arXiv subjects

Christopher C. Lovell

Publications and source records attributed to Christopher C. Lovell.

At least 37 records · Page 2Linked to original sources

arXiv2025

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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arXiv2025

Think inside the box: cosmic variance and large-scale conformity of high-redshift massive galaxies in the FLAMINGO simulations

We use the highest-resolution FLAMINGO hydrodynamical simulation to quantify cosmic variance and large-scale coherence in the evolution of massive galaxies at high redshift. FLAMINGO combines a $(1\,\mathrm{cGpc})^3$ volume with baryonic resolution sufficient to identify ${\gtrsim}\,10^3$ independent JWST-like survey volumes of $(100\,\mathrm{cMpc})^3$, providing unprecedented statistics to characterize the extremes of cosmic variance. At $z\,{\simeq}\,6$, the total variance in the number of haloes with $M_{200}\,{\simeq}\,10^{11.5}\,\mathrm{M_\odot}$ (or $M_\ast\,{\simeq}\,10^{10}\,\mathrm{M_\odot}$) is 2--3 times the Poisson expectation, while this ratio decreases with redshift. Similarly, at $z\,{\gtrsim}\,4$, the variance in the most massive halo per JWST-like field is twice the Poisson prediction. We find a pronounced large-scale \emph{conformity}: in volumes ranked by the stellar mass of their most massive galaxy ($M_{\ast,\mathrm{max}}$), the stellar-to-halo mass relation and star-formation efficiency are coherently elevated or suppressed throughout the full $(100\,\mathrm{cMpc})^3$ volume. When accounting for galaxies outside the volume, this signal persists only to radii $\lesssim 50\,\mathrm{cMpc}$, demonstrating that the detectable conformity is enhanced by the survey footprint. Moreover, $M_{\ast,\mathrm{max}}$ is a better predictor of the volume-wide efficiency of massive galaxies than the total number counts, which mainly trace clustering. Finally, the stellar fraction of the most massive galaxies peaks at $f_\ast\,{=}\,M_\ast\,/\,(M_{200}f_{\rm b,cosmic})\,{\simeq}\,0.2$ at $z\,{\simeq}\,5$, with a narrower dispersion in $f_\ast$ at fixed redshift and stronger redshift evolution than commonly assumed. These results show that both cosmic variance and footprint-confined conformity must be modelled when interpreting early massive galaxy populations in JWST fields.

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arXiv2025

Galactification: painting galaxies onto dark matter only simulations using a transformer-based model

Connecting the formation and evolution of galaxies to the large-scale structure is crucial for interpreting cosmological observations. While hydrodynamical simulations accurately model the correlated properties of galaxies, they are computationally prohibitive to run over volumes that match modern surveys. We address this by developing a framework to rapidly generate mock galaxy catalogs conditioned on inexpensive dark-matter-only simulations. We present a multi-modal, transformer-based model that takes 3D dark matter density and velocity fields as input, and outputs a corresponding point cloud of galaxies with their physical properties. We demonstrate that our trained model faithfully reproduces a variety of galaxy summary statistics and correctly captures their variation with changes in the underlying cosmological and astrophysical parameters, making it the first accelerated forward model to capture all the relevant galaxy properties, their full spatial distribution, and their conditional dependencies in hydrosimulations.

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arXiv2025

Learning the Universe: Cosmological and Astrophysical Parameter Inference with Galaxy Luminosity Functions and Colours

We perform the first direct cosmological and astrophysical parameter inference from the combination of galaxy luminosity functions and colours using a simulation based inference approach. Using the Synthesizer code we simulate the dust attenuated ultraviolet-near infrared stellar emission from galaxies in thousands of cosmological hydrodynamic simulations from the CAMELS suite, including the Swift-EAGLE, IllustrisTNG, Simba & Astrid galaxy formation models. For each galaxy we calculate the rest-frame luminosity in a number of photometric bands, including the SDSS $\textit{ugriz}$ and GALEX FUV & NUV filters; this dataset represents the largest catalogue of synthetic photometry based on hydrodynamic galaxy formation simulations produced to date, totalling >200 million sources. From these we compile luminosity functions and colour distributions, and find clear dependencies on both cosmology and feedback. We then perform simulation based (likelihood-free) inference using these distributions to constrain $Ω_m$, $σ_8$, and four parameters controlling the strength of stellar and AGN feedback. Both colour distributions and luminosity functions provide complementary information on certain parameters when performing inference. We achieve constraints on the stellar feedback parameters, as well as $Ω_m$ and $σ_8$. The latter is attributable to the fact that the photometry encodes the star formation-metal enrichment history of each galaxy; galaxies in a universe with a higher $σ_8$ tend to form earlier and have higher metallicities, which leads to redder colours. We find that a model trained on one galaxy formation simulation generalises poorly when applied to another, and attribute this to differences in the subgrid prescriptions, and lack of flexibility in our emission modelling. The photometric catalogues are publicly available at: https://camels.readthedocs.io/

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arXiv2025

First Light And Reionization Epoch Simulations (FLARES) -- XIX: Supermassive black hole mergers in the early Universe and their environmental dependence

The upcoming space-based gravitational wave (GW) observatory, LISA, is expected to detect GW signals from supermassive black hole (SMBH) mergers occurring at high redshifts. However, understanding the origin and growth of SMBHs in the early Universe remains an open problem in astrophysics. In this work, we utilize the First Light And Reionization Epoch Simulations (FLARES), a suite of cosmological hydrodynamical zoom-in simulations, to study SMBH mergers at $5 \lesssim z \lesssim 10$ across a wide range of environments. Most mergers in FLARES involve secondary SMBHs near the seed mass ($m_{\rm seed} \approx 1.5 \times 10^{5}~{\rm M}_{\odot}$) while primary SMBHs span up to $10^{9}~{\rm M}_{\odot}$, resulting in mass ratios from $q \sim 10^{-4}$ to $1$, with a peak at $q \sim 1$. The number of mergers increases rapidly towards lower redshifts, and the comoving total number density scales with overdensity as $n_{\rm merger} = 10^{-3.81} (1 + δ)^{4.78}$. Denser regions host more massive mergers, with higher merger redshifts and lower mass ratios. Within the FLARES redshift range, LISA is expected to detect mergers with $10^{5} \lesssim M_{\rm tot}/{\rm M}_{\odot} \lesssim 10^{8}$ and $q \gtrsim 10^{-2}$, corresponding to a detection rate of $0.030~{\rm yr}^{-1}$ for events with signal-to-noise ratio ${\rm SNR} \geq 10$. Our study demonstrates the sensitivity of GW predictions at high redshifts to SMBH seed models and merger time delays, highlighting the need for improved modeling in future cosmological simulations to maximize LISA's scientific return.

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arXiv2025

Synthesizer: a Software Package for Synthetic Astronomical Observables

We present Synthesizer, a fast, flexible, modular and extensible platform for modelling synthetic astrophysical observables. Synthesizer can be used for a number of applications, but is predominantly designed for generating mock observables from analytical and numerical galaxy formation simulations. These use cases include (but are not limited to) analytical modelling of the star formation and metal enrichment histories of galaxies, the creation of mock images and integral field unit observations from particle based simulations, detailed photoionisation modelling of the central regions of active galactic nuclei, and spectro-photometric fitting. We provide a number of stellar population synthesis models, photoionisation code configurations, dust models, and imaging configurations that can be used 'out-of-the-box' interactively. The code can be used to quantitatively test the dependence of forward modelled observables on various model and parameter choices, and rapidly explore large parameter ranges for calibration and inference tasks. We invite and encourage the community to use, test and develop the code, and hope that the foundation developed will provide a flexible framework for a number of tasks in forward and inverse modelling of astrophysical observables. The code is publicly available at https://synthesizer-project.github.io/

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arXiv2025

How does feedback affect the star formation histories of galaxies?

Star formation in galaxies is regulated by the interplay of a range of processes that shape the multiphase gas in the interstellar and circumgalactic media. Using the CAMELS suite of cosmological simulations, we study the effects of varying feedback and cosmology on the average star formation histories (SFHs) of galaxies at $z\sim0$ across the IllustrisTNG, SIMBA and ASTRID galaxy formation models. We find that galaxy SFHs in all three models are sensitive to changes in stellar feedback, which affects the efficiency of baryon cycling and the rates at which central black holes grow, while effects of varying AGN feedback depend on model-dependent implementations of black hole seeding, accretion and feedback. We also find strong interaction terms that couple stellar and AGN feedback, usually by regulating the amount of gas available for the central black hole to accrete. Using a double power-law to describe the average SFHs, we derive a general set of equations relating the shape of the SFHs to physical quantities like baryon fraction and black hole mass across all three models. We find that a single set of equations (albeit with different coefficients) can describe the SFHs across all three CAMELS models, with cosmology dominating the SFH at early times, followed by halo accretion, and feedback and baryon cycling at late times. Galaxy SFHs provide a novel, complementary probe to constrain cosmology and feedback, and can connect the observational constraints from current and upcoming galaxy surveys with the physical mechanisms responsible for regulating galaxy growth and quenching.

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arXiv2025

Explaining ultra-massive quiescent galaxies at $3 < z < 5$ in the context of their environments

The swift assembly of the earliest galaxies poses a significant challenge to our understanding of galaxy formation. Ultra-massive quiescent galaxies at intermediate redshifts ($3 < z < 5$) currently present one of the most pressing problems for theoretical modeling, since very few mechanisms can be invoked to explain how such galaxies formed so early in the history of the Universe. Here, we exploit the fact that these galaxies all reside within significant overdensities to explain their masses. To this end, we construct and release a modified version of the Extreme Value Statistics (EVS) code which takes into account galaxy environment by incorporating clustering in the calculation. With this new version of EVS, we find that ultra-massive quiescent galaxies at $3<z<5$ do not present as serious a tension with simple models of galaxy formation when the analysis of a given galaxy is conditioned on its environment.

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arXiv2025

First Light and Reionization Epoch Simulations (FLARES) -- XVIII: the ionising emissivities and hydrogen recombination line properties of early AGN

One of the most remarkable results from the \emph{James Webb Space Telescope} has been the discovery of a large population of compact sources exhibiting strong broad H$α$ emission, typically interpreted to be low-luminosity broad-line (Type 1) active galactic nuclei (BLAGN). An important question is whether these observations are in tension with galaxy formation models, and if so how? While comparisons have been made using physical properties (i.e.~black hole mass and accretion rate) inferred from observations, these require the use of SED modelling assumptions, or locally inferred scaling relations, which may be unjustified, at least in the distant high-redshift Universe. In this work we take an alternative approach and forward model predictions from the First Light And Reionisation Epoch Simulations (FLARES) suite of cosmological hydrodynamical zoom simulations to predict the observable properties of BLAGN. We achieve this by first coupling \flares\ with the \qsosed\ model to predict the ionising photon luminosities of high-redshift ($z>5$) AGN. To model the observed broad H$α$ emission we then assume a constant conversion factor and covering fraction, and the fraction of AGN that have observable broad-lines. With a reasonable choice of these parameters, \flares\ is able to reproduce observational constraints on the H$α$ luminosity function and equivalent width distribution at $z=5$.

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arXiv2025

Probing the co-evolution of SMBHs and their hosts from scaling relations pairwise residuals: dominance of stellar velocity dispersion and host halo mass

The correlations between Supermassive Black Holes (SMBHs) and their host galaxies still defy our understanding from both the observational and theoretical perspectives. Here we perform pairwise residual analysis on the latest sample of local inactive galaxies with a uniform calibration of their photometric properties and with dynamically measured masses of their central SMBHs. The residuals reveal that stellar velocity dispersion $σ$ and, possibly host dark matter halo mass $M_{\rm halo}$, appear as the galactic properties most correlated with SMBH mass, with a secondary (weaker) correlation with spheroidal (bulge) mass $M_{\rm sph}$, as also corroborated by additional Machine Learning tests. These findings may favour energetic/kinetic feedback from Active Galactic Nuclei (AGN) as the main driver in shaping SMBH scaling relations. Two state-of-the-art hydrodynamic simulations, inclusive of kinetic AGN feedback, are able to broadly capture the mean trends observed in the residuals, although they tend to either favour $M_{\rm sph}$ as the most fundamental property, or generate too flat residuals. Increasing AGN feedback kinetic output does not improve the comparison with the data. In the Appendix we also show that the galaxies with dynamically measured SMBHs are biased high in $σ$ at fixed luminosity with respect to the full sample of local galaxies, proving that this bias is not a byproduct of stellar mass discrepancies. Overall, our results suggest that probing the SMBH-galaxy scaling relations in terms of total stellar mass alone may induce biases, and that either current data sets are incomplete, and/or that more insightful modelling is required to fully reproduce observations.

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arXiv2025

Behind the Spotlight: A systematic assessment of outshining using NIRCam medium-bands in the JADES Origins Field

The spatial resolution and sensitivity of JWST's NIRCam instrument has revolutionised our ability to probe the internal structure of early galaxies. By leveraging deep medium-band imaging in the Jades Origins Field, we assemble comprehensive spectral energy distributions (SEDs) using 19 photometric bands for over 200 high-redshift galaxies ($z \geq 4.5$). We present an analysis of this sample with particular emphasis on investigating the "outshining" phenomenon, which can bias the inferred stellar populations by masking the presence of evolved stellar populations ($\geq$ 100 Myr) with the light of bright, young O and B-type stars. We address this problem by performing spatially-resolved SED-fitting of both binned and full pixel-by-pixel photometry, which we compare to the traditional integrated approach. We find evidence for systematic underestimation of stellar mass in low-mass galaxies ($\leq 10^9 \rm M_\odot$) with bursty star formation, which can exceed a factor of 10 in individual cases, but on average is typically a factor of 1.25-2.5, depending on the binning methodology and SFH model used. The observed mass offset correlates with burstiness (SFR$_{10 \ \rm Myr}$/SFR$_{100 \ \rm Myr}$) and sSFR, such that galaxies with recently rising SFHs have larger mass offsets. The integrated SFH models which produce the most consistent stellar masses are the double power-law and non-parametric `continuity' models, although no integrated model fully reproduces all resolved SFHs. We apply an outshining correction factor to the Stellar Mass Function at $z=7$, finding little impact within the uncertainties. We conclude that outshining can be important in individual low-mass galaxies, but the overall impact is limited and should be considered alongside other systematic SED fitting effects.

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arXiv2025

On the Significance of Rare Objects at High Redshift: The Impact of Cosmic Variance

The discovery of extremely luminous galaxies at ultra-high redshifts ($z\gtrsim 8$) has challenged galaxy formation models. Most analyses of this tension have not accounted for the variance due to field-to-field clustering, which causes the number counts of galaxies to vary greatly in excess of Poisson noise. This super-Poissonian variance is often referred to as cosmic variance. Since cosmic variance increases rapidly as a function of mass, redshift, and smaller observing areas, the most massive objects in deep \textit{JWST} surveys are severely impacted by cosmic variance. We construct a simple model, including cosmic variance, to predict the distribution of the mass of the most massive galaxy for different surveys, which increases the tension with observations. The distributions differ significantly from previous predictions using the Extreme Value Statistics formalism, changing the position and shape of the distributions. We test our model using the \texttt{UniverseMachine} simulations, where the predicted effects of cosmic variance are clearly identifiable. We find that the high skew in the distributions of galaxy counts for typical deep surveys imply a high statistical variance on the cosmic variance itself. This impacts the calibration of the cosmic variance, as well as the expected mass of the most massive galaxy. We also find that the impact of cosmic variance dominates the impact of any realistic scatter in the stellar-to-halo-mass relation at $z\gtrsim 12$. It is therefore crucial to accurately account for the impact of cosmic variance in any analysis of tension between early extreme galaxies and galaxy formation models.

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arXiv2025

First Light and Reionization Epoch Simulations (FLARES) -- XV: The physical properties of super-massive black holes and their impact on galaxies in the early universe

Understanding the co-evolution of super-massive black holes (SMBHs) and their host galaxies remains a key challenge of extragalactic astrophysics, particularly the earliest stages at high-redshift. However, studying SMBHs at high-redshift with cosmological simulations, is challenging due to the large volumes and high-resolution required. Through its innovative simulation strategy, the First Light And Reionisation Epoch Simulations (FLARES) suite of cosmological hydrodynamical zoom simulations allows us to simulate a much wider range of environments which contain SMBHs with masses extending to $M_{\bullet}>10^{9}\ M_{\odot}$ at $z=5$. In this paper, we use FLARES to study the physical properties of SMBHs and their hosts in the early Universe ($5\le\, z \le10$). FLARES predicts a sharply declining density with increasing redshift, decreasing by a factor of 100 over the range $z=5\to 10$. Comparison between our predicted bolometric luminosity function and pre-\emph{JWST} observations yield a good match. However, recent \emph{JWST} observations appear to suggest a larger contribution of SMBHs than previously observed, or predicted by FLARES. Finally, by using a re-simulation with AGN feedback disabled, we explore the impact of AGN feedback on their host galaxies. This reveals that AGN feedback results in a reduction of star formation activity, even at $z>5$, but only in the most massive galaxies. A deeper analysis reveals that AGN are also the cause of suppressed star formation in passive galaxies but that the presence of an AGN doesn't necessarily result in the suppression of star formation.

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arXiv2025

First Light And Reionisation Epoch Simulations (FLARES) XVI: Size Evolution of Massive Dusty Galaxies at Cosmic Dawn from UV to IR

We use the First Light And Reionisation Epoch Simulations (FLARES) to study the evolution of the rest-frame ultraviolet (UV) and far-infrared (FIR) sizes for a statistical sample of massive ($\gtrsim10^{9}$M$_{\odot}$) high redshift galaxies (z $\in$ [5,10]). Galaxies are post-processed using the SKIRT radiative transfer code, to self-consistently obtain the full spectral energy distribution and surface brightness distribution. We create mock observations of the galaxies for the Near Infrared Camera (NIRCam) to study the rest-frame UV 1500 $\unicode{xC5}$ morphology. We also generate mock rest-frame FIR (50 $μ$m) photometry and mock ALMA (158 $μ$m) (0.01"-0.03" and $\approx$0.3" angular resolution) observations to study the dust-continuum. We find the effect of dust on observed sizes reduces with increasing wavelength from the UV to optical ($\sim$0.6 times the UV at 0.4$μ$m), with no evolution in FIR sizes. Observed sizes vary within 0.4-1.2 times the intrinsic sizes at different signal to noise ratios (SNR = 5-20) across redshifts. The effect of PSF and noise makes bright structures prominent, whereas fainter regions blend with noise, leading to an underestimation (factor of 0.4-0.8) of sizes at SNR=5. At SNR=15-20, the underestimation reduces (factor of 0.6-0.9) at z=5-8 but due to PSF, at z=9-10, bright cores are dominant, resulting in an overestimation (factor of 1.0-1.2). For ALMA, low resolution sizes are effected by noise which acts as extended emission. The size evolution in UV broadly agrees with current observational samples and other simulations. This work is one of the first to analyse the panchromatic sizes of a statistically significant sample of simulated high-redshift galaxies, complementing a growing body of research highlighting the importance of conducting an equivalent comparison between observed galaxies and their simulated counterparts in the early Universe.

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arXiv2025

The Spectral Energy Distributions of Galaxies

The spectral energy distribution (SED) of a galaxy represents the distribution of electromagnetic radiation emitted across all wavelengths, from radio waves to gamma rays. The galaxy SED is akin to its fingerprint, and serves as a fundamental tool in modern astrophysics. It enables researchers to determine crucial properties of galaxies, including their star-formation rates, stellar populations, dust content, and evolutionary state. By analyzing galactic SEDs, astronomers can reconstruct the physical processes occurring within galaxies and trace their evolutionary histories. This article explores our current understanding of the components that contribute to galactic SEDs, the observational techniques used to measure them, and their applications in understanding galaxy formation and evolution.

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arXiv2025

Learning the Universe: physically-motivated priors for dust attenuation curves

Understanding the impact of dust on the spectral energy distributions (SEDs) of galaxies is crucial for inferring their physical properties and for studying the nature of interstellar dust. We analyze dust attenuation curves for $\sim 6400$ galaxies ($M_{\star} \sim 10^9 - 10^{11.5}\,M_{\odot}$) at $z=0.07$ in the IllustrisTNG50 and TNG100 simulations. Using radiative transfer post-processing, we generate synthetic attenuation curves and fit them with a parametric model that captures known extinction and attenuation laws (e.g., Calzetti, MW, SMC, LMC) and more exotic forms. We present the distributions of the best-fitting parameters: UV slope ($c_1$), optical-to-NIR slope ($c_2$), FUV slope ($c_3$), 2175 Angstrom bump strength ($c_4$), and normalization ($A_{\rm V}$). Key correlations emerge between $A_{\rm V}$ and the star formation rate surface density $Σ_{\rm SFR}$, as well as the UV slope $c_1$. The UV and FUV slopes ($c_1, c_3$) and the bump strength and visual attenuation ($c_4, A_{\rm V}$) exhibit robust internal correlations. Using these insights from simulations, we provide a set of scaling relations that predict a galaxy's median (averaged over line of sight) dust attenuation curve based solely on its $Σ_{\rm SFR}$ and/or $A_{\rm V}$. These predictions agree well with observed attenuation curves from the GALEX-SDSS-WISE Legacy Catalog despite minor differences in bump strength. This study delivers the most comprehensive library of synthetic attenuation curves for local galaxies, providing a foundation for physically motivated priors in SED fitting and galaxy inference studies, such as those performed as part of the Learning the Universe Collaboration.

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arXiv2025

EPOCHS IV: SED Modelling Assumptions and their impact on the Stellar Mass Function at 6.5 < z < 13.5 using PEARLS and public JWST observations

We utilize deep JWST NIRCam observations for the first direct constraints on the Galaxy Stellar Mass Function (GSMF) at $z>10$. Our EPOCHS v1 sample includes 1120 galaxy candidates at $6.5<z<13.5$ taken from a consistent reduction and analysis of publicly available deep JWST NIRCam data covering the PEARLS, CEERS, GLASS, JADES GOOD-S, NGDEEP, and SMACS0723 surveys, totalling 187 arcmin$^2$. We investigate the impact of SED fitting methods, assumed star formation histories (SFH), dust laws, and priors on galaxy masses and the resultant GSMF. Whilst our fiducial GSMF agrees with the literature at $z<13.5$, we find that the assumed SFH model has a large impact on the GSMF and stellar mass density (SMD), finding a 0.75~dex increase in the SMD at $z=10.5$ between a flexible non-parametric and standard parametric SFH. Overall, we find a flatter SMD evolution at $z \geq 9$ than some studies predict, suggesting a rapid buildup of stellar mass in the early Universe. We find no incompatibility between our results and those of standard cosmological models, as suggested previously, although the most massive galaxies may require a high star formation efficiency. We find that the "Little Red Dot" galaxies dominate the $z=7$ GSMF at high-masses, necessitating a better understanding of the relative contributions of AGN and stellar emission. We show that assuming a theoretically motivated top-heavy IMF reduces stellar mass by 0.5~dex without affecting fit quality, but our results remain consistent with existing cosmological models with a standard IMF.

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arXiv2025

Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects

It has been recently shown that a powerful way to constrain cosmological parameters from galaxy redshift surveys is to train graph neural networks to perform field-level likelihood-free inference without imposing cuts on scale. In particular, de Santi et al. (2023) developed models that could accurately infer the value of $Ω_{\rm m}$ from catalogs that only contain the positions and radial velocities of galaxies that are robust to uncertainties in astrophysics and subgrid models. However, observations are affected by many effects, including 1) masking, 2) uncertainties in peculiar velocities and radial distances, and 3) different galaxy selections. Moreover, observations only allow us to measure redshift, intertwining galaxies' radial positions and velocities. In this paper we train and test our models on galaxy catalogs, created from thousands of state-of-the-art hydrodynamic simulations run with different codes from the CAMELS project, that incorporate these observational effects. We find that, although the presence of these effects degrades the precision and accuracy of the models, and increases the fraction of catalogs where the model breaks down, the fraction of galaxy catalogs where the model performs well is over 90 %, demonstrating the potential of these models to constrain cosmological parameters even when applied to real data.

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