circuits is a subtask in the field of natural language processing, focusing on categorizing classical textual descriptions of quantum circuits through classical machine learning methods. The goal of this task is to accurately identify and distinguish different types of quantum circuits, thereby supporting research and applications in the field of quantum computing. By efficiently classifying the textual descriptions of quantum circuits, it can accelerate the design and optimization of quantum algorithms, and improve the development efficiency of quantum computing systems.