Time delay lens modelling challenge
Time delay lens modelling challenge
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DOI：
10.1093/mnras/stab484
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发表时间：
2020-06
影响因子：
4.8
通讯作者：
Xuheng Ding;T. Treu;S. Birrer;G. C. Chen;J. Coles;P. Denzel;Matteo Frigo;A. Galan;P. Marshall;M. Millon;A. More;A. Shajib;D. Sluse;H. Tak;Dandan Xu;M. Auger;V. Bonvin;H. Chand;F. Courbin;G. Despali;C. Fassnacht;D. Gilman;S. Hilbert;S. R. Kumar;J. Lin;J. Park;P. Saha;S. Vegetti;L. V. D. Vyvere;L. Williams
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文献类型：
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作者：
Xuheng Ding;T. Treu;S. Birrer;G. C. Chen;J. Coles;P. Denzel;Matteo Frigo;A. Galan;P. Marshall;M. Millon;A. More;A. Shajib;D. Sluse;H. Tak;Dandan Xu;M. Auger;V. Bonvin;H. Chand;F. Courbin;G. Despali;C. Fassnacht;D. Gilman;S. Hilbert;S. R. Kumar;J. Lin;J. Park;P. Saha;S. Vegetti;L. V. D. Vyvere;L. Williams
近年来，方法和数据上的突破使引力时间延迟成为测量哈勃常数$H_0$的非常强大的工具。然而，已发表的最先进的分析需要1年的专家调查时间和每个系统高达100万小时的计算时间。此外，随着精度的提高，识别和减少系统不确定性至关重要。通过这种时间延迟透镜建模挑战，我们的目标是通过模拟数据集的盲分析来评估建模技术的精度和准确度水平，这些建模技术目前足够快，可以处理50阶透镜。结果表明，在Rung 1和Rung 2中，仅使用点源位置的方法往往具有较低的精度（10 - 20美元），同时保持准确。在Rung 2中，利用成像和运动学数据集的全部信息的方法可以在目标精度（$）内恢复$H_0$|一|< 2\%$）和精度（$< 6\%$每个系统），即使在存在已知的点扩散函数和复杂的源形态。对Rung 3的揭盲后分析表明，射线追踪宇宙学模拟的数值精度不足以在百分比水平上测试透镜建模方法，使得结果难以解释。为了在系统不确定性的调查方面取得进一步进展，需要改进模拟的新挑战。为了完整起见，我们在附录中列出了Rung 3的结果，并使用它们来讨论在未来盲测挑战中减轻类似微妙数据生成影响的各种方法。
In recent years, breakthroughs in methods and data have enabled gravitational time delays to emerge as a very powerful tool to measure the Hubble constant $H_0$. However, published state-of-the-art analyses require of order 1 year of expert investigator time and up to a million hours of computing time per system. Furthermore, as precision improves, it is crucial to identify and mitigate systematic uncertainties. With this time delay lens modelling challenge we aim to assess the level of precision and accuracy of the modelling techniques that are currently fast enough to handle of order 50 lenses, via the blind analysis of simulated datasets. The results in Rung 1 and Rung 2 show that methods that use only the point source positions tend to have lower precision ($10 - 20\%$) while remaining accurate. In Rung 2, the methods that exploit the full information of the imaging and kinematic datasets can recover $H_0$ within the target accuracy ($ |A| < 2\%$) and precision ($< 6\%$ per system), even in the presence of poorly known point spread function and complex source morphology. A post-unblinding analysis of Rung 3 showed the numerical precision of the ray-traced cosmological simulations to be insufficient to test lens modelling methodology at the percent level, making the results difficult to interpret. A new challenge with improved simulations is needed to make further progress in the investigation of systematic uncertainties. For completeness, we present the Rung 3 results in an appendix, and use them to discuss various approaches to mitigating against similar subtle data generation effects in future blind challenges.