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arXiv 1104.1399astro-ph.COastro-ph.IM
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高斯化弱透镜信号中的宇宙学信息

Cosmological information in Gaussianised weak lensing signals

B. Joachimi, A. N. Taylor, A. Kiessling

摘要:

研究了高斯化弱引力透镜会聚场中所包含的宇宙学信息。采用Box-Cox变换来确定高斯性的最佳变换,我们开发了变换后的功率谱的分析模型,包括噪声和平滑的影响。我们发现,优化的Box-Cox变换在高斯化收敛性方面比偏移对数变换表现得更好,但对于信噪比和参数约束,两者都产生非常相似的结果。没有一个变换能够消除不同角频率之间的功率谱的相关性,我们证明了这对宇宙学的误差有显着的影响。高斯功率谱的分析模型产生良好的拟合模拟和无偏的参数估计在大多数情况下,其中的例外可以追溯到建模的原始收敛的高阶相关性的限制。在理想的情况下,没有星系的形状噪声,我们发现一个增加的累积信号噪声的2.6倍的角频率高达1500,并在欧米茄_m-sigma_8平面的置信区域的面积减少了4.4倍的q值方面的最佳性能的转换。当添加一个现实水平的形状噪声时,所有的变换都表现不佳,角频率的去相关性很小,信噪比最大增加34%,甚至宇宙学参数的误差也略有下降。我们认为,要找到高斯化变换的实际用途,将需要超越的收敛的一点分布的变换,深入到非线性制度的分析,并诉诸于参数空间的探索,通过模拟。(节略)

英文摘要:

We investigate the information on cosmology contained in Gaussianised weak gravitational lensing convergence fields. Employing Box-Cox transformations to determine optimal transformations to Gaussianity, we develop analytical models for the transformed power spectrum, including effects of noise and smoothing. We find that optimised Box-Cox transformations perform substantially better than an offset logarithmic transformation in Gaussianising the convergence, but both yield very similar results for the signal-to-noise and parameter constraints. None of the transformations is capable of eliminating correlations of the power spectra between different angular frequencies, which we demonstrate to have a significant impact on the errors on cosmology. Analytic models of the Gaussianised power spectrum yield good fits to the simulations and produce unbiased parameter estimates in the majority of cases, where the exceptions can be traced back to the limitations in modelling the higher-order correlations of the original convergence. In the idealistic case, without galaxy shape noise, we find an increase in cumulative signal-to-noise by a factor of 2.6 for angular frequencies up to 1500, and a decrease in the area of the confidence region in the Omega_m-sigma_8 plane by a factor of 4.4 in terms of q-values for the best-performing transformation. When adding a realistic level of shape noise, all transformations perform poorly with little decorrelation of angular frequencies, a maximum increase in signal-to-noise of 34%, and even marginally degraded errors on cosmological parameters. We argue that, to find Gaussianising transformations of practical use, one will need to go beyond transformations of the one-point distribution of the convergence, extend the analysis deeper into the non-linear regime, and resort to an exploration of parameter space via simulations. (abridged)

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