Kurt Hamblin

We analyze eight spectroscopically confirmed little red dots (LRDs) at redshifts z = 5.1–8.7 with JWST/NIRCam, NIRSpec, and MIRI data. The LRDs have red NIRCam colors, F150W − F444W > 1, but flat NIRCam − MIRI colors, −0.5 < F444W − F770W < 0.5, suggesting weak warm/hot dust components. The LRDs have −1.0 < F1000W − F1500W < 1.1, suggestive of nonuniform rest near-IR properties within the sample. We model the spectral energy distributions (SEDs) of the LRDs using the CIGALE and P rospector codes to assess how the differing templates impact the interpretation for LRDs for cases of: (1) models with star-forming (SF) stellar populations only; (2) active galactic nuclei (AGN)-dominated models; and (3) composite AGN and SF models. Using the Bayesian information criterion, we find that six of the eight LRDs favor AGN models compared to SF models, though no model reproduces all of the observed properties. Two LRDs with pronounced Balmer breaks and broad H α have SEDs that are reproduced with hot, dense-gas ( log T / K = 5 – 5.7 , log n / cm − 3 = 9 – 11 ) models with low dust attenuation ( A ( V ) ≃ 0.5 mag). However, these models require an additional thermal component (800–1400 K) to account for the MIRI data, and fail to reproduce the rest-UV and narrow [O iii ] emission. The total bolometric emission from the dense-gas models, and possibly CIGALE AGN models, appears consistent with literature constraints in the far-IR and radio, and requires log L bol / L ⊙ < 12 . These results suggest that our LRDs cannot be modeled entirely with standard templates, but instead require a novel treatment of gas conditions, AGN, and star formation.

We present AGNBoost , a machine learning framework utilizing XGBoostLSS to identify active galactic nuclei (AGNs) and estimate redshifts from James Webb Space Telescope (JWST) Near Infrared Camera (NIRCam) and Mid-Infrared Instrument (MIRI) photometry. AGNBoost constructs 66 input features from seven NIRCam and four MIRI bands to predict the fraction of mid-IR 3–30 μ m emission attributable to an AGN power law (frac _AGN ) and photometric redshift. Each model is trained on 10 ⁶ simulated galaxies from the Code Investigating GALaxy Emission ( CIGALE ). Models are tested on mock CIGALE galaxies, an independent set of empirically derived templates, and 748 observations from the JWST MIRI EGS Galaxy and AGN (MEGA) survey. On idealized noise-free mock CIGALE galaxies, AGNBoost achieves 15% outlier fractions of 1.63% (frac _AGN ) and 0.15% (redshift), with σ _RMSE = 0.045 for frac _AGN and σ _NMAD = 0.004 for redshift. When realistic photometric uncertainties are introduced, performance remains robust with median predictions lying on the 1:1 relation, though outlier fractions increase to 4.38% and 3.35%, respectively. On the independent template set, AGNBoost identifies 92.6% of AGN candidates with frac _AGN > 0.3 and 100% with frac _AGN > 0.5, demonstrating generalization beyond the training distribution. For MEGA galaxies with spectroscopic redshifts, AGNBoost achieves σ _NMAD = 0.056 and 19.79% outliers. AGNBoost frac _AGN estimates broadly agree with CIGALE fitting ( σ _RMSE = 0.178, 11.96% outliers). The flexible framework allows straightforward incorporation of additional photometric bands and retraining for other variables. AGNBoost ’s computational efficiency makes it well suited for wide-sky surveys requiring rapid AGN identification and redshift estimation.

We present the Mid-Infrared Instrument (MIRI) Extended Groth Strip (EGS) Galaxy and Active Galactic Nucleus (MEGA) survey, a four-band MIRI survey with 25 pointings in the EGS extragalactic field. Three pointings utilized only the three reddest bands (F1000W, F1500W, and F2100W), while the remainder also included a blue filter (F770W). MEGA builds upon the existing observations in the EGS field by providing MIRI imaging for 68.9% of CEERS NIRCam imaging, filling a crucial gap in order to understand galaxy evolution by observing the obscured Universe. Here, we present the technical design, data reduction, photometric catalog creation for our first data release, and science drivers of the MEGA survey. Our data reduction starts with the standard James Webb Space Telescope calibration pipeline but adds additional warm pixel masking and custom background subtraction steps to improve the quality of the final science image. We estimate the image depth of the reduced mosaics and present new galaxy number counts in four MIRI bands.

We present the MIRI EGS Galaxy and AGN (MEGA) survey, a four band MIRI survey with 25 pointing in the Extended Groth Strip (EGS) extragalactic field. Three of the pointings utilized only the three reddest bands (F1000W, F1500W, F2100W) while the remainder of the pointings also add a blue filter (F770W). MEGA builds upon the existing observations in the EGS field by providing MIRI imaging for 68.9% of CEERS NIRCam imaging, filling a cruciality gap in order to understand galaxy evolution by observing the obscured Universe. Here, we present the technical design, data reduction, photometric catalog creation, the first data release, and science drivers of the MEGA survey. Our data reduction starts with the standard JWST calibration pipeline, but adds additional warm pixel masking and custom background subtraction steps to improve the quality of the final science image. We estimate the image depth of the reduced mosaics and present new galaxy number counts in four MIRI bands.

We report the discovery of a candidate galaxy with a photo-z of z ∼ 12 in the first epoch of the James Webb Space Telescope (JWST) Cosmic Evolution Early Release Science Survey. Following conservative selection criteria, we identify a source with a robust z _phot = 11.8 − 0.2 + 0.3 (1σ uncertainty) with m _F200W = 27.3 and ≳7σ detections in five filters. The source is not detected at λ < 1.4 μm in deep imaging from both Hubble Space Telescope (HST) and JWST and has faint ∼3σ detections in JWST F150W and HST F160W, which signal a Lyα break near the red edge of both filters, implying z ∼ 12. This object (Maisie’s Galaxy) exhibits F115W − F200W > 1.9 mag (2σ lower limit) with a blue continuum slope, resulting in 99.6% of the photo-z probability distribution function favoring z > 11. All data-quality images show no artifacts at the candidate’s position, and independent analyses consistently find a strong preference for z > 11. Its colors are inconsistent with Galactic stars, and it is resolved (r _h = 340 ± 14 pc). Maisie’s Galaxy has log M _*/M _⊙ ∼ 8.5 and is highly star-forming (log sSFR ∼ −8.2 yr⁻¹), with a blue rest-UV color (β ∼ −2.5) indicating little dust, though not extremely low metallicity. While the presence of this source is in tension with most predictions, it agrees with empirical extrapolations assuming UV luminosity functions that smoothly decline with increasing redshift. Should follow-up spectroscopy validate this redshift, our universe was already aglow with galaxies less than 400 Myr after the Big Bang.