five

Simulating Spectral Confusion in SPHEREx Photometry and Redshifts

收藏
DataCite Commons2026-02-23 更新2026-05-03 收录
下载链接:
http://dataverse.jpl.nasa.gov/citation?persistentId=doi:10.48577/jpl.4ACPQV
下载链接
链接失效反馈
官方服务:
资源简介:
We model the impact of source confusion on photometry and the resulting spectrophotometric red14 shifts for SPHEREx, a NASA Medium-Class Explorer that is carrying out an all-sky near-infrared spectral survey. Spectral confusion from untargeted background galaxies degrades sensitivity and introduces a spectral bias. Using interpolated spectral energy distributions (SEDs) from the COSMOS2020 catalog, we construct a Monte Carlo library of confusion spectra that captures the cumulative impact from faint galaxies. By injecting confusion realizations into galaxy SEDs and performing forced photometry at known source positions, we quantify photometric and redshift error and bias. For our current expected selection of sources for the cosmology analysis, we find typical 1-σ confusion levels range from 0.8 − 3.8 µJy across 0.75 − 5.0 µm. While negligible at full-sky survey depth, spectral confusion becomes significant in the SPHEREx deep fields, reducing the number of intermediate-precision redshifts and inducing a small systematic overestimation in redshift. In parallel, we also model targeted source blending from beam overlaps, which contributes additional photometric noise without systematic redshift bias, provided that positions are known exactly. Together, confusion and blending vary with the depth of the selected reference sample, revealing a trade-off, where deeper selections reduce confusion but increase blending-induced noise. Our methodology informs optimization of the SPHEREx source selection strategy and future treatments of stellar source blending and confusion.
提供机构:
Root
创建时间:
2026-02-22
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作