论文标题
部分可观测时空混沌系统的无模型预测
The halo bias for number counts on the light cone from relativistic N-body simulations
论文作者
论文摘要
我们介绍了光环数计数及其两点统计数据,即可观察的角功率谱,该量首次从相对论的N体模拟中提取。这项工作中使用的光环目录是根据相对论的N体型Gevolution构建的,并且使用非扰动射线追踪方法计算出观察到的源的红移和角度位置,其中包括所有相对论标量贡献对数量计数的贡献。我们研究了线性偏置处方的有效性和局限性,以描述我们的模拟功率谱。特别是,我们评估了大尺度上不同偏差测量值的一致性,并且估计线性偏差在统计误差内对数据进行建模是准确的。然后,我们在此上下文中未探索的一系列红移和鳞片上测试了二阶扰动偏置扩展,即$ 0.4 \ le \ bar {z} \ le 2 $ 2 $ for scales $ \ ell_ \ ell_ \ ell_ \ ell_ \ mathrm {max} \ sim} \ sim 1000 $。我们发现,在相等红移的角度谱可以以高精度建模,而偏差参数的数量最小的扩展,即使用包括线性偏置和潮汐偏置的两参数模型。我们表明,该模型的性能比没有潮汐偏见的模型要好得多,但具有二次偏见是额外的自由度,并且后者以$ \ bar {z} \ ge 0.7 $不准确。最后,我们从模拟中提取光环数计数和镜头收敛的互相关。我们表明,该互相关的线性偏差的估计与仅基于聚类统计数据的测量值一致,并且至关重要的是要考虑到晕圈数量计数中放大倍数的影响,以避免计算出的偏置中系统的变化。
We present the halo number counts and its two-point statistics, the observable angular power spectrum, extracted for the first time from relativistic N-body simulations. The halo catalogues used in this work are built from the relativistic N-body code gevolution, and the observed redshift and angular positions of the sources are computed using a non-perturbative ray-tracing method, which includes all relativistic scalar contributions to the number counts. We investigate the validity and limitations of the linear bias prescription to describe our simulated power spectra. In particular, we assess the consistency of different bias measurements on large scales, and we estimate up to which scales a linear bias is accurate in modelling the data, within the statistical errors. We then test a second-order perturbative bias expansion for the angular statistics, on a range of redshifts and scales previously unexplored in this context, that is $0.4 \le \bar{z} \le 2$ up to scales $\ell_\mathrm{max} \sim 1000$. We find that the angular power spectra at equal redshift can be modelled with high accuracy with a minimal extension of the number of bias parameters, that is using a two-parameter model comprising linear bias and tidal bias. We show that this model performs significantly better than a model without tidal bias but with quadratic bias as extra degree of freedom, and that the latter is inaccurate at $\bar{z} \ge 0.7$. Finally, we extract from our simulations the cross-correlation of halo number counts and lensing convergence. We show that the estimate of the linear bias from this cross-correlation is consistent with the measurements based on the clustering statistics alone, and that it is crucial to take into account the effect of magnification in the halo number counts to avoid systematic shifts in the computed bias.