[Paper Review] Simulations of the cosmic infrared and submillimeter background for future large surveys

N. Fernández-Conde, G. Lagache+2 more|arXiv (Cornell University)|Jun 8, 2010

Galaxies: Formation, Evolution, PhenomenaPhysics and Astronomy38 references6 citations

TL;DR

This paper presents a stacking technique to isolate high-redshift contributions to the cosmic infrared and submillimeter background (CIB) anisotropies by using 24 µm source positions to stack longer-wavelength maps. It achieves sub-noise detection (4–10× fainter than confusion noise) at 350–850 µm for z = 1–2 populations and enables effective removal of low-redshift (z < 2) anisotropies, producing clean CIB maps dominated by high-redshift galaxies for clustering and evolution studies.

ABSTRACT

Context. Herschel and Planck are surveying the sky at unprecedented angular scales and sensitivities over large areas. But both experiments are limited by source confusion in the submillimeter. The high confusion noise in particular restricts the study of the clustering properties of the sources that dominate the cosmic infrared background. At these wavelengths, it is more appropriate to consider the statistics of the unresolved component. In particular, high clustering will contribute in excess of Poisson noise in the power spectra of CIB anisotropies. Aims. These power spectra contain contributions from sources at all redshift. We show how the stacking technique can be used to separate the different redshift contributions to the power spectra. Methods. We use simulations of CIB representative of realistic Spitzer, Herschel, Planck, and SCUBA-2 observations. We stack the 24 μm sources in longer wavelengths maps to measure mean colors per redshift and flux bins. The information retrieved on the mean spectral energy distribution obtained with the stacking technique is then used to clean the maps, in particular to remove the contribution of low-redshift undetected sources to the anisotropies. Results. Using the stacking, we measure the mean flux of populations 4 to 6 times fainter than the total noise at 350 μm at redshifts z = 1 and z = 2, respectively, and as faint as 6 to 10 times fainter than the total noise at 850 μm at the same redshifts. In the deep Spitzer fields, the detected 24 μm sources up to z ~ 2 contribute significantly to the submillimeter anisotropies. We show that the method provides excellent (using COSMOS 24 μm data) to good (using SWIRE 24 μm data) removal of the z &lt; 2 (COSMOS) and z &lt; 1 (SWIRE) anisotropies. Conclusions. Using this cleaning method, we then hope to have a set of large maps dominated by high redshift galaxies for galaxy evolution study (e.g., clustering, luminosity density).

Motivation & Objective

• To separate low-redshift from high-redshift contributions to CIB anisotropies, which are otherwise obscured by confusion noise.
• To enable the study of high-redshift galaxy clustering and luminosity functions by cleaning submillimeter maps of low-z source contamination.
• To develop a method that allows statistical detection of faint, undetected sources at 350–850 µm using prior 24 µm detections and mean spectral energy distributions (SEDs).
• To produce large-scale, high-redshift-dominated CIB maps for future surveys using component separation and stacking.
• To validate the method’s effectiveness across different deep fields (COSMOS and SWIRE) and at multiple wavelengths (70–850 µm).

Proposed method

• Use 24 µm source positions from Spitzer surveys to stack fluxes in longer-wavelength maps (70–850 µm), leveraging known positions to co-add signals from undetected sources.
• Measure mean spectral energy distributions (SEDs) per redshift and flux bin using stacking, enabling accurate flux estimation for populations below the confusion limit.
• Apply the derived mean SEDs to clean submillimeter maps by subtracting the predicted contribution of low-redshift sources (z < 2 for COSMOS, z < 1 for SWIRE).
• Use power spectrum analysis to quantify the effectiveness of the cleaning, comparing total, low-redshift, and high-redshift anisotropy components.
• Simulate Herschel, Planck, and SCUBA-2 data to test the method across realistic survey conditions and noise levels.
• Apply the technique across multiple wavelengths (250–850 µm) to generate z ≳ 1–2 dominated CIB maps, with K-correction ensuring redshift-specific dominance.

Experimental results

Research questions

• RQ1 To what extent do low-redshift (z < 2) sources contribute to submillimeter anisotropies in deep surveys?
• RQ2 Can stacking of 24 µm-detected sources enable reliable flux estimation for populations undetected at 350–850 µm?
• RQ3 How effectively can the stacking-derived SEDs be used to remove low-redshift contamination from CIB power spectra?
• RQ4 What is the minimum detectable flux level for high-redshift populations using this method relative to confusion noise?
• RQ5 Can this method produce clean, high-redshift-dominated CIB maps suitable for clustering and evolution studies?

Key findings

• The stacking method measures mean fluxes of populations 4–6 times fainter than the confusion noise at 350 µm for sources at z = 1 and z = 2, respectively.
• At 850 µm, the method detects populations 6–10 times fainter than the confusion noise at the same redshifts.
• In the COSMOS field, the method achieves excellent removal of z < 2 anisotropies, while in SWIRE it achieves good removal of z < 1 anisotropies.
• The detected 24 µm sources up to z ∼ 2 contribute significantly to submillimeter anisotropies, validating the need for their removal.
• The cleaning method effectively reduces both Poissonian and correlated low-redshift anisotropies, especially at longer wavelengths where low-z contributions are smaller.
• The technique enables the creation of large-scale CIB maps dominated by high-redshift galaxies (z ≳ 1–2), suitable for power spectrum analysis and clustering studies.