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arXiv 2008.06873astro-ph.CO
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用HSC-SDSS模拟星表验证宇宙学参数推断的最小星系偏差方法

Validating a minimal galaxy bias method for cosmological parameter inference using HSC-SDSS mock catalogs

Sunao Sugiyama, Masahiro Takada, Yosuke Kobayashi, Hironao Miyatake, Masato Shirasaki, Takahiro Nishimichi, Youngsoo Park

备注：
Submitted to PRD, A revised version in response to the referee's comments
发表信息：
Phys. Rev. D 102, 083520 (2020)
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摘要：

我们评估的性能的扰动理论启发的方法推断宇宙学参数的联合测量星系星系弱透镜（$ΔΣ$）和投影星系团（$w_{\rm p}$）。为了做到这一点，我们使用各种各样的模拟星系目录的基础上构建了一个大的$N$体模拟斯巴鲁HSC-Y1和SDSS星系，并应用该方法的模拟信号，以解决是否恢复模拟的基本真实的宇宙学参数。我们发现，只要采用适当的尺度切割，$ΔΣ$和$w_{\rm p}$分别采用$12$和$8~h^{-1}{\rm Mpc}$，一个只使用线性偏置参数$b_1$和非线性物质功率谱的“最小偏置”模型就能恢复真实的宇宙学参数（此处侧重于$Ω_{\rm m}$和$σ_8$）在68%可信区间内，对于我们研究的所有模拟，包括其中实现了组装偏差效应的模拟。这是预期的，如果物理过程固有的星系形成/演化局限于本地，小尺度下的尺度切割，从而意味着实空间观测有一个优势，在过滤出的影响，小尺度的非线性效应的参数估计，相比，他们的傅立叶空间的同行。此外，我们发现，包括高阶偏置贡献，如非线性偏置参数$(b_2)$的理论模板并没有改善宇宙学的约束，而是导致一个更大的参数偏差相比，基线$b_1$ -方法。

英文摘要：

We assess the performance of a perturbation theory inspired method for inferring cosmological parameters from the joint measurements of galaxy-galaxy weak lensing ($ΔΣ$) and the projected galaxy clustering ($w_{\rm p}$). To do this, we use a wide variety of mock galaxy catalogs constructed based on a large set of $N$-body simulations that mimic the Subaru HSC-Y1 and SDSS galaxies, and apply the method to the mock signals to address whether to recover the underlying true cosmological parameters in the mocks. We find that, as long as the appropriate scale cuts, $12$ and $8~h^{-1}{\rm Mpc}$ for $ΔΣ$ and $w_{\rm p}$ respectively, are adopted, a "minimal-bias" model using the linear bias parameter $b_1$ alone and the nonlinear matter power spectrum can recover the true cosmological parameters (here focused on $Ω_{\rm m}$ and $σ_8$) to within the 68% credible interval, for all the mocks we study including one in which an assembly bias effect is implemented. This is as expected if physical processes inherent in galaxy formation/evolution are confined to local, small scales below the scale cut, and thus implies that real-space observables have an advantage in filtering out the impact of small-scale nonlinear effects in parameter estimation, compared to their Fourier-space counterparts. In addition, we find that a theoretical template including the higher-order bias contributions such as nonlinear bias parameter $(b_2)$ does not improve the cosmological constraints, but rather leads to a larger parameter bias compared to the baseline $b_1$-method.

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