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1. MAGAZ3NE: Massive, Extremely Dusty Galaxies at z ∼ 2 Lead to Photometric Overestimation of Number Densities of the Most Massive Galaxies at 3 < z < 4*

   https://doi.org/10.3847/1538-4357/ad8b1c  

   Forrest, Ben; Cooper, M C; Muzzin, Adam; Wilson, Gillian; Marchesini, Danilo; McConachie, Ian; Gomez, Percy; Annunziatella, Marianna; Marsan, Z Cemile; Braspenning, Joey; et al (December 2024, The Astrophysical Journal)

   Abstract We present rest-frame optical spectra from Keck/MOSFIRE and Keck/NIRES of 16 candidate ultramassive galaxies targeted as part of the Massive Ancient Galaxies atz> 3 Near-Infrared Survey (MAGAZ3NE). These candidates were selected to have photometric redshifts 3 ≲z_phot<4, photometric stellar masses $\log \left(M_{\ast }/M_{\odot }\right)$ > 11.7, and well-sampled photometric spectral energy distributions (SEDs) from the UltraVISTA and VIDEO surveys. In contrast to previous spectroscopic observations of blue star-forming and poststarburst ultramassive galaxies, candidates in this sample have very red SEDs implying significant dust attenuation, old stellar ages, and/or active galactic nuclei (AGN). Of these galaxies, eight are revealed to be heavily dust-obscured 2.0 <z< 2.7 galaxies with strong emission lines, some showing broad features indicative of AGN, three are Type I AGN hosts atz> 3, one is az∼ 1.2 dusty galaxy, and four galaxies do not have a confirmed spectroscopic redshift. In fact, none of the sample has ∣z_spec−z_phot∣ < 0.5, suggesting difficulties for photometric redshift programs in fitting similarly red SEDs. The prevalence of these red interloper galaxies suggests that the number densities of high-mass galaxies are overestimated atz≳ 3 in large photometric surveys, helping to resolve the “impossibly early galaxy problem” and leading to much better agreement with cosmological galaxy simulations. A more complete spectroscopic survey of ultramassive galaxies is required to pin down the uncertainties on their number densities in the early Universe. 

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2. The Merian survey: design, construction, and characterization of a filter set optimized to find dwarf galaxies and measure their dark matter halo properties with weak lensing

   https://doi.org/10.1093/mnras/stae925  

   Luo, Yifei; Leauthaud, Alexie; Greene, Jenny; Huang, Song; Kado-Fong, Erin; Danieli, Shany; Li, Ting S; Li, Jiaxuan; Blanco, Diana; Wasleske, Erik J; et al (May 2024, Monthly Notices of the Royal Astronomical Society)

   ABSTRACT The Merian survey is mapping ∼ 850 deg2 of the Hyper Suprime-Cam Strategic Survey Program (HSC-SSP) wide layer with two medium-band filters on the 4-m Victor M. Blanco telescope at the Cerro Tololo Inter-American Observatory, with the goal of carrying the first high signal-to-noise (S/N) measurements of weak gravitational lensing around dwarf galaxies. This paper presents the design of the Merian filter set: N708 (λc = 7080 Å, Δλ = 275 Å) and N540 (λc = 5400 Å, Δλ = 210 Å). The central wavelengths and filter widths of N708 and N540 were designed to detect the $$\rm H\alpha$$ and $$\rm [OIII]$$ emission lines of galaxies in the mass range $$8\lt \rm \log M_*/M_\odot \lt 9$$ by comparing Merian fluxes with HSC broad-band fluxes. Our filter design takes into account the weak lensing S/N and photometric redshift performance. Our simulations predict that Merian will yield a sample of ∼ 85 000 star-forming dwarf galaxies with a photometric redshift accuracy of σΔz/(1 + z) ∼ 0.01 and an outlier fraction of $$\eta =2.8~{{\ \rm per\ cent}}$$ over the redshift range 0.058 < z < 0.10. With 60 full nights on the Blanco/Dark Energy Camera (DECam), the Merian survey is predicted to measure the average weak lensing profile around dwarf galaxies with lensing S/N ∼32 within r < 0.5 Mpc and lensing S/N ∼90 within r < 1.0 Mpc. This unprecedented sample of star-forming dwarf galaxies will allow for studies of the interplay between dark matter and stellar feedback and their roles in the evolution of dwarf galaxies. 

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3. The Merian Survey: Design, Construction, and Characterization of a Filter Set Optimized to Find Dwarf Galaxies and Measure their Dark Matter Halo Properties with Weak Lensing

   Yifei Luo; Alexie Leauthaud; Jenny Greene; Song Huang; Erin Kado-Fong; Shany Danieli; Ting S. Li; Jiaxuan Li; Diana Blanco; Erik J. Wasleske; et al (May 2023, arXivorg)

   The Merian survey is mapping 850 degrees2 of the Hyper Suprime-Cam Strategic Survey Program (HSC-SSP) wide layer with two medium-band filters on the 4-meter Victor M. Blanco telescope at Cerro Tololo Inter-American Observatory, with the goal of carrying the first high signal-to-noise (S/N) measurements of weak gravitational lensing around dwarf galaxies. This paper presents the design of the Merian filter set: N708 and N540. The central wavelengths and filter widths of N708 and N540 were designed to detect the Ha and [OIII] emission lines of galaxies in the mass range 8 to 9 by comparing Merian fluxes with HSC broad-band fluxes. Our filter design takes into account the weak lensing S/N and photometric redshift performance. Our simulations predict that Merian will yield a sample of 85,000 star-forming dwarf galaxies with a photometric redshift accuracy of $Delta z/(1+z)= 0.01 and an outlier fraction of eta=2.8% over the redshift range 0.058 

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4. Simulating JWST deep extragalactic imaging surveys and physical parameter recovery

   https://doi.org/10.1051/0004-6361/202037450  

   Kauffmann, O. B.; Le Fèvre, O.; Ilbert, O.; Chevallard, J.; Williams, C. C.; Curtis-Lake, E.; Colina, L.; Pérez-González, P. G.; Pye, J. P.; Caputi, K. I. (August 2020, Astronomy & Astrophysics)

   null (Ed.)

   We present a new prospective analysis of deep multi-band imaging with the James Webb Space Telescope (JWST). In this work, we investigate the recovery of high-redshift 5 <   z  <  12 galaxies through extensive image simulations of accepted JWST programs, including the Early Release Science in the EGS field and the Guaranteed Time Observations in the HUDF. We introduced complete samples of ∼300 000 galaxies with stellar masses of log( M * / M ⊙ ) > 6 and redshifts of 0 <   z  <  15, as well as galactic stars, into realistic mock NIRCam, MIRI, and HST images to properly describe the impact of source blending. We extracted the photometry of the detected sources, as in real images, and estimated the physical properties of galaxies through spectral energy distribution fitting. We find that the photometric redshifts are primarily limited by the availability of blue-band and near-infrared medium-band imaging. The stellar masses and star formation rates are recovered within 0.25 and 0.3 dex, respectively, for galaxies with accurate photometric redshifts. Brown dwarfs contaminating the z  >  5 galaxy samples can be reduced to < 0.01 arcmin −2 with a limited impact on galaxy completeness. We investigate multiple high-redshift galaxy selection techniques and find that the best compromise between completeness and purity at 5 <   z  <  10 using the full redshift posterior probability distributions. In the EGS field, the galaxy completeness remains higher than 50% at magnitudes m UV  <  27.5 and at all redshifts, and the purity is maintained above 80 and 60% at z  ≤ 7 and 10, respectively. The faint-end slope of the galaxy UV luminosity function is recovered with a precision of 0.1–0.25, and the cosmic star formation rate density within 0.1 dex. We argue in favor of additional observing programs covering larger areas to better constrain the bright end. 

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5. Photometric Redshifts in JWST Deep Fields: A Pixel-Based Alternative with DeepDISC

   https://doi.org/10.33232/001c.156099  

   Merz, Grant; Zhuang, Ming-Yang; Li, Junyao; Yang, Qian; Shen, Yue; Liu, Xin; Crenshaw, John Franklin (January 2026, The Open Journal of Astrophysics)

   Photo-z algorithms that utilize SED template fitting have matured, and are widely adopted for use on high-redshift near-infrared data that provides a unique window into the early universe. Alternative photo-z methods have been developed, largely within the context of low-redshift optical surveys. Machine learning based approaches have gained footing in this regime, including those that utilize raw pixel information instead of aperture photometry. However, the efficacy of image-based algorithms on high-redshift, near-infrared data remains underexplored. Here, we test the performance of Detection, Instance Segmentation and Classification with Deep Learning (DeepDISC) on photometric redshift estimation with NIRCam images from the JWST Advanced Deep Extragalactic Survey (JADES) program. DeepDISC is designed to produce probabilistic photometric redshift estimates directly from images, after detecting and deblending sources in a scene. Using NIRCam-only images and a compiled catalog of spectroscopic redshifts, we show that DeepDISC produces reliable photo-zs and uncertainties comparable to those estimated from template fitting using HST+JWST filters; DeepDISC even outperforms template fitting (lower scatter/fewer outliers) when the input photometric filters are matched. Compared with template fitting, DeepDISC does not require measured photometry from images, and can produce a catalog of 94000 photo-zs in ~4 minutes on a single NVIDIA A40 GPU. While current spectroscopic training samples are small and incomplete in color-magnitude space, this work demonstrates the potential of DeepDISC for increasingly larger image volumes and spectroscopic samples from ongoing and future programs. We discuss the impact of the training data on applications to broader samples and produce a catalog of photo-zs for all JADES DR2 photometric sources in the GOOD-S field, with quality flags indicating caveats. 

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