Accurate redshift calibration is required to obtain unbiased cosmological information from large-scale galaxy surveys. In a forward modelling approach, the redshift distribution n(z) of a galaxy sample is measured using a parametric galaxy population model constrained by observations. We use a model that captures the redshift evolution of the galaxy luminosity functions, colours, and morphology, for red and blue samples. We constrain this model via simulation-based inference, using factorized Approximate Bayesian Computation (ABC) at the image level. We apply this framework to HSC deep field images, complemented with photometric redshifts from COSMOS2020. The simulated telescope images include realistic observational and instrumental effects. By applying the same processing and selection to real data and simulations, we obtain a sample of n(z) distributions from the ABC posterior. The photometric properties of the simulated galaxies are in good agreement with those from the real data, including magnitude, colour and redshift joint distributions. We compare the posterior n(z) from our simulations to the COSMOS2020 redshift distributions obtained via template fitting photometric data spanning the wavelength range from UV to IR. We mitigate sample variance in COSMOS by applying a reweighting technique. We thus obtain a good agreement between the simulated and observed redshift distributions, with a difference in the mean at the 1σ level up to a magnitude of 24 in the i band. We discuss how our forward model can be applied to current and future surveys and be further extended. The ABC posterior and further material will be made publicly available at https://cosmology.ethz.ch/research/software-lab/ufig.html.

中文翻译：

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基于模拟的深场推理：星系种群模型和红移分布

需要精确的红移校准才能从大规模星系调查中获得无偏差的宇宙学信息。在正演建模方法中，红移分布n（z）的星系样本是使用受观测约束的参数星系总体模型来测量的。我们使用一个模型来捕获红色和蓝色样本的星系光度函数、颜色和形态的红移演化。我们通过基于模拟的推理，在图像级别使用因式分解近似贝叶斯计算（ABC）来约束该模型。我们将此框架应用于 HSC 深场图像，并辅以 COSMOS2020 的光度红移。模拟望远镜图像包括真实的观测和仪器效果。通过对真实数据和模拟应用相同的处理和选择，我们获得了样本n（z) ABC 后验分布。模拟星系的光度特性与真实数据的光度特性非常一致，包括星等、颜色和红移联合分布。我们对比一下后路n（z）从我们的模拟到通过模板拟合光度数据获得的 COSMOS2020 红移分布，该数据涵盖从 UV 到 IR 的波长范围。我们通过应用重新加权技术来减轻 COSMOS 中的样本方差。因此，我们在模拟和观察到的红移分布之间获得了很好的一致性，在 1 处均值存在差异σ等级达到24级我乐队。我们讨论如何将我们的前瞻模型应用于当前和未来的调查并进一步扩展。 ABC 后面的内容和进一步的材料将在以下网址公开提供：https://cosmology.ethz.ch/research/software-lab/ufi.html。