Artificial intelligence (AI) is a potentially disruptive tool for physics and science in general. One crucial question is how this technology can contribute at a conceptual level to help acquire new scientific understanding. Scientists have used AI techniques to rediscover previously known concepts. So far, no examples of that kind have been reported that are applied to open problems for getting new scientific concepts and ideas. Here, we present Theseus, an algorithm that can provide new conceptual understanding, and we demonstrate its applications in the field of experimental quantum optics. To do so, we make four crucial contributions. (i) We introduce a graph-based representation of quantum optical experiments that can be interpreted and used algorithmically. (ii) We develop an automated design approach for new quantum experiments, which is orders of magnitude faster than the best previous algorithms at concrete design tasks for experimental configuration. (iii) We solve several crucial open questions in experimental quantum optics which involve practical blueprints of resource states in photonic quantum technology and quantum states and transformations that allow for new foundational quantum experiments. Finally, and most importantly, (iv) the interpretable representation and enormous speed-up allow us to produce solutions that a human scientist can interpret and gain new scientific concepts from outright. We anticipate that Theseus will become an essential tool in quantum optics for developing new experiments and photonic hardware. It can further be generalized to answer open questions and provide new concepts in a large number of other quantum physical questions beyond quantum optical experiments. Theseus is a demonstration of explainable AI (XAI) in physics that shows how AI algorithms can contribute to science on a conceptual level.

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通过量子光学实验的高效自动化设计进行概念理解

人工智能 (AI) 是一种对物理学和科学普遍具有潜在破坏性的工具。一个关键问题是，这项技术如何在概念层面做出贡献，以帮助获得新的科学理解。科学家们已经使用人工智能技术重新发现了以前已知的概念。到目前为止，还没有报道过将此类示例应用于开放问题以获得新的科学概念和想法。在这里，我们介绍 T heseus，一种可以提供新概念理解的算法，我们展示了它在实验量子光学领域的应用。为此，我们做出了四项重要贡献。(i) 我们介绍了一种基于图的量子光学实验表示，可以在算法上进行解释和使用。(ii) 我们为新的量子实验开发了一种自动化设计方法，在实验配置的具体设计任务中，它比以前最好的算法快几个数量级。(iii) 我们解决了实验量子光学中的几个关键的开放性问题，这些问题涉及光子量子技术中资源状态的实际蓝图以及允许新的基础量子实验的量子状态和转换。最后，也是最重要的，(iv) 可解释的表示和巨大的加速使我们能够产生人类科学家可以直接解释和获得新科学概念的解决方案。我们预计 Theseus将成为量子光学领域开发新实验和光子硬件的重要工具。它可以进一步推广以回答开放性问题并在量子光学实验之外的大量其他量子物理问题中提供新概念。牛逼heseus是可解释的AI（XAI）的物理显示了如何AI算法有助于科学概念层次的示范。