In quantum physics, AlphaEvolve's optimizations have made it possible to run complex molecular simulations on Google's Willow quantum processor by suggesting quantum circuits with 10x lower error than previous conventionally optimized baselines.
大多数人认为量子计算需要专门的量子物理知识和算法设计，但作者认为通用AI代理可以优化量子电路并实现数量级的改进。这挑战了量子计算领域的传统方法，暗示AI可能成为量子计算进步的关键驱动力，而非仅仅是一个辅助工具。
This benchmark is a six-part semantic scoring test that assesses any model's effectiveness at relevant calibration tasks. QCalEval measures a model's ability to interpret experimental results, classify outcomes, evaluate their significance, assess fit quality and key features, and generate actionable next-step recommendations.
令人惊讶的是：量子校准AI模型的评估竟然如此复杂，需要六个维度的语义评分来全面评估其能力。这反映了量子校准任务的复杂性，也表明AI在科学领域的应用需要专门的评估方法，不能简单地照搬传统AI评估标准。
Ising-Calibration-1 repeatedly outperforms state-of-the-art open and closed models of a range of parameters. As shown in Figure 1, Ising Calibration 1 scores 3.27% better on average than Gemini 3.1 Pro, 9.68% better than Claude Opus 4.6, and 14.5% better than GPT 5.4.
令人惊讶的是：专门为量子校准设计的AI模型Ising-Calibration-1竟然在量子校准任务上超越了包括GPT-5.4和Gemini 3.1 Pro在内的最先进通用AI模型，这表明专用AI模型在特定科学任务上可能比通用模型表现更好，颠覆了'通用AI万能'的传统观念。