中文

利用宿主星系光谱探究Ia型超新星标准化中的系统误差

宇宙学与河外天体物理 2022-10-26 v3 星系天体物理

摘要

我们利用暗能量巡天(DES)中测光识别的Ia型超新星(SNe Ia)宿主星系的堆叠光谱,寻找哈勃图残差与宿主星系光谱性质之间的相关性。对按哈勃残差分箱的堆叠光谱采用全谱拟合技术,我们发现哈勃残差与依赖光谱吸收特征的宿主星系性质(如恒星种群年龄、金属丰度和质光比)之间不存在趋势证据(<1.3σ< 1.3\sigma)。然而,我们发现哈勃残差与[OII]线强(4.4σ4.4\sigma)以及巴尔末发射线(3σ3\sigma)之间存在显著趋势。这些趋势弱于由宽波段测光得到的哈勃残差与宿主星系恒星质量之间的已知趋势(7.2σ7.2\sigma)。在光变曲线修正后,我们看到较暗的SNe Ia位于具有更大谱线强度的星系中。我们还利用Hβ{\beta}和Hγ{\gamma}发现了哈勃残差与巴尔末减幅(尘埃红化的度量)之间的趋势(3σ3\sigma)。由相关系数量化的该趋势在较红SNe Ia中略更显著,表明较蓝SNe Ia相对不受宿主星际介质中尘埃的影响,且尘埃导致了当前哈勃图的弥散,影响宇宙学参数的测量。

关键词

引用

@article{arxiv.2206.12085,
  title  = {Using Host Galaxy Spectroscopy to Explore Systematics in the Standardisation of Type Ia Supernovae},
  author = {M. Dixon and C. Lidman and J. Mould and L. Kelsey and D. Brout and A. Möller and P. Wiseman and M. Sullivan and L. Galbany and T. M. Davis and M. Vincenzi and D. Scolnic and G. F. Lewis and M. Smith and R. Kessler and A. Duffy and E. Taylor and C. Flynn and T. M. C. Abbott and M. Aguena and S. Allam and F. Andrade-Oliveir and J. Annis and J. Asorey and E. Bertin and S. Bocquet and D. Brooks and D. L. Burke and A. Carnero Rosell and D. Carollo and M. Carrasco Kind and J. Carretero and M. Costanzi and L. N. da Costa and M. E. S. Pereira and P. Doel and S. Everett and I. Ferrero and B. Flaugher and D. Friedel and J. Frieman and J. García-Bellido and M. Gatti and D. W. Gerdes and K. Glazebrook and D. Gruen and J. Gschwend and G. Gutierrez and S. R. Hinton and D. L. Hollowood and K. Honscheid and D. Huterer and D. J. James and K. Kuehn and N. Kuropatkin and U. Malik and M. March and F. Menanteau and R. Miquel and R. Morgan and B. Nichol and R. L. C. Ogando and A. Palmese and F. Paz-Chinchón and A. Pieres and A. A. Plazas Malagón and M. Rodriguez-Monroy and A. K. Romer and E. Sanchez and V. Scarpine and I. Sevilla-Noarbe and M. Soares-Santos and E. Suchyta and G. Tarle and C. To and B. E. Tucker and D. L. Tucker and T. N. Varga},
  journal= {arXiv preprint arXiv:2206.12085},
  year   = {2022}
}

备注

15 pages, 10 figures. Accepted for publication in MNRAS