AI 中文总结
该研究基于DESI和SDSS样本的补偿conformity统计量，发现其可抑制非线性聚类、暴露线性物质关联，能从观测数据中挽救线性聚类信息，相关模拟可重现其定性行为。
AI 中文摘要
星系 conformity（ conformity 指星系 conformity 现象，即相邻星系属性间的关联）关联着邻近星系的属性，通常被解读为星系成团偏差占据的特征。我们研究了颜色选择的 DESI BGS 和 SDSS MGS 样本中的投影和红移空间补偿 conformity 统计量，这些统计量结合了相关星系群体的关联，抑制了共享的非线性聚类贡献，同时保留了差分大尺度响应。我们测试这是否能暴露线性物质关联函数的形状，而普通颜色选择的聚类具有尺度依赖的非线性响应。我们将星系分为红色和蓝色子样本，测量普通关联、conformity 以及投影和红移空间单极子中的补偿组合，默认使用中心主星系。我们拟合线性物质模板，用有效核诊断响应，并与 MTNG、FLAMINGO 和 MDPL2--SAG 进行比较。普通高颜色聚类大致遵循线性模板，但呈现出尺度依赖的小尺度响应。在 DESI 中，Δf₀(s)、投影 Δf(rₚ) 和 Cw(rₚ) 在很大程度上追踪线性物质形状进入非线性区域，这与非线性聚类模式被抑制同时保留类线性物质模式的情况一致，该效应对中心主星系和致密样本更强。投影有效核在低视线分离处增强，有助于残差类似 ξᵐᵐˡⁱⁿ(rₚ) 而非 wᵐᵐˡⁱⁿ(rₚ)。模拟以模型依赖的振幅和残差尺度依赖重现了定性行为。这些结果表明，对成团敏感的群体差异可过滤非线性聚类模式，不过在用于精确宇宙学之前，必须校准残留的非线性污染。
英文摘要
Galactic conformity links the properties of neighbouring galaxies and is usually interpreted as a signature of assembly-biased galaxy occupation. We study projected and redshift-space compensated conformity statistics in colour-selected DESI BGS and SDSS MGS samples. These combine correlations of related galaxy populations, suppressing shared nonlinear clustering contributions while retaining a differential large-scale response. We test whether this exposes the linear matter correlation-function shape where ordinary colour-selected clustering has a scale-dependent nonlinear response. We split galaxies into red and blue subsamples and measure ordinary correlations, conformity, and compensated combinations in projection and redshift-space monopoles, using central primaries by default. We fit linear matter templates, diagnose the response with effective kernels, and compare with MTNG, FLAMINGO, and MDPL2--SAG. Ordinary high-colour clustering broadly follows the linear templates but develops a scale-dependent small-scale response. In DESI, $Δf_0(s)$, projected $Δf(r_p)$, and $C_w(r_p)$ track the linear matter shape substantially further into the nonlinear regime, consistent with suppression of nonlinear clustering modes while leaving a linear-matter-like mode visible. The effect is stronger for central-primary and dense samples. Projected effective kernels are enhanced at low line-of-sight separations, helping the residual resemble $ξ_{\rm mm}^{\rm lin}(r_p)$ rather than $w_{\rm mm}^{\rm lin}(r_p)$. Simulations reproduce the qualitative behaviour with model-dependent amplitudes and residual scale dependence. These results suggest that assembly-sensitive population differences can filter nonlinear clustering modes, although surviving nonlinear contamination must be calibrated before precision cosmological use. (abridged)
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