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arXiv 1401.4065astro-ph.CO
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SALT-II Ia型超新星光变曲线模型的宇宙学参数解

Cosmological Parameter Uncertainties from SALT-II Type Ia Supernova Light Curve Models

J. Mosher, J. Guy, R. Kessler, P. Astier, J. Marriner, M. Betoule, M. Sako, P. El-Hage, R. Biswas, R. Pain, S. Kuhlmann, N. Regnault, J. A. Frieman, D. P. Schneider

摘要:

我们使用模拟的超新星Ia样本,包括光度和光谱,进行第一次直接验证的宇宙学分析使用的SALT-II光变曲线模型。该验证包括来自光变曲线训练过程的残差、SN Ia距离测量的系统偏差以及暗能量状态方程参数w的偏差。使用SN分析软件包SNANA,我们模拟和分析了与SNLS 3分析中使用的数据样本相对应的实际样本:120个低红移(z < 0.1)SNe Ia,255个SDSS SNe Ia(z < 0.4)和290个SNLS SNe Ia(z <= 1)。为了详细探测系统不确定性,我们改变输入光谱模型、固有散射模型和平滑(即,正则化)参数。使用真实的固有散射模型导致训练的SALT-II模型的紫外部分中的轻微偏差,并且w偏差(winput - wrecovered)范围从-0.005 +/- 0.012到-0.024 +/- 0.010。在不确定性范围内,这些偏倚无法相互区分; w的平均偏倚为-0.014 +/- 0.007。

英文摘要:

We use simulated SN Ia samples, including both photometry and spectra, to perform the first direct validation of cosmology analysis using the SALT-II light curve model. This validation includes residuals from the light curve training process, systematic biases in SN Ia distance measurements, and the bias on the dark energy equation of state parameter w. Using the SN-analysis package SNANA, we simulate and analyze realistic samples corresponding to the data samples used in the SNLS3 analysis: 120 low-redshift (z < 0.1) SNe Ia, 255 SDSS SNe Ia (z < 0.4), and 290 SNLS SNe Ia (z <= 1). To probe systematic uncertainties in detail, we vary the input spectral model, the model of intrinsic scatter, and the smoothing (i.e., regularization) parameters used during the SALT-II model training. Using realistic intrinsic scatter models results in a slight bias in the ultraviolet portion of the trained SALT-II model, and w biases (winput - wrecovered) ranging from -0.005 +/- 0.012 to -0.024 +/- 0.010. These biases are indistinguishable from each other within uncertainty; the average bias on w is -0.014 +/- 0.007.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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