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Stéphanie Juneau

Publications and source records attributed to Stéphanie Juneau.

At least 19 recordsLinked to original sources

Near-infrared emission line diagnostics for AGN from the local Universe to redshift 3

Optical rest-frame spectroscopic diagnostics are usually employed to distinguish between star formation and AGN-powered emission. However, this method is biased against dusty sources, hampering a complete census of the AGN population across cosmic epochs. To mitigate this effect, it is crucial to observe at longer wavelengths in the rest-frame near-infrared (near-IR), which is less affected by dust attenuation and can thus provide a better description of the intrinsic properties of galaxies. AGN diagnostics in this regime have not been fully exploited so far, due to the scarcity of near-IR observations of both AGNs and star-forming galaxies, especially at redshifts higher than 0.5. Using Cloudy photoionization models, we identify new AGN - star formation diagnostics based on the ratio of bright near-infrared emission lines, namely [SIII] 9530 Angstrom, [CI] 9850 Angstrom, [PII] 1.188 $μm$, [FeII] $1.257 μm$, and [FeII] $1.64 μm$ to Paschen lines (either Pa$γ$ or Pa$β$), providing simple, analytical classification criteria. We apply these diagnostics to a sample of 64 star-forming galaxies and AGNs at 0 < z < 1, and 65 sources at 1 < z < 3 recently observed with JWST-NIRSpec in CEERS. We find that the classification inferred from the near-infrared is broadly consistent with the optical one based on the BPT and the [SII]/H$α$ ratio. However, in the near-infrared, we find $\sim 60 \%$ more AGNs than in the optical (13 instead of 8), with 5 sources classified as 'hidden' AGNs, showing a larger AGN contribution at longer wavelengths, possibly due to the presence of optically thick dust. The diagnostics we present provide a promising tool to find and characterize AGNs from z=0 to z=3 with low and medium-resolution near-IR spectrographs in future surveys.

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AstroVisBench: A Code Benchmark for Scientific Computing and Visualization in Astronomy

Large Language Models (LLMs) are being explored for applications in scientific research, including their capabilities to synthesize literature, answer research questions, generate research ideas, and even conduct computational experiments. Ultimately, our goal is for these to help scientists derive novel scientific insights. In many areas of science, such insights often arise from processing and visualizing data to understand its patterns. However, evaluating whether an LLM-mediated scientific workflow produces outputs conveying the correct scientific insights is challenging to evaluate and has not been addressed in past work. We introduce AstroVisBench, the first benchmark for both scientific computing and visualization in the astronomy domain. AstroVisBench judges a language model's ability to both (1) create astronomy-specific workflows to process and analyze data and (2) visualize the results of these workflows through complex plots. Our evaluation of visualizations uses a novel LLM-as-a-judge workflow, which is validated against annotation by five professional astronomers. Using AstroVisBench we present an evaluation of state-of-the-art language models, showing a significant gap in their ability to engage in astronomy research as useful assistants. This evaluation provides a strong end-to-end evaluation for AI scientists that offers a path forward for the development of visualization-based workflows, which are central to a broad range of domains from physics to biology.

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The Backup Program of the Dark Energy Spectroscopic Instrument's Milky Way Survey

The Milky Way Backup Program (MWBP), a survey currently underway with the Dark Energy Spectroscopic Instrument (DESI) on the Nicholas U. Mayall 4-m Telescope, works at the margins of the DESI Main surveys to obtain spectra of millions of additional stars from the Gaia catalog. Efficiently utilizing twilight times (<18 deg) and poor weather conditions, the MWBP extends the range of stellar sources studied to both brighter magnitudes and lower Galactic latitude and declination than the stars studied in DESI's Main Milky Way Survey. While the MWBP prioritizes candidate giant stars selected from the Gaia catalog (using color and parallax criteria), it also includes an unbiased sample of bright stars (i.e., 11.2 < G < 16 mag) as well as fainter sources (to G < 19 mag). As of March 1, 2025, the survey had obtained spectra of ~7 million stars, approximately 1.2 million of which are included in the DESI Data Release 1. The full survey, when completed, will cover an area of more than 21,000 square degrees and include approximately 10 million Gaia sources, roughly equal to the number of stellar spectra obtained through the DESI Main Survey, while only utilizing <9% of all DESI observing time.

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JWST NIRCam simulations and observations of AGN ionization cones in cosmic noon galaxies

The extended narrow line region (NLR) of Active Galactic Nuclei (AGN) provides a valuable laboratory for exploring the relationship between AGN and their host galaxies, often appearing as an "ionization cone" that can extend out to the very edge of the galaxy. We use new James Webb Space Telescope (JWST) NIRCam imaging to study the morphologies and sizes of NLRs traced by [O III] at cosmic noon ($z\sim2-3$). To determine NIRCam's ability to probe the properties of the NLR in cosmic noon galaxies, we present simulated images of AGN at $z=2-3$ created with archival data cubes from the Multi Unit Spectroscopic Explorer (MUSE) of nine nearby ($z<0.05$) AGN host galaxies with previously confirmed extended NLRs. Our simulated images show that NIRCam is able to resolve the morphologies of NLRs at $z=2-3$ with narrow- and medium-band observations. We then search for extended NLRs with NIRCam medium-band observations targeting the [O III]$+\mathrm{H}β$ emission in twenty-seven previously identified AGN at $z=2.4-3.4$ in the Great Observatories Origins Deep Survey South (GOODS-S) field. We detect six galaxies in our observed sample with [O III]$+\mathrm{H}β$ morphologies consistent with AGN ionization cones with characteristic NLR sizes of $1-2.5$ kpc. Thanks to our simulated data, we can predict the effects of cosmological surface brightness dimming and instrument noise on the NLR size measurements at high redshift, which has the biasing effect of lowering the NLR size-AGN luminosity trend that is observed at low redshift by a factor of $\sim 2$.

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SPARCL: SPectra Analysis and Retrievable Catalog Lab

SPectra Analysis and Retrievable Catalog Lab (SPARCL) at NOIRLab's Astro Data Lab was created to efficiently serve large optical and infrared spectroscopic datasets. It consists of services, tools, example workflows and currently contains spectra for over 7.5 million stars, galaxies and quasars from the Sloan Digital Sky Survey (SDSS) and the Dark Energy Spectroscopic Instrument (DESI) survey. We aim to eventually support the broad range of spectroscopic datasets that will be hosted at NOIRLab and beyond. Major elements of SPARCL include capabilities to discover and query for spectra based on parameters of interest, a fast web service that delivers desired spectra either individually or in bulk as well as documentation and example Jupyter Notebooks to empower users in their research. More information is available on the SPARCL website (https://astrosparcl.datalab.noirlab.edu).

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The Rise of Faint, Red AGN at $z>4$: A Sample of Little Red Dots in the JWST Extragalactic Legacy Fields

We present a sample of 341 "little red dots" (LRDs) spanning the redshift range $z\sim2-11$ using data from the CEERS, PRIMER, JADES, UNCOVER and NGDEEP surveys. Unlike past use of color indices to identify LRDs, we employ continuum slope fitting using shifting bandpasses to sample the same rest-frame emission blueward and redward of the Balmer break. This enables the detection of LRDs over a wider redshift range and with less contamination from galaxies with strong breaks that otherwise lack a rising red continuum. The redshift distribution of our sample increases at $z<8$ and then undergoes a rapid decline at $z\sim4.5$, which may tie the emergence of these sources to the inside-out growth that galaxies experience during this epoch. We find that LRDs are $\sim1$ dex more numerous than X-ray and UV selected AGN at z~5-7. Within our sample, we have identified the first two X-ray detected LRDs. An X-ray spectral analysis confirms that these AGN are moderately obscured with $\log\,(N_{\rm H}/{\rm cm}^{2}$) of $23.3^{+0.4}_{-1.3}$ and $22.72^{+0.13}_{-0.16}$. Our analysis reveals that reddened AGN emission dominates their rest-optical light, while the rest-UV originates from their host galaxies. We also present NIRSpec observations from the RUBIES survey of 17 LRDs that show broad emission lines consistent with AGN activity. The confirmed AGN fraction of our sample is 71\% for sources with F444W<26.5. In addition, we find three LRDs with blue-shifted Balmer absorption features in their spectra, suggesting an outflow of high-density, low-ionization gas from near the central engine of these faint, red AGN.

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A high black hole to host mass ratio in a lensed AGN in the early Universe

Early JWST observations have uncovered a new population of red sources that might represent a previously overlooked phase of supermassive black hole growth (Kocevski et al. 2023; Matthee et al. 2023, Labbé et al. 2023). One of the most intriguing examples is an extremely red, point-like object that was found to be triply-imaged by the strong lensing (SL) cluster Abell 2744 (Furtak et al. 2023). Here we present deep JWST/NIRSpec observations of this object, Abell2744-QSO1. The spectroscopy confirms that the three images are of the same object, and that it is a highly reddened ($A_V\simeq3$) broad emission-line Active Galactic Nucleus (AGN) at a redshift of $z_{\mathrm{spec}}=7.0451\pm0.0005$. From the width of H$β$ ($\mathrm{FWHM}=2800\pm250\,\frac{\mathrm{km}}{\mathrm{s}}$) we derive a black hole mass of $M_{\mathrm{BH}}=4_{-1}^{+2}\times10^7\,\mathrm{M}_{\odot}$. We infer a very high ratio of black hole to galaxy mass of at least 3%, an order of magnitude more than is seen in local galaxies (Bennert et al. 2011), and possibly as high as 100%. The lack of strong metal lines in the spectrum together with the high bolometric luminosity ($L_{\mathrm{bol}}=(1.1\pm0.3)\times10^{45}\,\frac{\mathrm{erg}}{\mathrm{s}}$) indicate that we are seeing the black hole in a phase of rapid growth, accreting at 30% of the Eddington limit. The rapid growth and high black hole to galaxy mass ratio of A2744-QSO1 suggest that it may represent the missing link between black hole seeds (Volonteri et al. 2021) and the first luminous quasars (Fan et al. 2022).

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Emission Line Predictions for Mock Galaxy Catalogues: a New Differentiable and Empirical Mapping from DESI

We present a simple, differentiable method for predicting emission line strengths from rest-frame optical continua using an empirically-determined mapping. Extensive work has been done to develop mock galaxy catalogues that include robust predictions for galaxy photometry, but reliably predicting the strengths of emission lines has remained challenging. Our new mapping is a simple neural network implemented using the JAX Python automatic differentiation library. It is trained on Dark Energy Spectroscopic Instrument Early Release data to predict the equivalent widths (EWs) of the eight brightest optical emission lines (including H$α$, H$β$, [O II], and [O III]) from a galaxy's rest-frame optical continuum. The predicted EW distributions are consistent with the observed ones when noise is accounted for, and we find Spearman's rank correlation coefficient $ρ_s > 0.87$ between predictions and observations for most lines. Using a non-linear dimensionality reduction technique (UMAP), we show that this is true for galaxies across the full range of observed spectral energy distributions. In addition, we find that adding measurement uncertainties to the predicted line strengths is essential for reproducing the distribution of observed line-ratios in the BPT diagram. Our trained network can easily be incorporated into a differentiable stellar population synthesis pipeline without hindering differentiability or scalability with GPUs. A synthetic catalogue generated with such a pipeline can be used to characterise and account for biases in the spectroscopic training sets used for training and calibration of photo-$z$'s, improving the modelling of systematic incompleteness for the Rubin Observatory LSST and other surveys.

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The UNCOVER Survey: A First-look HST+JWST Catalog of Galaxy Redshifts and Stellar Population Properties Spanning $0.2 \lesssim z \lesssim 15$

The recent UNCOVER survey with the James Webb Space Telescope (JWST) exploits the nearby cluster Abell 2744 to create the deepest view of our universe to date by leveraging strong gravitational lensing. In this work, we perform photometric fitting of more than 50,000 robustly detected sources out to $z \sim 15$. We show the redshift evolution of stellar ages, star formation rates, and rest-frame colors across the full range of $0.2 \lesssim z \lesssim 15$. The galaxy properties are inferred using the Prospector Bayesian inference framework using informative Prospector-$β$ priors on masses and star formation histories to produce joint redshift and stellar population posteriors, and additionally lensing magnification is performed on-the-fly to ensure consistency with the scale-dependent priors. We show that this approach produces excellent photometric redshifts with $σ_{\rm NMAD} \sim 0.03$, of a similar quality to the established photometric redshift code EAzY. In line with the open-source scientific objective of the Treasury survey, we publicly release the stellar population catalog with this paper, derived from the photometric catalog adapting aperture sizes based on source profiles. This release includes posterior moments, maximum-likelihood spectra, star-formation histories, and full posterior distributions, offering a rich data set to explore the processes governing galaxy formation and evolution over a parameter space now accessible by JWST.

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A CEERS Discovery of an Accreting Supermassive Black Hole 570 Myr after the Big Bang: Identifying a Progenitor of Massive z > 6 Quasars

We report the discovery of an accreting supermassive black hole at z=8.679, in CEERS_1019, a galaxy previously discovered via a Ly$α$-break by Hubble and with a Ly$α$ redshift from Keck. As part of the Cosmic Evolution Early Release Science (CEERS) survey, we observed this source with JWST/NIRSpec spectroscopy, MIRI and NIRCam imaging, and NIRCam/WFSS slitless spectroscopy. The NIRSpec spectra uncover many emission lines, and the strong [O III] emission line confirms the ground-based Ly$α$ redshift. We detect a significant broad (FWHM~1200 km/s) component in the H$β$ emission line, which we conclude originates in the broad-line region of an active galactic nucleus (AGN), as the lack of a broad component in the forbidden lines rejects an outflow origin. This hypothesis is supported by the presence of high-ionization lines, as well as a spatial point-source component embedded within a smoother surface brightness profile. The mass of the black hole is log($M_{BH}/M_{\odot})=6.95{\pm}0.37$, and we estimate that it is accreting at 1.2 ($\pm$0.5) x the Eddington limit. The 1-8 $μ$m photometric spectral energy distribution (SED) from NIRCam and MIRI shows a continuum dominated by starlight and constrains the host galaxy to be massive (log M/M$_{\odot}$~9.5) and highly star-forming (SFR~30 M$_{\odot}$ yr$^{-1}$). Ratios of the strong emission lines show that the gas in this galaxy is metal-poor (Z/Z$_{\odot}$~0.1), dense (n$_{e}$~10$^{3}$ cm$^{-3}$), and highly ionized (log U~-2.1), consistent with the general galaxy population observed with JWST at high redshifts. We use this presently highest-redshift AGN discovery to place constraints on black hole seeding models and find that a combination of either super-Eddington accretion from stellar seeds or Eddington accretion from massive black hole seeds is required to form this object by the observed epoch.

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Fast and efficient identification of anomalous galaxy spectra with neural density estimation

Current large-scale astrophysical experiments produce unprecedented amounts of rich and diverse data. This creates a growing need for fast and flexible automated data inspection methods. Deep learning algorithms can capture and pick up subtle variations in rich data sets and are fast to apply once trained. Here, we study the applicability of an unsupervised and probabilistic deep learning framework, the Probabilistic Autoencoder (PAE), to the detection of peculiar objects in galaxy spectra from the SDSS survey. Different to supervised algorithms, this algorithm is not trained to detect a specific feature or type of anomaly, instead it learns the complex and diverse distribution of galaxy spectra from training data and identifies outliers with respect to the learned distribution. We find that the algorithm assigns consistently lower probabilities (higher anomaly score) to spectra that exhibit unusual features. For example, the majority of outliers among quiescent galaxies are E+A galaxies, whose spectra combine features from old and young stellar population. Other identified outliers include LINERs, supernovae and overlapping objects. Conditional modeling further allows us to incorporate additional information. Namely, we evaluate the probability of an object being anomalous given a certain spectral class, but other information such as metrics of data quality or estimated redshift could be incorporated as well. We make our code publicly available at https://github.com/VMBoehm/Spectra_PAE

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ALMA FIR View of Ultra High-redshift Galaxy Candidates at $z\sim$ 11-17: Blue Monsters or Low-$z$ Red Interlopers?

We present ALMA Band~7 observations of a remarkably bright galaxy candidate at $z_{\rm phot}$=$16.7^{+1.9}_{-0.3}$ ($M_{\rm UV}$=$-21.6$), S5-z17-1, identified in JWST Early Release Observation data of Stephen's Quintet. We do not detect the dust continuum at 866~$μ$m, ruling out the possibility that \targb\ is a low-$z$ dusty starburst with a star-formation rate of $\gtrsim 30$~$M_{\odot}$~yr$^{-1}$. We detect a 5.1$σ$ line feature at $338.726\pm0.007$~GHz exactly coinciding with the JWST source position, with a 2\% likelihood of the signal being spurious. The most likely line identification would be [OIII]52$μ$m at $z=16.01$ or [CII]158$μ$m at $z=4.61$, whose line luminosities do not violate the non-detection of the dust continuum in both cases. Together with three other $z\gtrsim$ 11--13 candidate galaxies recently observed with ALMA, we conduct a joint ALMA and JWST spectral energy distribution (SED) analysis and find that the high-$z$ solution at $z\sim$11--17 is favored in every candidate as a very blue (UV continuum slope of $\simeq-2.3$) and luminous ($M_{\rm UV}\simeq[-$24:$-21]$) system. Still, we find in several candidates that reasonable SED fits ($Δ$ $χ^{2}\lesssim4$) are reproduced by type-II quasar and/or quiescent galaxy templates with strong emission lines at $z\sim3$--5, where such populations predicted from their luminosity functions and EW([OIII]+H$β$) distributions are abundant in survey volumes used for the identification of the $z\sim$11--17 candidates. While these recent ALMA observation results have strengthened the likelihood of the high-$z$ solutions, lower-$z$ possibilities are not completely ruled out in several of the $z\sim$11--17 candidates, indicating the need to consider the relative surface densities of the lower-$z$ contaminants in the ultra high-$z$ galaxy search.

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Siena Galaxy Atlas 2020

We present the 2020 version of the Siena Galaxy Atlas (SGA-2020), a multi-wavelength optical and infrared imaging atlas of 383,620 nearby galaxies. The SGA-2020 uses optical $grz$ imaging over $\approx20,000$ deg$^{2}$ from the DESI Legacy Imaging Surveys Data Release 9 and infrared imaging in four bands (spanning 3.4-22 $μ$m) from the six-year unWISE coadds; it is more than 95% complete for galaxies larger than $R(26)\approx25$ arcsec and $r<18$ measured at the 26 mag arcsec$^{-2}$ isophote in the $r$-band. The atlas delivers precise coordinates, multi-wavelength mosaics, azimuthally averaged optical surface brightness profiles, model images and photometry, and additional ancillary metadata for the full sample. Coupled with existing and forthcoming optical spectroscopy from the Dark Energy Spectroscopic Instrument (DESI), the SGA-2020 will facilitate new detailed studies of the star formation and mass assembly histories of nearby galaxies; enable precise measurements of the local velocity field via the Tully-Fisher and Fundamental Plane relations; serve as a reference sample of lasting legacy value for time-domain and multi-messenger astronomical events; and more.

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Dusty Starbursts Masquerading as Ultra-high Redshift Galaxies in JWST CEERS Observations

Lyman Break Galaxy (LBG) candidates at z>10 are rapidly being identified in JWST/NIRCam observations. Due to the (redshifted) break produced by neutral hydrogen absorption of rest-frame UV photons, these sources are expected to drop out in the bluer filters while being well detected in redder filters. However, here we show that dust-enshrouded star-forming galaxies at lower redshifts (z<7) may also mimic the near-infrared (near-IR) colors of z>10 LBGs, representing potential contaminants in LBG candidate samples. First, we analyze CEERS-DSFG-1, a NIRCam dropout undetected in the F115W and F150W filters but detected at longer wavelengths. Combining the JWST data with (sub)millimeter constraints, including deep NOEMA interferometric observations, we show that this source is a dusty star-forming galaxy (DSFG) at z~5.1. We also present a tentative 2.6sigma SCUBA-2 detection at 850um around a recently identified z~16 LBG candidate in the same field and show that, if the emission is real and associated with this candidate, the available photometry is consistent with a z~5 dusty galaxy with strong nebular emission lines despite its blue near-IR colors. Further observations on this candidate are imperative to mitigate the low confidence of this tentative submillimeter emission and its positional uncertainty. Our analysis shows that robust (sub)millimeter detections of NIRCam dropout galaxies likely imply z=4-6 redshift solutions, where the observed near-IR break would be the result of a strong rest-frame optical Balmer break combined with high dust attenuation and strong nebular line emission, rather than the rest-frame UV Lyman break. This provides evidence that DSFGs may contaminate searches for ultra high-redshift LBG candidates from JWST observations.

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The Physical Conditions of Emission-Line Galaxies at Cosmic Dawn from JWST/NIRSpec Spectroscopy in the SMACS 0723 Early Release Observations

We present rest-frame optical emission-line flux ratio measurements for five $z>5$ galaxies observed by the JWST Near-Infared Spectrograph (NIRSpec) in the SMACS 0723 Early Release Observations. We add several quality-control and post-processing steps to the NIRSpec pipeline reduction products in order to ensure reliable relative flux calibration of emission lines that are closely separated in wavelength, despite the uncertain \textit{absolute} spectrophotometry of the current version of the reductions. Compared to $z\sim3$ galaxies in the literature, the $z>5$ galaxies have similar [OIII]$λ$5008/H$β$ ratios, similar [OIII]$λ$4364/H$γ$ ratios, and higher ($\sim$0.5 dex) [NeIII]$λ$3870/[OII]$λ$3728 ratios. We compare the observations to MAPPINGS V photoionization models and find that the measured [NeIII]$λ$3870/[OII]$λ$3728, [OIII]$λ$4364/H$γ$, and [OIII]$λ$5008/H$β$ emission-line ratios are consistent with an interstellar medium that has very high ionization ($\log(Q) \simeq 8-9$, units of cm~s$^{-1}$), low metallicity ($Z/Z_\odot \lesssim 0.2$), and very high pressure ($\log(P/k) \simeq 8-9$, units of cm$^{-3}$). The combination of [OIII]$λ$4364/H$γ$ and [OIII]$λ$(4960+5008)/H$β$ line ratios indicate very high electron temperatures of $4.1<\log(T_e/{\rm K})<4.4$, further implying metallicities of $Z/Z_\odot \lesssim 0.2$ with the application of low-redshift calibrations for ``$T_e$-based'' metallicities. These observations represent a tantalizing new view of the physical conditions of the interstellar medium in galaxies at cosmic dawn.

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Reconstructing and Classifying SDSS DR16 Galaxy Spectra with Machine-Learning and Dimensionality Reduction Algorithms

Optical spectra of galaxies and quasars from large cosmological surveys are used to measure redshifts and infer distances. They are also rich with information on the intrinsic properties of these astronomical objects. However, their physical interpretation can be challenging due to the substantial number of degrees of freedom, various sources of noise, and degeneracies between physical parameters that cause similar spectral characteristics. To gain deeper insights into these degeneracies, we apply two unsupervised machine learning frameworks to a sample from the Sloan Digital Sky Survey data release 16 (SDSS DR16). The first framework is a Probabilistic Auto-Encoder (PAE), a two-stage deep learning framework consisting of a data compression stage from 1000 elements to 10 parameters and a density estimation stage. The second framework is a Uniform Manifold Approximation and Projection (UMAP), which we apply to both the uncompressed and compressed data. Exploring across regions on the compressed data UMAP, we construct sequences of stacked spectra which show a gradual transition from star-forming galaxies with narrow emission lines and blue spectra to passive galaxies with absorption lines and red spectra. Focusing on galaxies with broad emission lines produced by quasars, we find a sequence with varying levels of obscuration caused by cosmic dust. The experiments we present here inform future applications of neural networks and dimensionality reduction algorithms for large astronomical spectroscopic surveys.

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A Long Time Ago in a Galaxy Far, Far Away: A Candidate z ~ 12 Galaxy in Early JWST CEERS Imaging

We report the discovery of a candidate galaxy with a photo-z of z~12 in the first epoch of the JWST Cosmic Evolution Early Release Science (CEERS) Survey. Following conservative selection criteria we identify a source with a robust z_phot = 11.8^+0.3_-0.2 (1-sigma uncertainty) with m_F200W=27.3, and >7-sigma detections in five filters. The source is not detected at lambda < 1.4um in deep imaging from both HST and JWST, and has faint ~3-sigma detections in JWST F150W and HST F160W, which signal a Ly-alpha break near the red edge of both filters, implying z~12. This object (Maisie's Galaxy) exhibits F115W-F200W > 1.9 mag (2-sigma lower limit) with a blue continuum slope, resulting in 99.6% of the photo-z PDF 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*/Msol ~ 8.5 and is highly star-forming (log sSFR ~ -8.2 yr^-1), with a blue rest-UV color (beta ~ -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 which smoothly decline with increasing redshift. Should followup spectroscopy validate this redshift, our Universe was already aglow with galaxies less than 400 Myr after the Big Bang.

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CEERS Key Paper III: The Resolved Host Properties of AGN at 3 < z < 5 with JWST

We report on the host properties of five X-ray luminous Active Galactic Nuclei (AGN) identified at $3 < z < 5$ in the first epoch of imaging from the Cosmic Evolution Early Release Science Survey (CEERS). Each galaxy has been imaged with the \textit{James Webb Space Telescope} (\jwst) Near-Infrared Camera (NIRCam), which provides spatially resolved, rest-frame optical morphologies at these redshifts. We also derive stellar masses and star formation rates for each host galaxy by fitting its spectral energy distribution using a combination of galaxy and AGN templates. The AGN hosts have an average stellar mass of ${\rm log}(M_{*}/{\rm M_{\odot}} )= 11.0$, making them among the most massive galaxies detected at this redshift range in the current CEERS pointings, even after accounting for nuclear light from the AGN. We find that three of the AGN hosts have spheroidal morphologies, one is a bulge-dominated disk and one host is dominated by point-like emission. None are found to show strong morphological disturbances that might indicate a recent interaction or merger event. Notably, all four of the resolved hosts have rest-frame optical colors consistent with a quenched or post-starburst stellar population. The presence of AGN in passively evolving galaxies at $z>3$ is significant because a rapid feedback mechanism is required in most semi-analytic models and cosmological simulations to explain the growing population of massive quiescent galaxies observed at these redshifts. Our findings are in general agreement with this picture and show that AGN can continue to inject energy into these systems after their star formation is curtailed, possibly helping to maintain their quiescent state.

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