星系的初光与形成（FLAGS）I：JWST/NIRCam数密度计数与河外背景光作为星系形成模型的约束
First Light and Assembly of GalaxieS (FLAGS) I: The JWST/NIRCam Number Counts and IGL as Constraints on Galaxy Formation Models
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中文总结 AI 辅助
该研究推出FLAGS系列，利用JWST/NIRCam数据测量星系数密度计数与IGL，发现IGL不可靠，SC-SAM模型表现最佳，数密度计数可可靠评估星系演化模型。
中文摘要 AI 辅助
JWST观测已结合SED拟合来推断不同宇宙时期星系的物理性质，揭示出与理论模型预测存在的张力，但该过程相关的偏差尚未被充分理解，这限制了其真正的约束能力。我们推出“星系的初光与形成（First Light and Assembly of GalaxieS，FLAGS）”系列研究，将利用正向建模以更可靠的直接可观测量来检验模型。我们描述了对30个独立天区、覆盖超过1平方度的NIRCam成像数据的一致性处理，该数据可用于测量0.9-4.4微米波段的星系数密度计数。在最长波长处，河外背景光（Integrated Galaxy Light，IGL）的约束精度约为2.5%，在2.77微米和4.10微米处分别给出6.92+0.17 -0.17 nW·m⁻²·sr⁻¹和3.46+0.09 -0.08 nW·m⁻²·sr⁻¹的新约束。我们将这些测量结果与星系演化模型的预测进行比较，发现IGL并非衡量模型性能的可靠指标；直接与数密度计数对比则显示，SC-SAM是表现最佳的模型（约化卡方值χ²ν=18.6），其相比SAGE的优异表现源于低质量暗晕中超新星（SNe）的有效反馈。我们研究了测光系统误差和正向建模不确定性的影响，确认数密度计数可作为评估模型预测及未来开展基于模拟的天体物理参数推断的可靠手段。
英文摘要
JWST observations have been used in conjunction with SED fitting to infer the physical properties of galaxies throughout cosmic time, revealing tensions with the predictions of theoretical models. However, the biases associated with this process are poorly understood, which limits its true constraining power. We introduce the First Light and Assembly of GalaxieS (FLAGS) series, which will leverage forward modelling to confront models with more reliable direct observables. We describe the consistent processing of NIRCam imaging spanning $>1 \ \mathrm{deg}^{\, 2}$ across 30 independent fields, which can be used to measure the galaxy number counts from $0.9-4.4 \ μ\mathrm{m}$. The integrated galaxy light (IGL) is constrained with a certainty of $\sim2.5\%$ at the longest wavelengths, producing novel constraints of $6.92^{\, +0.17}_{\, -0.17}$ and $3.46^{\, +0.09}_{\, -0.08} \ \mathrm{nW\,m^{-2}\,sr^{-1}}$ at $2.77$ and $4.10 \ \mathrm{μm}$ respectively. We compare these measurements with predictions from galaxy evolution models and find that the IGL is an unreliable measure of model performance. Comparing against the number counts directly reveals SC-SAM as the best-performing model ($χ^{2}_ν=18.6$), with its superior performance relative to SAGE attributed to efficient SNe feedback in low-mass halos. We investigate the impact of systematic photometry and forward modelling uncertainties, confirming that the number counts can be a reliable means of evaluating model predictions and performing simulation-based astrophysical parameter inference in the future.
