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(蒙提·派森与) HoliGRALE:一种混合GRALE透镜反演方法,用合成和真实数据进行的诊断性评估

(Monty Python and the) HoliGRALE: A Hybrid GRALE Lens Inversion Methodology Diagnostically Evaluated with Synthetic and Real Data

Derek Perera, Jori Liesenborgs, John H. Miller, Ashley Francis, Liliya L. R. Williams, Birendra Dhanasingham, Jose M. Diego

arXiv 2610.09014首次发表:更新:

发表机构

University of Minnesota; UHasselt – Flanders Make; Instituto de Física de Cantabria (CSIC-UC)(明尼苏达大学; 哈瑟尔特大学—法兰德斯制造研究所; 坎塔布里亚物理研究所(西班牙高等科学研究理事会—坎塔布里亚大学))

机构由 AI 辅助整理,请以论文原文为准。

AI 中文总结

HoliGRALE是GRALE的混合扩展,结合参数化组件,在合成和真实数据上优于GRALE,准确重建密度、放大率和时间延迟,并预测SN Requiem时间延迟及Abell S1063暗物质核心半径。

AI 中文摘要

我们提出HoliGRALE(混合、仅含光、引力透镜),它是自由形式方法GRALE的混合透镜建模扩展。HoliGRALE在自由形式遗传算法GRALE中融入了物理动机的参数化组件。利用来自IllustrisTNG的三个合成星系团(每个具有不同的复杂度),我们根据其在重建密度分布、图像位置、放大率和时间延迟方面的准确性来评估其性能。我们发现HoliGRALE在所有方面普遍优于GRALE,并且在图像数密度较高的区域表现出更高的准确性。我们估计,在由观测图像约束的区域中,简单、少组件星系团的投影密度误差预算为$<5\\%$,而复杂、多组件星系团的误差预算约为$\sim5-10\\%$。然后,我们使用HoliGRALE对三个透镜进行建模:RX J2129.7$+$0005、MACS J0138.0$-$2155和Abell S1063。在每种情况下,HoliGRALE都能准确重建观测到的放大率和时间延迟。在其预测中,HoliGRALE被发现比GRALE更精确。我们特别强调,对SN Requiem下一个到达图像的时间延迟预测为$4346.61^{+490.27}_{-818.36}$天(约2026年4月至2029年10月),与之前的工作一致,尽管精度较低。在Abell S1063中,我们报告了主暗物质晕核心半径的重建为$89.9\pm33.2$ kpc,与过去的工作非常一致,并有助于检验暗物质理论。我们的结果强调了HoliGRALE的预期误差预算,在将来将HoliGRALE应用于其他透镜系统时,应提及并仔细审查这一预算。

英文摘要

We present HoliGRALE (Hybrid, only light included, GRAvitational LEnsing), a hybrid lens modeling extension of the freeform method GRALE. HoliGRALE incorporates physically motivated parametric components within the freeform genetic algorithm GRALE. Using three synthetic clusters from IllustrisTNG, each of varying complexity, we evaluate its performance according to its accuracy in reconstructing the density distribution, image positions, magnifications, and time delays. We find that HoliGRALE generally outperforms GRALE on all fronts, and shows greater accuracy in regions containing a high image number density. We estimate the error budget in projected density to be $<5\%$ for simple, few component clusters, and $\sim5-10\%$ for complex, multi-component clusters in the regions constrained by observed images. We then use HoliGRALE to model three lenses: RX J2129.7$+$0005, MACS J0138.0$-$2155, and Abell S1063. In each case, HoliGRALE is able to accurately reconstruct observed magnifications and time delays. In its predictions, HoliGRALE is found to be more precise than GRALE. We particularly highlight the predicted time delay for the next arriving image of SN Requiem to be $4346.61^{+490.27}_{-818.36}$ days ($\approx$ April 2026 -- October 2029), consistent with previous work, albeit with less precision. In Abell S1063, we report the reconstruction of a main dark matter halo core radius of $89.9\pm33.2$ kpc, in excellent agreement with past work and useful in testing theories of dark matter. Our results emphasize the expected error budget of HoliGRALE, which should be mentioned and scrutinized in future applications of HoliGRALE for other lens systems.

Comments23 pages, 15 figures. Submitted to the Open Journal of Astrophysics. Comments welcome

论文原文

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