arXiv subjects

Kurt Hamblin

Publications and source records attributed to Kurt Hamblin.

5 recordsLinked to original sources

arXiv2026

MEGA and SMILES Find Fewer Dusty Galaxies than Expected at Cosmic Noon

We present infrared (IR) luminsosity functions (LFs) and resulting star formation rate densities using the JWST Mid-infrared Instrument (MIRI) observations from the MIRI EGS Galaxy and AGN (MEGA) survey and Systematic MIRI Legacy Extragalactic Survey (SMILES). JWST allows us to perform a robust analysis on the faint end of the IR LF beyond the local universe. We directly measure the 7.7$\mu$m polycyclic aromatic hydrocarbon (PAH) feature using either F1000W, F1500W, or F2100W photometry. This results in a sample of 634 galaxies across the two surveys covering an area of 105 arcmin$^2$ ($\sim$70 in the EGS and $\sim35$ in the GOODS-S/HUDF fields) and spanning $0.2<z<2$. We convert the 7.7$\mu$m PAH luminosity to total IR luminosity, resulting in LFs that are two orders of magnitude fainter than previous studies. In contrast to previous extrapolations based on shallower observations, we find a strong flattening in the faint end of the LF with an average slope of $\alpha\sim0.147$. This indicates that less luminous galaxies do not have as much dust obscured star formation as predicted. We measure the star formation rate density (SFRD) by integrating our new IR LFs and find a slightly lower SFRD in all redshift bins than previous studies made with ALMA, Herschel, and Spitzer. We also measure the contribution to the SFRD as a function of luminosity and confirm that LIRGs and ULIRGs remain the dominant contributors to the dust-obscured star formation at $z\sim1-2$.

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arXiv2025

MEGA: Spectrophotometric SED Fitting of Little Red Dots Detected in JWST MIRI

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, $-0.5 < \mathrm{F444W - F770W} < 0.5$, suggesting weak warm/hot dust components. The LRDs have $-1.0 < {F1000W - F1500W} < 1.1$, suggestive of non-uniform rest near-IR properties within the sample. We model the spectral energy distributions (SEDs) of the LRDs using the CIGALE and Prospector codes to assess how the differing templates impact the interpretation for LRDs for cases of: (1) models with star-forming stellar populations only; (2) active galactic nuclei (AGN) dominated models; and (3) composite AGN and star-forming models. Using the Bayesian information criterion, we find that six of the eight LRDs favor AGN models compared to star-forming models, though no model reproduces all of the observed properties. Two LRDs with pronounced Balmer-breaks and broad H$\alpha$ have SEDs that are reproduced with hot, dense-gas ($\log T/\mathrm{K}=5-5.7$, $\log n/\mathrm{cm^{-3}} = 9-11$) models with low dust attenuation ($A(V)\simeq 0.5$ 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 [OIII] emission. The total bolometric emission from the dense-gas models, and possibly CIGALE AGN models, appear consistent with literature constraints in the far-IR and radio, and require $\log L_{bol}/L_\odot<12$. 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.

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arXiv2025

AGNBoost: A Machine Learning Approach to AGN Identification with JWST/NIRCam+MIRI Colors and Photometry

We present AGNBoost, a machine learning framework utilizing XGBoostLSS to identify AGN and estimate redshifts from JWST NIRCam and MIRI photometry. AGNBoost constructs 66 input features from 7 NIRCam and 4 MIRI bands to predict the fraction of mid-IR $3$--$30\,\mu$m emission attributable to an AGN power law ($\text{frac}_{\text{AGN}}$) and photometric redshift. Each model is trained on $10^6$ simulated galaxies from 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 $1.63\%$ ($\text{frac}_{\text{AGN}}$) and $0.15\%$ (redshift), with $\sigma_{\text{RMSE}} = 0.045$ for $\text{frac}_{\text{AGN}}$ and $\sigma_{\text{NMAD}} = 0.004$ for redshift. When realistic photometric uncertainties are introduced, performance remains robust with median predictions 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 $\text{frac}_{\text{AGN}} > 0.3$ and $100\%$ with $\text{frac}_{\text{AGN}} > 0.5$, demonstrating generalization beyond the training distribution. On MEGA galaxies with spectroscopic redshifts, AGNBoost achieves $\sigma_{\text{NMAD}} = 0.056$ and $19.79\%$ outliers. AGNBoost $\text{frac}_{\text{AGN}}$ estimates broadly agree with CIGALE fitting ($\sigma_{\text{RMSE}} = 0.178$, $11.96\%$ outliers). The flexible framework allows straightforward incorporation of additional photometric bands and re-training for other variables. AGNBoost's computational efficiency makes it well-suited for wide-sky surveys requiring rapid AGN identification and redshift estimation.

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arXiv2025

MEGA Mass Assembly with JWST: The MIRI EGS Galaxy and AGN Survey

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.

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arXiv2020

The Accretion History of AGN: A Newly Defined Population of Cold Quasars

Quasars are the most luminous of active galactic nuclei (AGN), and are perhaps responsible for quenching star formation in their hosts. The Stripe 82X catalog covers 31.3 deg$^2$ of the Stripe 82 field, of which the 15.6 deg$^2$ covered with XMM-Newton is also covered by Herschel/SPIRE. We have 2500 X-ray detected sources with multi-wavelength counterparts, and 30% of these are unobscured quasars, with $L_X > 10^{44}\,$erg/s and $M_B < -23$. We define a new population of quasars which are unobscured, have X-ray luminosities in excess of $10^{44}\,$erg/s, have broad emission lines, and yet are also bright in the far-infrared, with a 250$μ$m flux density of $S_{\rm 250}>30$mJy. We refer to these Herschel-detected, unobscured quasars as "Cold Quasars". A mere 4% (21) of the X-ray- and optically-selected unobscured quasars in Stripe 82X are detected at 250$μ$m. These Cold Quasars lie at $z\sim1-3$, have $L_{\rm IR}>10^{12}\,L_\odot$, and have star formation rates of $\sim200-1400\,M_\odot$/yr. Cold Quasars are bluer in the mid-IR than the full quasar population, and 72% of our Cold Quasars have WISE W3 $<$ 11.5 [Vega], while only 19% of the full quasar sample meets this criteria. Crucially, Cold Quasars have on average $\sim9\times$ as much star formation as the main sequence of star forming galaxies at similar redshifts. Although dust-rich, unobscured quasars have occasionally been noted in the literature before, we argue that they should be considered as a separate class of quasars due to their high star formation rates. This phase is likely short-lived, as the central engine and immense star formation consume the gas reservoir. Cold Quasars are type-1 blue quasars that reside in starburst galaxies.

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