Medium Bands, Mega Science: a JWST/NIRCam Medium-Band Imaging Survey of Abell 2744

TL;DR

MegaScience leverages JWST/NIRCam medium-band imaging over Abell 2744 to deliver 20-band coverage from $0.7-5\,\mu$m with $R\sim15$-level spectrophotometry, enabling precise photometric redshifts and spatially-resolved stellar populations. By combining with the UNCOVER dataset, it reduces $z_{\rm phot}$ scatter by ~3x and lowers catastrophic outliers by ~2x, while simultaneously mapping emission-line and continuum morphology across cosmic history, including clumpy [OIII] emission in $z>6$ galaxies. The survey provides a powerful, publicly available data set of fully reduced mosaics and catalogs, enabling integrated and resolved studies of galaxy growth from the local universe to the epoch of reionization and beyond, with lensing magnification enabling finer spatial detail (down to ~500 pc) in some sources. These results establish a benchmark for multi-band, spatially-resolved SED analyses with JWST and offer rich opportunities for cross-program calibration and future stellar-population inferences.

Abstract

In this paper, we describe the "Medium Bands, Mega Science" JWST Cycle 2 survey (JWST-GO-4111) and demonstrate the power of these data to reveal both the spatially-integrated and spatially-resolved properties of galaxies from the local universe to the era of cosmic dawn. Executed in November 2023, MegaScience obtained ~30 arcmin^2 of deep multiband NIRCam imaging centered on the z~0.3 Abell 2744 cluster, including eleven medium-band filters and the two shortest-wavelength broad-band filters, F070W and F090W. Together, MegaScience and the UNCOVER Cycle 1 treasury program provide a complete set of deep (~28-30 mag) images in all NIRCam medium- and broad-band filters. This unique dataset allows us to precisely constrain photometric redshifts, map stellar populations and dust attenuation for large samples of distant galaxies, and examine the connection between galaxy structures and formation histories. MegaScience also includes ~17 arcmin^2 of NIRISS parallel imaging in two broad-band and four medium-band filters from 0.9-4.8um, expanding the footprint where robust spectral energy distribution (SED) fitting is possible. We provide example SEDs and multi-band cutouts at a variety of redshifts, and use a catalog of JWST spectroscopic redshifts to show that MegaScience improves both the scatter and catastrophic outlier rate of photometric redshifts by factors of 2-3. Additionally, we demonstrate the spatially-resolved science enabled by MegaScience by presenting maps of the [OIII] line emission and continuum emission in three spectroscopically-confirmed z>6 galaxies. We show that line emission in reionization-era galaxies can be clumpy, extended, and spatially offset from continuum emission, implying that galaxy assembly histories are complex even at these early epochs. We publicly release fully reduced mosaics and photometric catalogs for both the NIRCam primary and NIRISS parallel fields.

Figures (10)

• Figure 1: Schematic of the on-sky footprint of MegaScience and UNCOVER (left), other NIRCam and NIRISS imaging programs (center), and NIRCam grism programs (right); these programs are described in additional detail in the main text. The MegaScience footprint is shown in light blue in all three panels. A comparison with footprints of pre-JWST data, including HST and MUSE, is shown in bezanson22. For the UNCOVER parallel observations in the southeast of the image, we only show pointings which are included in the reduced mosaics released along with this paper (declination $<30^\circ28$).
• Figure 2: Existing photometric coverage in both the NIRCam primary and NIRISS parallel fields, along with new imaging from this program. MegaScience "completes" the imaging in the primary field, with deep images in all 20 of NIRCam's broad- and medium-band filters. The addition of two broad-band and four medium-band filters in the NIRISS parallel field will allow for robust SED modeling.
• Figure 3: PSF growth curves for each filter added to UNCOVER before (top) and after (bottom) matching to F444W. After matching, all filters have deviations below the 1% level at the smallest aperture diameter used (0.32$^{\prime\prime}$). Growth curves are shown relative to the F444W growth curve; a value of 1 indicates perfect matching with F444W. Dashed lines indicate the $\pm1$% deviations from exact matching (solid black line). Dotted lines indicate the location of 0.32$^{\prime\prime}$ and 0.70$^{\prime\prime}$ aperture diameters.
• Figure 4: Example SEDs from UNCOVER (left) vs MegaScience (center), as well as eazy-py photometric redshift distributions (right). SEDs are shown in $f_\nu$ (in units of $10^{30}\rm{erg\ s}^{-1}\rm{cm}^{-2}\rm{Hz}^{-1}$). Each object is spectroscopically confirmed by UNCOVER (top four objects; Price et al. in prep.) or ALT (bottom two objects; Naidu & Matthee et al. in prep). Objects are ordered by increasing redshift; each is chosen to demonstrate one "failure mode" of SED-fitting that is solved by the increased photometric coverage of MegaScience. Each example is discussed in additional detail in Section \ref{['sec:integrated-science']}.
• Figure 5: Comparison of photometric redshifts with a sample of $\sim300$ high-quality spectroscopic redshifts from the UNCOVER survey (S. Price et al., in prep). The top row shows our Prospector redshifts wang24, and the bottom row shows eazy-py redshifts based on photometry from the 'SUPER' catalog weaver24. The left column shows redshifts from the public DR2 UNCOVER data release, while the right column shows MegaScience redshifts from the DR3 public data products accompanying this paper. MegaScience shows nearly a factor of three reduction in $\sigma_{\rm{NMAD}}$, and close to a factor of two reduction in catastrophic outliers (as in weaver24, defined as objects with $\Delta z / (1+z_{\rm{spec}})\ge 0.15$; shown by dotted red lines). Prospector and eazy-py show similar performance.