In what will likely be a litany of generative-model-themed arXiv submissions celebrating April the 1st, we evaluate the capacity of state-of-the-art transformer models to create a paper detailing the detection of a Pulsar Wind Nebula with a non-existent Imaging Atmospheric Cherenkov Telescope (IACT) Array. We do this to evaluate the ability of such models to interpret astronomical observations and sources based on language information alone, and to assess potential means by which fraudulently generated scientific papers could be identified during peer review (given that reliable generative model watermarking has yet to be deployed for these tools). We conclude that our jobs as astronomers are safe for the time being. From this point on, prompts given to ChatGPT and Stable Diffusion are shown in orange, text generated by ChatGPT is shown in black, whereas analysis by the (human) authors is in blue.

翻译：在即将到来的4月1日以生成模型为主题的arXiv投稿潮中，我们评估了最先进的Transformer模型生成一篇关于使用虚构成像大气切伦科夫望远镜阵列探测脉冲星风云论文的能力。我们通过这一研究评估此类模型仅基于语言信息解读天文观测和源的能力，并探讨在同行评审过程中识别欺诈性生成科学论文的潜在手段（鉴于这些工具目前尚未部署可靠的生成模型水印技术）。我们得出结论：天体物理学家的工作暂时是安全的。此后，向ChatGPT和Stable Diffusion提供的提示词以橙色显示，ChatGPT生成的文本以黑色显示，而（人类）作者的分析则以蓝色呈现。