黑暗能源调查中IA型超新星的镜头弱

论文标题

黑暗能源调查中IA型超新星的镜头弱

Weak Lensing of Type Ia Supernovae from the Dark Energy Survey

论文作者

Macaulay, E., Bacon, D., Nichol, R. C., Davis, T. M., Elvin-Poole, J., Brout, D., Carollo, D., Glazebrook, K., Hinton, S. R., Lewis, G. F., Lidman, C., Möller, A., Sako, M., Scolnic, D., Smith, M., Sommer, N. E., Tucker, B. E., Abbott, T. M. C., Aguena, M., Annis, J., Avila, S., Bertin, E., Bhargava, S., Brooks, D., Burke, D. L., Rosell, A. Carnero, Kind, M. Carrasco, Carretero, J., Castander, F. J., Costanzi, M., da Costa, L. N., Desai, S., Diehl, H. T., Doel, P., Flaugher, B., Foley, R. J., García-Bellido, J., Gaztanaga, E., Gerdes, D. W., Gruen, D., Gruendl, R. A., Gschwend, J., Gutierrez, G., Hollowood, D. L., Honscheid, K., Huterer, D., James, D. J., Kuehn, K., Kuropatkin, N., Lahav, O., Lima, M., Maia, M. A. G., Marshall, J. L., Melchior, P., Menanteau, F., Miquel, R., Palmese, A., Plazas, A. A., Romer, A. K., Roodman, A., Sanchez, E., Scarpine, V., Schubnell, M., Serrano, S., Sevilla-Noarbe, I., Soares-Santos, M., Suchyta, E., Swanson, M. E. C., Tarle, G., Varga, T. N., Walker, A. R., Weller, J.

论文摘要

我们考虑弱重力镜头对从黑暗能源调查（DES）的1至3年级观察到的196个光谱型IA型超新星（SNE IA）的观察结果。我们同时测量角度相关函数和由弱透镜引起的非高斯偏度。这种方法的优点是对SNE IA幅度的固有分散不敏感。我们将这两种效果的幅度建模为$σ_8$的函数，并找到$σ_8= 1.2^{+0.9} _ { - 0.8} $。我们还将我们的方法应用于关节曲线分析（JLA）的488 SNE的子样本（选择与我们用于这项工作的红移范围相匹配），并找到$σ_8= 0.8 = 0.8^{+1.1} _ { - 0.7} $。 DES-SN和JLA较大数量的SNE之间的$σ_8$的可比不确定性突出了DES-SN样本同质性的好处，以及校准和数据分析的改进。

We consider the effects of weak gravitational lensing on observations of 196 spectroscopically confirmed Type Ia Supernovae (SNe Ia) from years 1 to 3 of the Dark Energy Survey (DES). We simultaneously measure both the angular correlation function and the non-Gaussian skewness caused by weak lensing. This approach has the advantage of being insensitive to the intrinsic dispersion of SNe Ia magnitudes. We model the amplitude of both effects as a function of $σ_8$, and find $σ_8 = 1.2^{+0.9}_{-0.8}$. We also apply our method to a subsample of 488 SNe from the Joint Light-curve Analysis (JLA) (chosen to match the redshift range we use for this work), and find $σ_8 = 0.8^{+1.1}_{-0.7}$. The comparable uncertainty in $σ_8$ between DES-SN and the larger number of SNe from JLA highlights the benefits of homogeneity of the DES-SN sample, and improvements in the calibration and data analysis.

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