在Λ-冷暗物質宇宙學典範下，宇宙中結構是以階層式形成。星系團最亮星系（Brightest cluster galaxies, 簡稱BCG）位於星系團的中心，正代表了此階層式結構形成的頂點。星系團最亮星系的性質與它們的星系團有強烈關聯，並且它們的形成過程很可能含有星系與星系團形成的重要限制條件。紅移小於0.5時，星系團最亮星系的恆星質量增長在觀測和模擬之間有差異。此研究旨在解決此差異。

我們藉由直接比較星系團最亮星系中心區域的多核率來解決這個差異。我們利用MaNGA計畫（Mapping Nearby Galaxies at APO, 簡稱MaNGA）所提供89個星系團最亮星系的空間解析光譜，以區分合併系統和視線方向隨機重疊的投影，並得到星系團最亮星系多核率之最具統計顯著性的成果。我們開發了一套程式以自動化偵測星系團最亮星系的核，並將此程式使用於最新最大的宇宙學流體動力學模擬IllustrisTNG的300^3立方百萬秒差距（Mpc^3）版本製成的擬真模擬影像。

我們從紅移為0.06-0.15的體積限制樣本（volume-limited sample）測得觀測多核率為0.097±0.036，並從218個模擬的星系團最亮星系測得多核率為0.066±0.018。

我們的觀測結果與模擬結果只有一個標準差的差異。我們還發現多核通常實際上和星系團最亮星系有關聯，而非隨機的重疊投影。將來我們的自動化程式可應用在對於星系團最亮星系的更深影像巡天計畫和更多樣本的無狹縫光譜巡天計畫。

In the ΛCDM cosmological paradigm, structures form hierarchically. Brightest cluster galaxies (BCGs) are located at the center of galaxy clusters, which represent the culmination of this formation. The properties of BCGs are strongly connected with their host clusters, and their growth paths potentially contain important constraints on cluster and galaxy formation. This work aims to solve the discrepancy between observation and simulation on the stellar mass growth of BCGs at z < 0.5.

We tackle this discrepancy by directly comparing the multiple-core frequency (a proxy for merger rate) in the inner regions of BCGs. We take advantage of the spatially resolved spectroscopy of 89 BCGs from Mapping Nearby Galaxies at APO (MaNGA) to distinguish merging systems from chance projections, and present the result of the first IFU survey of the multiple-core frequency of BCGs. We develop a pipeline to automatically detect cores and apply it to realistic synthetic images based on the (300 Mpc)^3 volume version of the cosmological hydrodynamical simulation IllustrisTNG.

We obtain an observational multiple-core frequency of 0.097±0.036 from a volume-limited sample at z = 0.06-0.15, and a multiple-core frequency of 0.066±0.018 from 218 simulated BCGs.

Our observation results show only a 1 sigma discrepancy from a leading hydrodynamical simulation. We also find multiple cores are most often associated with their BCGs rather than chance projections. In the future, our pipeline can be applied to data from deeper imaging surveys and larger slitless spectroscopy surveys of BCGs.

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