发表机构
Masaryk University（马萨里克大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究利用Gaia DR3等数据，编制已知系外行星的Gaia星表编号目录并识别与星团相关的系外行星，为系外行星属性及演化研究提供支持。
AI 中文摘要
系外行星研究领域因TESS、Kepler/K2任务正快速发展，最新的数据发布Gaia DR3已彻底改变星团研究。结合已知系外行星及其所在星团的属性，可更细致地研究行星并检验行星演化理论。本研究旨在创建已知系外行星的Gaia星表编号目录，用于将这些行星与星表星团目录关联。研究利用NASA系外行星档案和系外行星百科全书编制已知系外行星目录，再将该数据与Gaia DR3源交叉匹配以获取系外行星的Gaia星表编号，据此推断这些系外行星与星团的潜在关联，描述其统计属性，最终编制出已知系外行星的Gaia星表编号目录并识别出与星团相关的系外行星。该资源可支持对系外行星属性及其在恒星团内演化环境的详细研究。
英文摘要
The field of exoplanetary research is rapidly evolving, thanks to TESS and Kepler/K2. With the latest data release, Gaia DR3, Gaia has transformed the study of star clusters. By combining the known properties of exoplanets and those of star clusters, in which they are found, it is possible to study the planets in greater detail and test theories of planetary evolution. We aim to create a catalogue of Gaia IDs for known exoplanets and use it to link the planets to a catalogue of star clusters. We utilised the NASA Exoplanet Archive and the Extrasolar Planets Encyclopaedia to compile a catalogue of known exoplanets. We then cross-matched the data with Gaia DR3 sources to obtain the Gaia IDs of the exoplanets. Using this information, we inferred the potential association of these exoplanets with star clusters. We described the statistical properties of these exoplanets. We compiled a catalogue of Gaia IDs for known exoplanets and identified those associated with star clusters. This resource facilitates detailed studies of exoplanet properties and their evolutionary contexts within stellar clusters.
Comments14 pages, 6 figures, accepted by Astronomische Nachrichten
