论文标题

使用HSC-SDSS模拟目录验证最小的星系偏置法来推断宇宙学参数推理

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

论文作者

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

论文摘要

我们评估了一种摄动理论的性能,该方法是从星系 - 半甲状体弱透镜($Δς$)和预计的星系聚类($ W _ {\ rm p} $)的联合测量中推断宇宙学参数的性能。为此,我们使用了基于模仿Subaru HSC-Y1和SDSS星系的大量$ n $体体模拟构建的各种模拟星系目录,并将方法应用于模拟信号,以解决是否恢复模拟中基本的真正宇宙学参数。 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} $和$σ_8$)在68%的可靠间隔内,对于我们研究的所有模拟,包括实现组装偏差效应的模拟。如果星系形成/演变中固有的物理过程仅限于量表下的局部小尺度,那么这意味着实际空间可观察物在过滤与傅立叶空间对应物相比,实际空间可观察到在过滤小尺度非线性效应中具有优势。此外,我们发现一个理论模板,包括高阶偏差贡献,例如非线性偏差参数$(B_2)$不会改善宇宙学的约束,而是与基线$ B_1 $ -METHOD相比会导致更大的参数偏差。

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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