SALT3: An Improved Type Ia Supernova Model for Measuring Cosmic Distances
SALT3: An Improved Type Ia Supernova Model for Measuring Cosmic Distances
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DOI：
10.3847/1538-4357/ac30d8
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发表时间：
2021-04
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通讯作者：
W. Kenworthy;D. Jones;M. Dai;R. Kessler;D. Scolnic;D. Brout;M. Siebert;J. Pierel;K. Dettman-K.-Det
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作者：
W. Kenworthy;D. Jones;M. Dai;R. Kessler;D. Scolnic;D. Brout;M. Siebert;J. Pierel;K. Dettman-K.-Det
Ia型超新星（SNe Ia）的光谱能量分布（SED）模型是测量大红移范围内精确距离和限制性宇宙学参数的关键工具。我们提出了一个改进的模型框架，SALT3，它比目前的模型有几个优点，包括领先的SALT2模型（SALT2.4）。虽然SALT3具有类似的原理，但它与SALT2的不同之处在于改进了对不确定性的估计，更好地分离颜色和光曲线拉伸，以及公开可用的训练代码。我们介绍了我们的训练方法在具有1207个光谱的1083个SNe交叉校准编译中的应用。我们的编制比SALT2训练样本大2.5倍，大大降低了校准不确定性。由此产生的训练SALT3。与SALT2相比，K21模型具有扩展的波长范围2000-11,000 Å （1800 Å更红）和减少的不确定性，能够准确使用低z I和iz光度带。包括这些之前被丢弃的条带，SALT3。K21使低z基础和CfA3样品的哈勃散射分别降低了15%和10%。为了检查潜在的系统不确定性，我们比较了训练汇编中低（0.01 < z < 0.2）和高（0.4 < z < 0.6）红移SNe的距离，发现SALT2.4和SALT3.K21之间有3±14 mmag的不显著偏移。而SALT3。利用光学数据对K21模型进行训练，该方法可用于建立罗马空间望远镜静帧近红外样本的模型。我们的开源培训代码、公共培训数据、模型和文档可在https://saltshaker.readthedocs.io/en/latest/上获得，该模型集成到sncosmo和SNANA软件包中。
A spectral-energy distribution (SED) model for Type Ia supernovae (SNe Ia) is a critical tool for measuring precise and accurate distances across a large redshift range and constraining cosmological parameters. We present an improved model framework, SALT3, which has several advantages over current models—including the leading SALT2 model (SALT2.4). While SALT3 has a similar philosophy, it differs from SALT2 by having improved estimation of uncertainties, better separation of color and light-curve stretch, and a publicly available training code. We present the application of our training method on a cross-calibrated compilation of 1083 SNe with 1207 spectra. Our compilation is 2.5× larger than the SALT2 training sample and has greatly reduced calibration uncertainties. The resulting trained SALT3.K21 model has an extended wavelength range 2000–11,000 Å (1800 Å redder) and reduced uncertainties compared to SALT2, enabling accurate use of low-z I and iz photometric bands. Including these previously discarded bands, SALT3.K21 reduces the Hubble scatter of the low-z Foundation and CfA3 samples by 15% and 10%, respectively. To check for potential systematic uncertainties, we compare distances of low (0.01 < z < 0.2) and high (0.4 < z < 0.6) redshift SNe in the training compilation, finding an insignificant 3 ± 14 mmag shift between SALT2.4 and SALT3.K21. While the SALT3.K21 model was trained on optical data, our method can be used to build a model for rest-frame NIR samples from the Roman Space Telescope. Our open-source training code, public training data, model, and documentation are available at https://saltshaker.readthedocs.io/en/latest/, and the model is integrated into the sncosmo and SNANA software packages.