HSC成像（SuGOHI）中引力透镜物体的调查。VI。使用Space Warps进行众包镜头查找
Survey of Gravitationally-lensed Objects in HSC Imaging (SuGOHI). VI. Crowdsourced lens finding with Space Warps
摘要：
强透镜是探测宇宙学距离上星系和星系团尺度上物质分布的非常有用的探针，但很少见，也很难找到。目前已知的透镜的数量大约为1000个。我们希望使用众包来进行镜头搜索，目标是从Hyper Suprime-Cam（HSC）调查的超过442平方度的光度数据中选择的大质量星系。我们选择了一个样本的$\sim300,000$星系光度红移范围内的$0.2 < z_{phot} < 1.2$和光度推断恒星质量$\log{M_*} > 11.2$。我们在Zooniverse平台上众包了这个星系样本的镜头发现，作为Space Warps项目的一部分。为了训练的目的，该样品由一组大的模拟镜片和视觉选择的非镜片补充。近6,000名公民志愿者参与了实验。与此同时，我们使用YattaLens，一种自动透镜查找算法，在同一星系样本中查找透镜。基于对志愿者分类数据的统计分析，我们选择了最有希望的$\sim1,500$候选样本，然后进行目视检查：其中一半被证明是可能的（C级）镜片或更好的镜片。包括YattaLens发现的镜头或在Space Warps网站的讨论部分偶然发现的镜头，我们能够找到14个确定的镜头，129个可能的镜头和581个可能的镜头。YattaLens通过众包找到了一半的镜头。与目前可用的自动化算法相比，众包能够产生具有高完整性和纯度的镜片候选样品。一种混合方法，其中通过发现算法预选和/或与机器学习相结合的镜片候选样本的目视检查是众包的，将是2020年代镜片发现的可行选择。
英文摘要：
Strong lenses are extremely useful probes of the distribution of matter on galaxy and cluster scales at cosmological distances, but are rare and difficult to find. The number of currently known lenses is on the order of 1,000. We wish to use crowdsourcing to carry out a lens search targeting massive galaxies selected from over 442 square degrees of photometric data from the Hyper Suprime-Cam (HSC) survey. We selected a sample of $\sim300,000$ galaxies with photometric redshifts in the range $0.2 < z_{phot} < 1.2$ and photometrically inferred stellar masses $\log{M_*} > 11.2$. We crowdsourced lens finding on this sample of galaxies on the Zooniverse platform, as part of the Space Warps project. The sample was complemented by a large set of simulated lenses and visually selected non-lenses, for training purposes. Nearly 6,000 citizen volunteers participated in the experiment. In parallel, we used YattaLens, an automated lens finding algorithm, to look for lenses in the same sample of galaxies. Based on a statistical analysis of classification data from the volunteers, we selected a sample of the most promising $\sim1,500$ candidates which we then visually inspected: half of them turned out to be possible (grade C) lenses or better. Including lenses found by YattaLens or serendipitously noticed in the discussion section of the Space Warps website, we were able to find 14 definite lenses, 129 probable lenses and 581 possible lenses. YattaLens found half the number of lenses discovered via crowdsourcing. Crowdsourcing is able to produce samples of lens candidates with high completeness and purity, compared to currently available automated algorithms. A hybrid approach, in which the visual inspection of samples of lens candidates pre-selected by discovery algorithms and/or coupled to machine learning is crowdsourced, will be a viable option for lens finding in the 2020s.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
