标题： 天体物理叙事：通过马尔可夫链对费米LAT伽马射线发射的诗意表征 显示英文标题

标题： Astrophysical Narratives: Poetic Representations of Gamma-Ray Emission from FermiLAT via Markov Chains

摘要： 艺术与科学的交汇提供了新颖的方式来诠释和表征复杂现象。 本项目通过提出一种基于马尔可夫链的算法，探索高能天体物理学、具象诗歌和自然语言处理（NLP）的融合，该算法能够从宇宙伽马射线发射图中生成诗意文本。 伽马射线，电磁辐射中最富能量的形式，源于超新星、脉冲星和黑洞吸积等剧烈的天体物理过程，可通过仪器如 \textit{费米大面积望远镜} （费米LAT）观测到。 这些高能事件被映射并处理成矩阵，被视为马尔可夫链，其中每个状态的转移概率由感兴趣区域内伽马射线源的强度决定。 显示英文摘要

摘要： The intersection of art and science offers novel ways to interpret and represent complex phenomena. This project explores the convergence of high-energy astrophysics, concrete poetry, and natural language processing (NLP) by proposing a Markov chain-based algorithm that generates poetic texts from gamma-ray emission maps of the universe. Gamma rays, the most energetic form of electromagnetic radiation, arise from violent astrophysical processes such as supernovae, pulsars, and black hole accretion, observable through instruments like the \textit{Fermi Large Area Telescope} (FermiLAT). These high-energy events are mapped and processed into matrices, treated as Markov chains, where each state's transition probability is determined by the intensity of gamma-ray sources in a region of interest.