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arXiv 0801.4041astro-ph
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Ia型超新星特殊速度引起的参数误差的量化

Quantifying parameter errors due to the peculiar velocities of type Ia supernovae

R. Ali Vanderveld

摘要:

观测到的Ia型超新星的红移和星等与我们在均匀宇宙学模型中看到的相吻合,导致了宇宙学参数的限制。然而,在进行这样的拟合时,假设采样的超新星随着哈勃流运动,即它们的特有速度为零。实际上,奇特的速度会以一种可能影响最佳拟合宇宙学参数的方式修改超新星数据。我们从理论上量化这种影响的非线性制度与蒙特卡洛分析,使用的数据从半解析星系目录,是建立从千年N体模拟。我们发现的标度关系的最佳拟合参数的错误,仅从奇特的速度,作为一个函数的超新星调查N和它的最大红移z_max的源的总数。对于低红移的巡天,我们发现这些误差可以与0.1等的内禀星等散射引起的误差在同一数量级上。对于N=2000和z_max=1.7的巡天,我们估计在最佳拟合的宇宙学常数密度和状态方程中,预期的特殊速度引起的误差可以分别为sigma_Lambda~0.009和sigma_w~0.01,其对于由于固有散射引起的误差是次主导的。我们进一步发现,丢弃低于红移z~0.01-0.02的超新星数据可以减少由于特殊速度和内在散射引起的综合误差,但只有大约10%。

英文摘要:

The fitting of the observed redshifts and magnitudes of type Ia supernovae to what we would see in homogeneous cosmological models has led to constraints on cosmological parameters. However, in doing such fits it is assumed that the sampled supernovae are moving with the Hubble flow, i.e. that their peculiar velocities are zero. In reality, peculiar velocities will modify supernova data in a way that can impact best-fit cosmological parameters. We theoretically quantify this effect in the nonlinear regime with a Monte-Carlo analysis, using data from semi-analytic galaxy catalogs that are built from the Millennium N-body simulation. We find scaling relations for the errors in best-fit parameters resulting solely from peculiar velocities, as a function of the total number of sources in a supernova survey N and its maximum redshift z_max. For low redshift surveys, we find that these errors can be of the same order of magnitude as the errors due to an intrinsic magnitude scatter of 0.1 mag. For a survey with N=2000 and z_max=1.7, we estimate that the expected peculiar velocity-induced errors in the best-fit cosmological constant density and equation of state can be sigma_Lambda~0.009 and sigma_w~0.01, respectively, which are subdominant to the errors due to the intrinsic scatter. We further find that throwing away supernova data below a redshift z~0.01-0.02 can reduce the combined error, due to peculiar velocities and the intrinsic scatter, but by only about 10%.

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