模拟中的超样本协方差
Super-Sample Covariance in Simulations
摘要：
使用单独的宇宙模拟，我们准确地量化超样本协方差（SSC），通常占主导地位的抽样误差的物质功率谱估计在一个有限的体积，这是由于超级调查模式的存在。通过量化的功率谱响应的背景模式，这种方法自动捕获的拍耦合在准线性制度，晕样本方差在非线性制度和一个新的膨胀效应，改变尺度的功率谱相干整个调查量，包括重子声学振荡规模的单独影响。与直接在一套大体积模拟中使用数千个测量体积相比，它对任何测量几何结构的少量小体积模拟通常以百分之几的水平或更好的水平模拟这些影响。响应的随机性是足够小的，在准线性制度，SSC可以交替地包括通过拟合的平均密度在体积与这些固定的模板参数估计。我们还测试了晕轮模型处方，并发现协议通常优于10%的响应水平。
英文摘要：
Using separate universe simulations, we accurately quantify super-sample covariance (SSC), the typically dominant sampling error for matter power spectrum estimators in a finite volume, which arises from the presence of super survey modes. By quantifying the power spectrum response to a background mode, this approach automatically captures the separate effects of beat coupling in the quasilinear regime, halo sample variance in the nonlinear regime and a new dilation effect which changes scales in the power spectrum coherently across the survey volume, including the baryon acoustic oscillation scale. It models these effects at typically the few percent level or better with a handful of small volume simulations for any survey geometry compared with directly using many thousands of survey volumes in a suite of large volume simulations. The stochasticity of the response is sufficiently small that in the quasilinear regime, SSC can be alternately included by fitting the mean density in the volume with these fixed templates in parameter estimation. We also test the halo model prescription and find agreement typically at better than the 10% level for the response.
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