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Marc Huertas-Company

Publications and source records attributed to Marc Huertas-Company.

At least 19 recordsLinked to original sources

Rubin LSST DP2 unveils almost-dark galaxies in the Virgo Cluster

Galaxies with the faintest surface brightness are currently known only in the Local Group. Similar objects should exist beyond our vicinity and are crucial for understanding galaxy evolution, structure, and dark matter content, yet surveys have not reached the depth required to detect them systematically. We present a population of seven almost-dark galaxies identified in Data Preview 2 of the Rubin Legacy Survey of Space and Time. They surround M49 in the vicinity of the Virgo Cluster, and exhibit central surface brightnesses in the range of $26.9 - 28.5 \, \mathrm{mag \, arcsec^{-2}}$ in the $g$-band, with half-light radii of $0.6 - 4.6 \, \mathrm{kpc}$ at the distance of Virgo, and stellar masses of $10^6 - 10^7 \, \mathrm{M_\odot}$. Their characteristics are analogous to those of the faintest and low-mass galaxies identified among satellite galaxies And XXI, And XXIII, and And XXV in the Local Group. This discovery demonstrates the power of the forthcoming Rubin LSST 10-year survey to uncover extremely faint galaxies at scale, promising the large statistical samples needed to constrain the faint-end luminosity function and the nature of dark matter.

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Hidden in Pixels. I. Discovery of dual "little red dots" indicates excess clustering on kilo-parsec scales

``Little Red Dots'' (LRDs) are an abundant high-redshift population newly discovered by the James Webb Space Telescope (JWST) and considered to be an early growth phase of supermassive black holes (SMBHs). Using a method of pixel-by-pixel color selection and relaxing the compactness criteria, we identify four dual LRD candidates in the COSMOS-Web survey with projected separations of $0.\!\!^{\prime\prime}2$-$1.\!\!^{\prime\prime}2$. A comparison between existing LRD samples and mock data reveals that the projected separations of these dual LRD candidates are unlikely to result from chance projections of objects at different redshifts. Furthermore, two of the four systems are covered by COSMOS-3D slitless spectroscopy, and a single-line detection at the same observed wavelength for each LRD in a pair strongly supports that they are at identical redshifts. Assuming that the detected lines are H$α$ based on their high equivalent width and broad profile, the spectroscopic redshifts of $z=5.822$ and $5.464$ for the two pairs are consistent with their photometric redshifts, yielding projected separations of $1.64$ and $7.36\,{\rm kpc}$. These discoveries suggest that the angular auto-correlation function (ACF) of LRDs exhibits an excess ($\sim20$-$30$ times) on sub-arcsec (kilo-parsec) separations compared to an extrapolation of a power-law ACF of JWST-found AGNs measured over $10^{\prime\prime}$-$100^{\prime\prime}$. Our sample is likely to represent precursors of mergers between LRDs, and such mergers may be one of the mechanisms that can drive the rapid growth of SMBHs in their early evolutionary stages.

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Semiresolved Stellar Populations as Distance Indicators

Galaxy distances are central to our understanding of the Universe. Despite the success of existing approaches, independent and complementary methods remain valuable for testing systematic effects and extending the applicability range of different distance metrics. Here we demonstrate that the spectrum of an individual semi-resolved stellar population encodes direct information about its distance and that valuable distance constraints can, in principle, be obtained by combining multiple independent measurements. When applied to optical spectra of bulge of the Andromeda galaxy (M\,31), we derive a stellar population-based distance of 756$\pm$57 kpc ($μ_0 = 24.39 \pm 0.15$), in agreement with state-of-the-art measurements. Crucially, semi-resolved stellar population distances does not require secondary calibrations, although its absolute scale remains conditional on the adopted stellar population models. Our findings provide a first assessment of the feasibility of deriving stellar population-based distance estimates from simple stellar population models, motivating further tests of the broader applicability and precision of the method.

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A Pixel-by-Pixel Path to Population III Discovery with JWST

The identification of the first generation of metal-free stars, known as Population III (Pop~III), remains a primary goal of modern observational astronomy. While JWST has discovered an abundance of UV-bright galaxies at $z > 10$, distinguishing primordial stellar populations from early metal-enriched systems is a significant challenge. We present an end-to-end framework that combines physically motivated forward modelling from Yggdrasil primordial models with simulation-based inference (SBI) to test Pop~III detectability in JWST-like observations, from isolated sources to realistic overlap with enriched (Pop~II) hosts. Our analysis spans several Pop~III initial mass function (IMF) assumptions, nebular configurations, and Lyman-$α$ transmission scenarios, while mocking the noise properties and filter coverage of the JWST Advanced Deep Extragalactic Survey (JADES). We find that unresolved or integrated analyses are strongly limited by host-galaxy contamination, whereas spatially resolved, pixel-based model comparison substantially improves recoverability. In our resolved experiments, detectability is highest for young and massive Pop~III clumps in nearly-quenched hosts at larger projected separations from their centres, reaching $\sim 90\%$ recovery in favourable configurations, while older and centrally embedded clumps are rarely recovered. Applying the framework to a literature candidate yields spatially differentiated behaviour: a compact blue companion is preferentially described by Pop~III-like models, while the host is better explained by fiducial Pop~I/II models. Our pipeline provides practical criteria for future searches and motivates imaging-first, spectroscopy-assisted strategies for identifying primordial stellar populations in JWST data.

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Exploring the Relationship Between Bars, Star Formation Activity, and Host Galaxy Properties from $\mathbf{z \sim 0}$ to $\mathbf{z \sim 2}$

We present the most comprehensive study to date of the relationship between bars, star formation, and galaxy properties from $z \sim$ 0 to $z \sim$ 2. We use a mass-complete sample of 1,171 galaxies from the JWST CEERS survey with $M_\star > 10^{10} M_\odot$ and repeat the analysis using COSMOS-Web data. Our results are: 1) At high redshift ($z \sim$ $1-2$) barred galaxies tend to have high sSFRs and low Sérsic indices ($n \leq 2$), while at low redshifts barred galaxies emerge with both low sSFR and higher $n$, suggestive of quiescent galaxies with bulges. 2) The fractional contribution of barred quiescent galaxies to the bar fraction rises steeply from $z \sim$ 2 to $z \sim$ 0, while that of barred actively star-forming galaxies falls. 3) The fraction of quiescent galaxies that are barred rises steeply over the last 10 Gyr. 4) Our empirical results show good agreement with the TNG50-1 simulations for bars with $a_{\mathrm{bar}}$ $>$ 1.5 kpc. Our results allow for the possibility that bar-driven secular evolution may lead to quiescence and/or that bars are more likely to persist and grow in gas-poor, quiescent galaxies. The steep rise in the quiescent bar fraction over 10 Gyr may represent an evolutionary sequence whereby gas-rich disks at high redshift first develop short, dynamically young bars and over time, repeated bar-driven gas inflows lead to central starbursts and declining gas fractions that strengthen the bar as the galaxy transitions toward quiescence.

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Learning What's Real: Disentangling Signal and Measurement Artifacts in Multi-Sensor Data, with Applications to Astrophysics

Data collected from the physical world is always a combination of multiple sources: an underlying signal from the physical process of interest and a signal from measurement-dependent artifacts from the sensor or instrument. This secondary signal acts as a confounding factor, limiting our ability to extract information about the physics underlying the phenomena we observe. Furthermore, it complicates the combination of observations in heterogeneous or multi-instrument settings. We propose a deep learning framework that leverages overlapping observations, a dual-encoder architecture, and a counterfactual generation objective to disentangle these factors of variation. The resulting representations explicitly separate intrinsic signals from sensor-specific distortions and noise, and can be used for counterfactual view generation, parameter inference unconfounded by measurement distortions, and instrument-independent similarity search. We demonstrate the effectiveness of our approach on astrophysical galaxy images from the DESI Legacy Imaging Survey (Legacy) and the Hyper Suprime-Cam (HSC) Survey as a representative multi-instrument setting. This framework provides a general recipe for scientific and multi-modal self-supervised pretraining: construct training pairs from overlapping observations of the same physical system, treat sensor- or modality-specific effects as augmentations, and learn invariant representations through counterfactual generation.

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FASTAR -- II. Semi-resolved evolutionary stellar population models

Standard evolutionary synthesis models rely on the assumption of a fully sampled stellar initial mass function (IMF). Under this assumption, the age, chemical composition, and IMF uniquely define the predicted absorption spectra. However, with current instrumentation pushing observations towards higher spatial resolutions and lower surface brightnesses, the assumption of a fully sampled IMF does not always hold true. Here we present the semi-resolved version of the FASTAR models, a comprehensive set of evolutionary synthesis predictions able to reproduce the stochastic behavior of discretely-sampled IMFs. Semi-resolved FASTAR predictions share the same evolutionary principles, ingredients, and features of the integral (fully sampled IMF) version of the FASTAR models, expanding a range of ages from 20 Myr to 14 Gyr, metallicities between -2.5 < [M/H] < +0.3, and several IMF functional forms. Detailed spectroscopic measurements can be carried out within the 3,540-7,400 A wavelength range, and low-resolution spectral energy distributions can also be synthesized over a wider 2,000-to-12,000 A coverage. Semi-resolved FASTAR models also depend on the number of stars contributing to the observed spectra, which determines the effective sampling of the different stellar evolutionary phases along the isochrones. This incomplete sampling implies that semi-resolved FASTAR models are inevitably stochastic. On top of the inherent stochasticity of the models, derived quantities such as equivalent widths, colors, or mass-to-light ratios might present strong deviations compared to standard fully sampled simple stellar population models. This stochasticity dilutes the boundary between model predictions and data, promoting new sampling-based inference approaches. FASTAR semi-resolved models allow for the effective exploration of the parameter space thanks to their optimized, JAX-based computation.

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FASTAR -- I. Continuous and differentiable evolutionary stellar population models

The development of evolutionary stellar population models is central to interpreting observations of galaxies in terms of astrophysical quantities. Stellar population models must therefore be both accurate and compatible with inversion algorithms in order to extract meaningful information from the observed data. Here we present FASTAR, a fully differentiable stellar population synthesis code. Contrary to traditional, grid-based single stellar population models, FASTAR can be continuously evaluated at any age (between 20 Myr and 14 Gyr), metallicity (-2.5 < [M/H] < +0.3), and initial mass function (IMF). Changes in the IMF parameterization are straightforward, allowing for consistent conversions of colors, magnitudes, and mass-to-light ratios, as well as the synthesis of models under the assumption of arbitrary IMF functional forms. FASTAR provides detailed spectroscopic predictions over the MILES wavelength range (3,540-7,400 A) as well as more coarsely sampled spectral energy distributions across a wider 2,000-to-12,000 A, which can be directly convolved with any arbitrary set of photometric filters. FASTAR performs at the same level of state-of-the-art simple stellar population models benchmarked against observations of globular clusters and high signal-to-noise spectra of early-type galaxies, but it is faster, lighter, and more flexible. Moreover, its differentiable nature allows for a quantitative understanding of model behavior and uncertainties, as well as a natural framework for gradient descent inference algorithms.

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The GlimmIr: Spectroscopic Variability in a z~7 LRD Indicates Rapid Changes in Both the Narrow and Broad Line Regions

The enigmatic population of ``Little Red Dots'' (LRDs) sit at the center of some of the largest debates in extragalactic astronomy today. The source(s) of ionizing emission and the physical scale over which it governs is still largely unknown. We show for the first time spectroscopic variability in a z ~ 7 LRD. Comparing a recently obtained 10.2 hr JWST/NIRSpec F290LP/G395M spectrum via the C3PO survey to an 8.4 hr F290LP/G395M spectrum taken 99 days earlier (~13 rest-days) via the THRILS survey, we find a ~30% $ difference in the continuum and broad-line flux, and a 42% difference between [OIII]5008 flux in the two epochs. Through rigorous testing, we confirm that such differences are not the result of differing MSA slit placements on source nor merely flux calibration offsets. These results are further corroborated by both a similar continuum and [OIII]5008 flux differences found in NIRSpec prism/clear observations of the source at an epoch taken approximately a year earlier than the THRILS observations via RUBIES and an additional observation fortuitously taken during the THRILS epoch (within a rest-day) via the CAPERS survey. Assuming LRDs are a type of accreting black hole system, this implies direct sight-lines must exist from the accretion disk to the surrounding nebular gas on scales beyond the broad-line region, and thus any high-density gas interpretations must allow for covering fractions < 100%. Furthermore, these results show the [OIII] line emission is likely not galaxy process-dominated, with a significant population of the narrow-line emitting gas closest to the broad-line region being directly ionized by the LRD. Finally, these results highlight the need for new approaches in inferring black hole properties of these systems, accounting for the lack of significant ionization via star formation, and/or exploring more exotic host-galaxy conditions at these early epochs.

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A Morphology Catalog of Galaxies in CEERS: Evolution in the Size and Color Gradients of Galaxies Since Cosmic Dawn

We present measurements of morphological parameters from fitting 53,885 galaxies detected to a magnitude limit of F356W$< 28.5$ in the CEERS NIRCam imaging with galfit in six broadband filters: F115W, F150W, F200W, F277W, F356W, and F444W. We provide a public catalog of Sérsic index, effective semi-major axis, axis ratio, integrated magnitude, and position angle for these galaxies in each of the filters. Uncertainties in the measured parameters are estimated from simulated galaxies that have similar noise and background properties as the observed galaxies. We compare our measurements with those in the CANDELS/EGS field measured with HST/WFC3 and find that the sizes agree to within 0.09 dex and the Sérsic indices agree to within 0.13 dex. We further present the evolution in the size-mass relation, and find that the evolution to $z\sim9$ is consistent with previous results derived at lower redshift. Finally, we look at the color gradients of galaxies at $1 2.5$), the color gradients are nearly flat with no dependence on mass, indicating that the stellar populations are more uniform throughout. The structural measurements presented are accurate to $20\%$ or better for most galaxies with F356W $<27.0$ mag and will enable further studies of galaxy morphology to $z\sim10$.

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Through Thick and Thin: The Cosmic Evolution of Disk Scale Height

To investigate the formation and evolution of vertical structures in disk galaxies, we measure global $\operatorname{sech}^2$ scale heights, averaging thin and thick components when present, for 2631 edge-on disk galaxies with $M_*>10^{10} M_\odot$ at $0 1.5$, but rises to $4.0\pm0.4$ at $z=0.25$. These results imply that the high-redshift progenitors of present-day thick disks were of intermediate thickness, neither thin nor thick, yet dynamically hot and dense. The observed radial variation of scale height is consistent with the artificial flaring expected from observational effects, disfavoring minor mergers as the primary mechanism of disk thickening. Instead, we suggest that the high-redshift intermediate-thickness disks were single-component systems that increased their vertical scale height through decreasing surface mass density and/or violent gravitational instabilities, eventually producing thick disks. Thin-disk growth begins at $z\approx2$ and dominates at $z\lesssim1$, yielding a vertically more compact system with decreasing scale heights from $z\approx1$ to $0$. The inferred thin-disk mass fraction increases from $0.1\pm0.03$ at $z=1$ to $0.6\pm0.1$ at $z=0$. Together, these findings reveal a continuous evolutionary link between high-redshift single-component disks and present-day thick thin disk systems.

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ERGO-ML: The assembly histories of HSC galaxy images via invertible neural networks, contrastive learning, and cosmological simulations

In this paper of ERGO-ML (Extracting Reality from Galaxy Observables with Machine Learning), we develop a model that infers the merger/assembly histories of galaxies directly from optical images. We apply the self-supervised contrastive learning framework NNCLR (Nearest-Neighbor Contrastive Learning of visual Representations) on realistic HSC mock images (g,r,i - bands) produced from galaxies simulated within the TNG50 and TNG100 flagship runs of the IllustrisTNG project. The resulting representation is then used as conditional input for a cINN (conditional Invertible Neural Network) to gain posteriors for merger/assembly statistics, particularly the lookback time and stellar mass of the last major merger and the fraction of ex-situ stars. Through validation against the ground truth available for simulated galaxies, we assess the performance of our model, achieving good accuracy in inferring the stellar ex-situ fraction ($\le \pm 10$ per cent for 80 per cent of the test sample) and the mass of the last major merger (within $\pm 0.5 \log \MSUN$ for stellar masses $>10^{9.5} \MSUN$ ). We successfully apply the TNG-trained model to simulated mocks from the EAGLE simulation, demonstrating that our model is applicable outside of the TNG domain. We use our simulation-based model to infer aspects of the history of observed galaxies, in particular for HSC images that are close to the domain of TNG ones. We recover the trend of increasing ex-situ stellar fraction with stellar mass and more spherical morphology, but we also identify a discrepancy between TNG and HSC: on average, observed galaxies generally exhibit lower ex-situ fractions. Despite challenges such as information loss (e.g. projection effects and surface brightness limits) and domain shifts (from simulations to observations), our results demonstrate the feasibility of extracting the merger past of galaxies from their optical images.

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Why the Northern Hemisphere Needs a 30-40 m Telescope and the Science at Stake: Cosmology and High-z Universe

Full sky coverage with 30-40 meter-class telescopes is essential to answer fundamental questions in Astrophysics, Cosmology, and Physics, such as the composition of the Universe and the formation of the first stars and supermassive black holes. An ELT/TMT-like telescope in the Northern Hemisphere is a fundamental and necessary facility to provide multiplexing of observing power, diversity of instrumentation, rapid response, and statistical power required to address the questions and the problems, current and future, unveiled by full sky observatories such as JWST, Euclid, or Roman space telescopes. The Northern ELT/TMT will expedite the study of unique, extreme, rare, transient, and/or high-energy events which will give the most information about fundamental Physics problems in the era of multi-messenger and time-domain Astronomy.

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THRILS -- The High-(Redshift+Ionization) Line Search: Program Description & Redshift Catalog

To date, many spectroscopic confirmations of z>7 galaxies have been obtained using JWST/NIRSpec prism observations, with most of their physical properties inferred from these observations and corresponding imaging. What is needed are higher-resolution spectra at deeper depths to study these sources in detail. We present The High-(Redshift+Ionization) Line Search (THRILS) program: deep (>8 hr) observations in two pointings of JWST/NIRSpec G395M spectroscopy to 1) probe high ionization spectral features in z>8 galaxies that are indicative of top-heavy initial mass functions or growing massive black holes, 2) search for accreting supermassive black holes in typical galaxies at z~4-9 through broad Balmer line emission, and 3) probe the stellar-mass growth histories of massive galaxies. We include spectroscopic redshift measurements for 89 sources from the THRILS data, as well as a detection threshold for the full and half depth integration times of the program.

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Beyond the Monsters: A More Complete Census of Black Hole Activity at Cosmic Dawn

JWST has revealed an abundance of low-luminosity active galactic nuclei (AGN) at high redshifts ($z > 3$), pushing the limits of black hole (BH) science in the early Universe. Results have claimed that these BHs are significantly more massive than expected from the BH mass-host galaxy stellar mass relation derived from the local Universe. We present a comprehensive census of the BH populations in the early Universe through a detailed stacking analysis of galaxy populations, binned by luminosity and redshift, using JWST spectroscopy from the CEERS, JADES, RUBIES, and GLASS extragalactic deep field surveys. Broad H$α$ detections in $31\%$ of the stacked spectra (5/16 bins) imply median BH masses of $10^{5.21} - 10^{6.13}~ \rm{M_{\odot}}$ and the stacked SEDs of these bins indicate median stellar masses of $10^{7.84} - 10^{8.56} ~\rm{M_{\odot}}$. This suggests that the median galaxy hosts a BH that is at most a factor of 10 times over-massive compared to its host galaxy and lies closer to the locally derived $M_{BH}-M_*$ relation. We investigate the seeding properties of the inferred BHs and find that they can be well-explained by a light stellar remnant seed undergoing moderate Eddington accretion. Our results indicate that individual detections of AGN are more likely to sample the upper envelope of the $M_{BH}-M_*$ distribution, while stacking on ``normal" galaxies and searching for AGN signatures can overcome the selection bias of individual detections.

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Flexible Simulation Based Inference for Galaxy Photometric Fitting with Synthesizer

We introduce Synference, a new, flexible Python framework for galaxy SED fitting using simulation-based inference (SBI). Synference leverages the Synthesizer package for flexible forward-modelling of galaxy SEDs and integrates the LtU-ILI package to ensure best practices in model training and validation. In this work we demonstrate Synference by training a neural posterior estimator on $10^6$ simulated galaxies, based on a flexible 8-parameter physical model, to infer galaxy properties from 14-band HST and JWST photometry. We validate this model, demonstrating excellent parameter recovery (e.g. R$^2>$0.99 for M$_\star$) and accurate posterior calibration against nested sampling results. We apply our trained model to 3,088 spectroscopically-confirmed galaxies in the JADES GOODS-South field. The amortized inference is exceptionally fast, having nearly fixed cost per posterior evaluation and processing the entire sample in $\sim$3 minutes on a single CPU (18 galaxies/CPU/sec), a $\sim$1700$\times$ speedup over traditional nested sampling or MCMC techniques. We demonstrate Synference's ability to simultaneously infer photometric redshifts and physical parameters, and highlight its utility for rapid Bayesian model comparison by demonstrating systematic stellar mass differences between two commonly used stellar population synthesis models. Synference is a powerful, scalable tool poised to maximise the scientific return of next-generation galaxy surveys.

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The stellar mass function of quiescent and star-forming galaxies and its dependence on morphology in COSMOS-Web

We study the stellar mass function (SMF) of quiescent and star-forming galaxies and its dependence on morphology in 10 redshift bins at $0.2 0.6$) dominate the quiescent SMF at ${\rm log}(M_{\star}/{\rm M_{\odot}})>10$ at all redshifts, while disks ($B/T<0.2$) dominate at ${\rm log}(M_{\star}/{\rm M_{\odot}})<9$. However, most bulge-dominated galaxies are star-forming, with their fraction increasing with redshift and decreasing mass, consistent with being progenitors of quiescent bulges. We find evidence for environmental quenching onset at $z\sim3$ from the upturn in the quiescent SMF at ${\rm log}(M_{\star}/{\rm M_{\odot}})<9.5$, contributed by disk-dominated galaxies consistent with satellite quenching that retains disk morphologies. Number densities of ${\rm log}(M_{\star}/{\rm M_{\odot}})>10$ quiescent galaxies are lower than recent literature by $0.1-0.7$ dex, but agree well with simulations at $2 3$, simulations increasingly underpredict observations. Finally, we build an empirical model describing galaxy number density evolution by parametrizing quenching rates, baryon conversion efficiency, and bulge formation. Our model supports a scenario where star-forming galaxies grow central bulges before quenching in massive halos.

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Simulation-based inference of galaxy properties from JWST pixels

We present an efficient Bayesian SED-fitting framework tailored to multiwavelength pixel photometry from the JWST Advanced Deep Extragalactic Survey (JADES). Our method employs simulation-based inference to enable rapid posterior sampling across galaxy pixels, leveraging the unprecedented spatial resolution, wavelength coverage, and depth provided by the survey. It is trained on synthetic photometry generated from MILES stellar population models, incorporating both parametric and non-parametric SFHs, realistic noise, and JADES-like filter sensitivity thresholds. We validate this amortised inference approach on mock datasets, achieving robust and well-calibrated posterior distributions, with an $R^2$ score of 0.99 for stellar mass. Applying our pipeline to real observations, we derive spatially resolved maps of stellar population properties down to $\mathrm{S/N}_{\rm{pixel}}=5$ (averaged over F277W, F356W, F444W) for 1083 JADES galaxies and ~2 million pixels with spectroscopic redshifts. These maps enable the identification of dusty or starburst regions and offer insights into mass growth and the structural assembly. We assess the outshining phenomenon by comparing pixel-based and integrated stellar mass estimates, finding limited impact only in low-mass galaxies ($<10^8M_{\odot}$) but systematic differences of ~0.20 dex linked to SFH priors. With an average posterior sampling speed of $10^{-4}$ seconds per pixel and a total inference time of ~1 CPU-day for the full dataset, our model offers a scalable solution for extracting high-fidelity stellar population properties from HST+JWST datasets, opening the way for statistical studies at sub-galactic scales.

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