Simulating Spectral Confusion in SPHEREx Photometry and Redshifts

Abstract We model the impact of source confusion on photometry and the resulting spectrophotometric redshifts 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 μ Jy across 0.75–5.0 μ m. 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.

Authors

Institutions

Publication Details

Journal
The Astrophysical Journal
Published
2026-03-12
DOI
https://doi.org/10.3847/1538-4357/ae472b
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simulating Spectral Confusion in SPHEREx Photometry and Redshifts

Seán Bruton, Richard M. Feder, B. P. Crill, James R. Cheshire et al.
The Astrophysical Journal
Galaxies: Formation, Evolution, Phenomena
article

Simulating Spectral Confusion in SPHEREx Photometry and Redshifts

Seán Bruton, Richard M. Feder, B. P. Crill, James R. Cheshire, Jean Choppin de Janvry, James J. Bock, Woong-Seob Jeong, Bomee Lee, Daniel C. Masters, Spencer W. Everett, Yongjung Kim, Olivier Doré, Zhaoyu Huai, Andreas L. Faisst, Yun-Ting 昀庭 Cheng 鄭
article en

Abstract

Abstract We model the impact of source confusion on photometry and the resulting spectrophotometric redshifts 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 μ Jy across 0.75–5.0 μ m. 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.

The Astrophysical JournalVol. 1000(1)
California Institute of Technology (US), Jet Propulsion Laboratory (US), Lawrence Berkeley National Laboratory (US), Korea Astronomy and Space Science Institute (KR), Sejong University (KR), Infrared Processing and Analysis Center (US), University of California, Berkeley (US)
Affordable and clean energy
Openalex Percentile: Top 28%
Galaxies: Formation, Evolution, Phenomena
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.