论文标题
在蒙面宇宙剪切功率光谱中传播残留偏见
Propagating residual biases in masked cosmic shear power spectra
论文作者
论文摘要
在本文中,我们得出了弱透镜形状测量偏见传播到宇宙剪切功率光谱中的完整表达,包括丢失数据的效果。我们使用模拟显示,可以忽略偏差参数中高于一阶的术语,并且偏差的影响只能通过术语仅取决于乘法偏差字段的均值来捕获。我们确定B模式功率包含有关乘法偏置的信息。我们发现,如果没有关于残留乘法偏差$ΔM$ $ $ $ $和随机椭圆方差$σ_E$的限制,则可以完全退化,而在应用稳定的振幅$ a $通过经典的Mareginalization Parad Parad Parad Parad Parad Parad Parad Parad parad parad parad parad a $时,就会完全退化。使用全天空高斯的随机场模拟,我们发现$(1+2Δm)的组合对于联合EE和BB功率频谱的可能性是公正的,如果随机椭圆方差的错误和平均值(精度和准确性)已知比$σ(σ_e)\ leq 0.05 $ nequectect of $ q. 01,则已知的椭圆方差(精确性和准确性)。优于$σ(m)\ leq 0.07 $和$ΔM\ leq 0.01 $。
In this paper we derive a full expression for the propagation of weak lensing shape measurement biases into cosmic shear power spectra including the effect of missing data. We show using simulations that terms higher than first order in bias parameters can be ignored and the impact of biases can be captured by terms dependent only on the mean of the multiplicative bias field. We identify that the B-mode power contains information on the multiplicative bias. We find that without priors on the residual multiplicative bias $δm$ and stochastic ellipticity variance $σ_e$ that constraints on the amplitude of the cosmic shear power spectrum are completely degenerate, and that when applying priors the constrained amplitude $A$ is slightly biased low via a classic marginalisation paradox. Using all-sky Gaussian random field simulations we find that the combination of $(1+2δm)A$ is unbiased for a joint EE and BB power spectrum likelihood if the error and mean (precision and accuracy) of the stochastic ellipticity variance is known to better than $σ(σ_e)\leq 0.05$ and $Δσ_e\leq 0.01$, or the multiplicative bias is known to better than $σ(m)\leq 0.07$ and $Δm\leq 0.01$.