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arXiv 2405.04522astro-ph.CO
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超新星的天体测量红移

Astrometric Redshifts of Supernovae

Jaemyoung Jason Lee, Masao Sako, Richard Kessler, Alex I. Malz, The LSST Dark Energy Science Collaboration

AI总结:

本文提出利用差分色折射从多波段时序成像数据推断超新星红移,并在 LSST DDF 模拟中验证其在 z<0.6 范围内准确,且与测光红移结合可显著改善估计。

摘要:

差分色折射(DCR)是由地球大气折射率的波长依赖性引起的,它会根据天体光谱能量分布(SED)的不同,移动恒星和星系的视位置并扭曲其形状。虽然在成像观测中通常会减轻和校正这种效应,但我们研究如何反过来利用 DCR,从多波段、时间序列成像数据中推断超新星的红移。我们在拟议的 Vera C. Rubin 天文台时空遗产巡天(LSST)深钻场(DDF)中模拟 Ia 型超新星(SNe Ia),并评估天体测量红移。我们发现,红移精度随着天体测量统计质量和天体测量解算精度的提高而显著提升。在保守选择 5 毫角秒系统不确定性下限的情况下,我们发现红移估计在 $z < 0.6$ 范围内是准确的。随后,我们将天体测量红移与宿主星系测光红移以及超新星测光(光变曲线)红移相结合,结果表明这显著改善了整体红移估计。这些天体测量红移将特别有价值,因为 Rubin 将发现大量无法获得光谱红移的超新星。

英文摘要:

Differential Chromatic Refraction (DCR) is caused by the wavelength dependence of our atmosphere's refractive index, which shifts the apparent positions of stars and galaxies and distorts their shapes depending on their spectral energy distributions (SEDs). While this effect is typically mitigated and corrected for in imaging observations, we investigate how DCR can instead be used to our advantage to infer the redshifts of supernovae from multi-band, time-series imaging data. We simulate Type Ia supernovae (SNe Ia) in the proposed Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) Deep Drilling Field (DDF), and evaluate astrometric redshifts. We find that the redshift accuracy improves dramatically with the statistical quality of the astrometric measurements as well as with the accuracy of the astrometric solution. For a conservative choice of a 5-mas systematic uncertainty floor, we find that our redshift estimation is accurate at $z < 0.6$. We then combine our astrometric redshifts with both host galaxy photometric redshifts and supernovae photometric (light-curve) redshifts and show that this considerably improves the overall redshift estimates. These astrometric redshifts will be valuable especially since Rubin will discover a vast number of supernovae for which we will not be able to obtain spectroscopic redshifts.

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