Euclid Quick Data Release (Q1). The average far-infrared properties of Euclid-selected star-forming galaxies

TL;DR

We address the average far-infrared properties of Euclid-selected star-forming main-sequence galaxies by stacking on Herschel SPIRE, PACS, and SCUBA-2 maps using the SimStack framework to account for clustering. The authors derive mean dust temperatures, dust masses, and SFRs across bins in redshift and stellar mass by fitting a modified blackbody SED with fixed $eta=1.96$ and a mid-IR power law, finding that $T_d(t)=T_2+(T_1-T_2) e^{-t/ au}$ with $T_1\approx79.7$ K, $T_2\approx23.2$ K, and $ au\approx1.6$ Gyr, and that $M_d/M_*$ grows to $z\sim1$ then plateaus while $T_d$ is largely independent of $M_*$. The analysis shows substantial CIB resolution from Euclid MS galaxies—$>60 ext{--}80 ext{%}$ in SPIRE bands—highlighting the role of older stellar heating at late times and providing SFRD estimates consistent with the MS framework at $z<1.5$. Comparisons with the MAMBO simulation reveal similar SFRs and Md but a differing Td evolution, likely due to model temperature assignments. These results demonstrate the power of combining Euclid with far-IR data to study dust evolution and the CIB, with future Euclid releases poised to push to higher redshift and lower stellar mass.

Abstract

The first Euclid Quick Data Release contains millions of galaxies with excellent optical and near-infrared (IR) coverage. To complement this dataset, we investigate the average far-IR properties of Euclid-selected main sequence (MS) galaxies using existing Herschel and SCUBA-2 data. We use 17.6deg$^2$ (2.4deg$^2$) of overlapping Herschel (SCUBA-2) data, containing 2.6 million (240000) MS galaxies. We bin the Euclid catalogue by stellar mass and photometric redshift and perform a stacking analysis following SimStack, which takes into account galaxy clustering and bin-to-bin correlations. We detect stacked far-IR flux densities across a significant fraction of the bins. We fit modified blackbody spectral energy distributions in each bin and derive mean dust temperatures, dust masses, and star-formation rates (SFRs). We find similar mean SFRs compared to the Euclid catalogue, and we show that the average dust-to-stellar mass ratios decreased from z$\simeq$1 to the present day. Average dust temperatures are largely independent of stellar mass and are well-described by the function $T_2+(T_1-T_2){\rm e}^{-t/τ}$, where $t$ is the age of the Universe, $T_1=79.7\pm7.4$K, $T_2=23.2\pm0.1$K, and $τ=1.6\pm0.1$Gyr. We argue that since the dust temperatures are converging to a non-zero value below $z=1$, the dust is now primarily heated by the existing cooler and older stellar population, as opposed to hot young stars in star-forming regions at higher redshift. We show that since the dust temperatures are independent of stellar mass, the correlation between dust temperature and SFR depends on stellar mass. Lastly, we estimate the contribution of the Euclid catalogue to the cosmic IR background (CIB), finding that it accounts for >60% of the CIB at 250, 350, and 500$μ$m. Forthcoming Euclid data will extend these results to higher redshifts, lower stellar masses, and recover more of the CIB.

Figures (15)

• Figure 1: Top:-SPIRE data covering the CDFS-SWIRE field (which overlaps with the EDF-F) at 250, 350, and 500 $\mu$m. The blue contour shows the mask applied to the SPIRE images in order to remove bad edge pixels. The grey contours show the corresponding catalogue mask, where masked rectangles are the locations of bright stars in the field that contaminate source extraction. Bottom: Same as the top panel, but showing the RMS of the -SPIRE data. Coordinates are conventional RA and Dec.
• Figure 2: Same as \ref{['fig:field_summary_edff']}, but for the -SPIRE AKARI-NEP field (which overlaps with the EDF-N).
• Figure 3: Modified blackbody SEDs (with $\beta=1.96$ and $\alpha=2.3$) fit to the stacked and SCUBA-2 flux densities. The redshifts and stellar masses of each bin are indicated by the top and right axis labels, respectively. The best-fit parameters are given in Table \ref{['table:bestfit_sed']}. SEDs have only been fit to bins where all three SPIRE flux densities are detected with S/N$\,{>}\,3$, and at least one PACS flux density is detected with S/N$\,{>}\,3$; panels are blank otherwise. Bins that are ${>}\,95\%$ complete in stellar mass are highlighted in blue.
• Figure 4: Ratio of our SFRs measured from far-IR photometry to a parameterisation of the star-forming MS, shown as a function of redshift and split into different stellar mass stacking bins. Only redshift and stellar mass bins with ${>}\,95\%$ completeness are shown. We use the MS parameterisation from popesso2023, which a continuous function of $z$/$t$ and is in good agreement with Q1-SP031.
• Figure 5: Best-fit dust temperatures from our SED fitting, $T_{\rm d}$, as a function of time (bottom axis) and redshift (top axis), considering only the redshift and stellar mass bins that are ${>}\,95\%$ complete. We show the dust temperature evolution for five different stellar mass bins, with the stellar mass values of the centres of the bins given in the legend. The solid curve is a fit to the simple form $T_2\,{+}\,(T_1\,{-}\,T_2)\,e^{-t/\tau}$, while the dotted line is the quadratic-in-redshift fit from koprowski2024 and the dashed line is the linear-in-redshift fit from schreiber2017. We also show published mean temperature estimates for star-forming galaxies at low redshift lamperti2019 in blue.