论文标题
关于星系偏见不确定性对原始非高斯性约束的影响
On the impact of galaxy bias uncertainties on primordial non-Gaussianity constraints
论文作者
论文摘要
我们研究了不确定性对星系偏差参数之间假定关系的影响对本地png $ f _ {\ rm nl} $参数的约束的影响。我们专注于线性密度星系偏差$ B_1 $与本地PNG偏见$ b_ϕ $之间的关系，该预测设置具有多阶段的Galaxy Power Spectrum和Bispectrum数据。我们考虑了星系偏差的两个参数化：1）一个受通用关系启发的启发，其中$ b_ϕ =2Δ_c\ left（b_1 -p \ right）$和$ p $是一个免费参数； 2）另一个直接适用于$ f _ {\ rm nl} b_ϕ $的偏差参数和$ f _ {\ rm nl} $的产品。 $ f _ {\ rm nl} -p $平面上的约束是显着的，并且在$ f _ {\ rm nl} $上的边缘化约束的中心值和宽度都敏感地取决于$ p $。假设固定的$ p = 1 $在约束中，基准值为$ p = 0.55 $可以偏向推断的$ f _ {\ rm nl} $ to $0.5σ$至$1σ$;但是，在我们的设置中，该基准价值周围的$ΔP\约0.5美元足以返回无偏的约束。在电源谱分析中，参数化2，在$ b_ϕ $上没有假设，可以区分$ f _ {\ rm nl} \ neq 0 $具有与参数化1相同的意义1，假设$ b_ϕ $的完美知识（$ f _ {\ rm nl nl} $的值）。参数化2的缺点是，双光谱信息的添加不如参数化1中的有益。我们的结果强烈促使在PNG约束分析中纳入缓解策略，以及在PNG约束分析中的偏置策略，以及在偏见参数之间的关系中进一步的理论研究，以更好地告知这些策略。
We study the impact that uncertainties on assumed relations between galaxy bias parameters have on constraints of the local PNG $f_{\rm NL}$ parameter. We focus on the relation between the linear density galaxy bias $b_1$ and local PNG bias $b_ϕ$ in an idealized forecast setup with multitracer galaxy power spectrum and bispectrum data. We consider two parametrizations of galaxy bias: 1) one inspired by the universality relation where $b_ϕ= 2δ_c\left(b_1 - p\right)$ and $p$ is a free parameter; and 2) another in which the product of bias parameters and $f_{\rm NL}$, like $f_{\rm NL} b_ϕ$, is directly fitted for. The constraints on the $f_{\rm NL}-p$ plane are markedly bimodal, and both the central value and width of marginalized constraints on $f_{\rm NL}$ depend sensitively on the priors on $p$. Assuming fixed $p=1$ in the constraints with a fiducial value of $p=0.55$ can bias the inferred $f_{\rm NL}$ by $0.5σ$ to $1σ$; priors $Δp \approx 0.5$ around this fiducial value are however sufficient in our setup to return unbiased constraints. In power spectrum analyses, parametrization 2, that makes no assumptions on $b_ϕ$, can distinguish $f_{\rm NL} \neq 0$ with the same significance as parametrization 1 assuming perfect knowledge of $b_ϕ$ (the value of $f_{\rm NL}$ is however left unknown). A drawback of parametrization 2 is that the addition of the bispectrum information is not as beneficial as in parametrization 1. Our results motivate strongly the incorporation of mitigation strategies for bias uncertainties in PNG constraint analyses, as well as further theoretical studies on the relations between bias parameters to better inform those strategies.
