QCircuitBench_Sample

QCircuitBench is the first benchmark dataset designed to evaluate AI's capability in designing and implementing quantum algorithms in the form of quantum circuit codes. Key contributions of QCircuitBench include: 1. A general framework which formulates the key features of quantum algorithm design task for Large Language Models. 2. Implementation for quantum algorithms from basic primitives to advanced applications, spanning 3 task suites, 23 algorithms, and 128,573 data points. 3. Automatic validation and verification functions, allowing for iterative and interactive evaluation without human inspection. This is a sampled version of the full QCircuitBench for easier access.QCircuitBench是首个旨在评估人工智能以量子电路代码形式设计与实现量子算法能力的基准数据集。其核心贡献包括： 1. 构建通用框架，对大语言模型（Large Language Model）的量子算法设计任务的核心特征进行形式化建模； 2. 覆盖从基础原语到高级应用的全品类量子算法实现，涵盖3个任务套件、23种算法及128573个数据点； 3. 集成自动验证与校验功能，支持无需人工审核的迭代式、交互式评估流程。 本版本为完整QCircuitBench的采样版本，便于用户获取与使用。