arXiv subjects

Vicente Rodriguez-Gomez

Publications and source records attributed to Vicente Rodriguez-Gomez.

At least 19 recordsLinked to original sources

arXiv2026

Performance of morphological classifiers for galaxy mergers compared to current machine learning methods

Aims. Non-parametric morphological statistics can be used for efficient classification of galaxy mergers. This work aims to compare the performance of morphological merger classifiers to state-of-the-art machine learning (ML) models. A secondary aim is to produce updated criteria for mergers based on non-parametric morphological statistics. Methods. The Gini coefficient (G), $M_{20}$ statistic, and concentration ($C$) were calculated for mock Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) images based on the IllustrisTNG and Horizon-AGN simulations, and observations from HSC-SSP. The IllustrisTNG images were used to find the line which best separates mergers and non-mergers in 2D morphological space with a Markov Chain Monte-Carlo (MCMC) method. Results. Based on the MCMC results, we classified galaxies with $G>(-0.267\pm0.081)M_{20}+(0.143\pm0.012)$ or $G>(0.162\pm0.048)C-(0.149\pm0.12)$ as mergers, these criteria had precisions of 69.5\% and 72.3\% respectively when applied to previously unseen IllustrisTNG mock HSC-SSP images. The precisions of the morphological classifications are consistent with state-of-the-art ML methods. The morphological classifiers were found to be effective at selecting only pre-mergers; post-merger galaxies are indistinguishable from non-mergers in terms of their $G$, $M_{20}$, and $C$ values. Morphological classifiers displayed a similar robustness to new data to ML methods up to a redshift of $\sim0.52$ and maintained robustness better than ML methods based on convolutional neural networks in the redshift range $0.52<z<1$. Conclusions. This work presents updated morphological classifiers which achieve similar precisions to ML based merger classifiers with a high robustness to new data. New morphological statistics are needed to identify the features of post-merger galaxies.

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arXiv2026

The emergence of the faint nature of Low Surface Brightness Galaxies in the IllustrisTNG simulation

We employ a simulated sample of galaxies drawn from the IllustrisTNG suite to study the emergence of the diffuse and extended nature of $\sim12,000$ low surface brightness galaxies (LSBGs) within a wide stellar mass range (${M}_{*}=10^{9}-10^{12} \rm{M}_{\odot}$). We employ merger trees to follow the evolution of their physical properties such as stellar surface density, specific angular momentum and halo spin parameter, finding that the central low density nature of LSBGs is mainly a consequence of an increase in their angular momentum and (inner) halo spin parameter. We also find that star formation histories of LSBGs are quite similar to their high surface brightness (HSBGs) counterparts, with significant differences not in the time, but in the spatial distribution in which new stars are forming. We conclude that the mechanisms that favor the emergence of the low surface brightness nature are strongly related with variations in the spin parameter of host halos and their angular momentum, deviating the stellar distribution of galaxies from their inner regions to their outskirts, leading to a decrease in their central surface brightness. Once the LSBG nature is established, galaxies are less likely to experience strong variations in their central surface densities and morphology.

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arXiv2026

The TNG50-SKIRT Atlas: Multi-wavelength nonparametric galaxy morphology

Context: Galaxy morphology is a fundamental property to describe galaxy evolution. However, the observed morphology of a particular galaxy may depend on the observed wavelength. Aims: Our aim is to investigate the wavelength dependence and the effect of dust attenuation on nonparametric morphology indicators. Methods: We use the TNG50-SKIRT Atlas, an atlas of synthetic UV to near-infrared (NIR) broadband images for a complete stellar-mass-selected sample of 1154 galaxies extracted from the TNG50 cosmological simulation at $z = 0$. For each image, we calculate four nonparametric morphology indicators using the StatMorph code. Results: We find that the known correlations between the stellar mass and the morphological parameters measured in the optical, together with the Gini-$M_{20}$, concentration-Gini, and concentration-$M_{20}$ planes, are fully consistent with observational data. However, nonparametric morphological indicators change significantly with wavelength and that this wavelength dependence is stronger for disc-dominated than for bulge-dominated galaxies. The wavelength dependence of the morphology of our simulated TNG50 galaxies is consistent with measurements of local galaxies from the SINGS survey. We demonstrate that the effect of dust attenuation on nonparametric morphology indicators is modest across the full galaxy population but can be significant for individual galaxies.

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arXiv2026

statmorph-lsst: Quantifying and correcting morphological biases in galaxy surveys

Quantitative morphology provides a key probe of galaxy evolution across cosmic time and environments. However, these metrics can be biased by changes in imaging quality - resolution and depth - either across the survey area or the sample. To prepare for the upcoming Rubin LSST data, we investigate this bias for all metrics measured by statmorph and single-component Sérsic fitting with Galfit. We find that geometrical measurements (ellipticity, axis ratio, Petrosian radius, and effective radius) are robust within 10% at most depths and resolutions. Light concentration measurements ($C$, Gini, $M_{20}$) systematically decrease with resolution, leading low-mass or high-redshift bulge-dominated sources to appear indistinguishable from disks. Sérsic index $n$, while unbiased, suffers from a 20-40% uncertainty due to degeneracies in the Sérsic fit. Disturbance measurements ($A$, $A_S$, $D$) depend on signal-to-noise and are thus affected by noise and surface-brightness dimming. We quantify this dependence for each parameter, offer empirical correction functions, and show that the evolution in $C$ observed in JWST galaxies can be explained purely by observational biases. We propose two new measurements - isophotal asymmetry $A_X$ and substructure $St$ - that aim to resolve some of these biases. Finally, we provide a Python package statmorph-lsst implementing these changes and a full dataset that enables tests of custom functions (see text for links).

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arXiv2025

AGN -- host galaxy photometric decomposition using a fast, accurate and precise deep learning approach

Identifying active galactic nuclei (AGN) is extremely important for understanding galaxy evolution and its connection with the assembly of supermassive black holes (SMBH). With the advent of deep and high angular resolution imaging surveys such as those conducted with the James Webb Space Telescope (JWST), it is now possible to identify galaxies with a central point source out to the very early Universe. In this study, we develop a fast, accurate and precise method to identify galaxies which host AGNs and recover the intrinsic AGN contribution to the observed total light ($f_{AGN}$). We trained a deep learning (DL) based method Zoobot to estimate the fractional contribution of a central point source to the total light. Our training sample comprises realistic mock JWST images of simulated galaxies from the IllustrisTNG cosmological hydrodynamical simulations. We injected different amounts of the real JWST point spread function (PSF) models to represent galaxies with different levels of $f_{AGN}$. We analyse the performance of our method and compare it with results obtained from the traditional light profile fitting tool GALFIT. We find excellent performance of our DL method in recovering the injected AGN fraction $f_{AGN}$, both in terms of precision and accuracy. The mean difference between the predicted and true injected $f_{AGN}$ is -0.002 and the overall root mean square error (RMSE) is 0.013. The relative absolute error (RAE) is 0.076 and the outlier (defined as predictions with RAE >20%) fraction is 6.5%. In comparison, using GALFIT on the same dataset, we achieve a mean difference of -0.02, RMSE of 0.12, RAE of 0.19 and outlier fraction of 19%. We applied our trained DL model to real JWST observations and found that 33% of X-ray-selected AGN and 15% of MIR-selected AGN are also identified as AGN using a cut at $f_{\rm AGN} > 0.1$.

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arXiv2025

Synthetic JWST galaxy images in the TNG50 simulation - I. Model validation and comparison to observations

We use the TNG50 cosmological simulation and three-dimensional radiative transfer post-processing to generate dust-aware synthetic observations of galaxies at $ 3 \leq z \leq 6 $ and $ \log_{10}(M_\ast/\mathrm{M}_\odot) \geq 8.5 $, tailored to match the depth and resolution of current deep JWST surveys (NGDEEP and JADES). We analyse the performance of spectral energy distribution (SED) fitting on the simulated sample, focusing on the recovery of photometric redshift and stellar mass. At $ z \leq 5 $, we find that 90 per cent of redshifts are recovered within $ \pm0.2 $, but performance declines at $ z = 6 $. Stellar masses are generally well-recovered within a factor of 2, but are systematically underestimated regardless of redshift, a trend that is more pronounced at the high-mass end $ ( \log_{10}(M_\ast/\mathrm{M}_\odot) \geq 10 ) $. In addition, we study the observer-frame colours of galaxies in this redshift range as well as the SED-inferred $UVJ$ diagram. We find that TNG50 galaxies broadly follow the tendencies marked by observations, but tend to be slightly redder at lower masses and bluer at higher masses, regardless of redshift. Finally, using a colour-based definition of quiescence, we determine the fraction of quiescent galaxies as a function of stellar mass at $ 3 \leq z \leq 6 $, which we find to be broadly consistent with observations.

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arXiv2025

Inferring the dark matter distribution of massive galaxy clusters from deep optical observations: insights from the TNG300 simulation

Extragalactic stars within galaxy clusters contribute to the intracluster light (ICL), which is thought to be a promising tracer of the underlying dark matter (DM) distribution. In this study, we employ the TNG300 simulation to investigate the prospect of recovering the dark matter distribution of galaxy clusters from deep, wide-field optical images. For this, we generate mock observations of 40 massive clusters ($M_{200}\gtrsim 10^{14.5}\,{\rm M}_\odot$) at $z=0.06$ for the $g'$ band of the Wendelstein Wide-Field Imager (WWFI), and isolate the emission from the brightest cluster galaxy (BCG) and the ICL by masking the satellite galaxies, following observational procedures. By comparing $Σ_{\rm BCG+ICL}$ profiles from these images against $Σ_{\rm DM}$ profiles for the central subhaloes, we find that $Σ_{\rm cen-DM}/Σ_{\rm BCG+ICL}$ exhibits a quasi-linear scaling relation in log space with the normalised distance $r/R_Δ$, for both $R_Δ=R_{200}$ and $R_{500}$. The scatter in the scaling is predominantly stochastic, showing a weak dependence on formation time and dynamical state. We recover the DM concentration and mass within $\approx 23$ and $\approx 15$ per cent of their true values (for $R_{200}$), respectively, and with $\approx 3$ per cent larger uncertainties for $R_{500}$. Alternatively, we find that the concentration can be estimated using the BCG+ICL fraction, the central's DM mass using the BCG+ICL flux, and the total DM mass using the bolometric flux. These results demonstrate the feasibility of deriving dark matter characteristics of galaxy clusters to be observed with facilities like the Vera C. Rubin Observatory in the near future.

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arXiv2025

Photometric analysis of the intracluster light in the TNG300 simulation and wide-field observations

We present a robust, apples-to-apples comparison between the photometric properties of the intracluster light (ICL) in the TNG300 magnetohydrodynamic cosmological simulation and those in Wendelstein Wide Field Imager (WWFI) observations. This is accomplished by generating synthetic $g'$-band images of 40 massive ($\log\left(M_{\rm 200, crit}/{\rm M}_{\odot}\right) > 14.5$) TNG300 clusters at $z \approx 0.06$, closely mimicking WWFI observations, and then performing identical photometric calculations on the synthetic and real images. Importantly, we apply the same observationally motivated satellite-masking procedure to both data-sets, which effectively removes any possible biases introduced by the halo finder. We first analyze the light distribution of the `smooth' stellar component of each cluster, composed of the brightest cluster galaxy (BCG) plus the ICL, and find that it tends to be about twice as extended in TNG300 than in observations, while also being approximately 1 $g'$ mag arcsec$^{-2}$ brighter. We then quantify $f_{\rm ICL}$, the ICL fraction relative to the BCG+ICL, by considering several ICL definitions: (i) the light dimmer than a surface brightness cut at 27 $g'$ mag arcsec$^{-2}$, (ii) the excess light over a de Vaucouleurs profile, (iii) the light beyond twice the half-light radius ($2 r_{\rm half}$), and (iv) the light beyond a fixed circular aperture of 30, 50, or 100 kpc. For most definitions, the median $f_{\rm ICL}$ is consistent between simulation and observations. However, the observations exhibit larger scatter in $f_{\rm ICL}$, which we attribute primarily to observational uncertainties in the total BCG+ICL luminosity rather than `true' cluster-to-cluster variation in the real Universe. We also find that most methods yield median $f_{\rm ICL}$ values near 0.3, which is consistent with a BCG/ICL transition radius around $2 r_{\rm half}$.

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arXiv2025

The stellar mass composition of galaxy clusters and dependencies on dark matter halo properties

We analyze 700 clusters from the TNG300 hydrodynamical simulation ($M_{200}\geq5\times10^{13} \,M_{\odot}$ at (z=0)) to examine the radial stellar mass distribution of their central objects, consisting of the brightest cluster galaxy (BCG) and the intracluster light (ICL). The BCG+ICL mass fraction weakly anticorrelates with $M_{200}$, but strongly correlates with the concentration, $c_{200}$, the assembly redshift, $z_{50}$, and the mass gap between the most massive and the fourth more massive member, $ΔM_{\rm \ast, 4th}$. We explore different aperture radii to nominally separate the ICL from the BCG and calculate ICL fractions. For $r_{\rm{ap}}=2r_{\rm half}$, where $r_{\rm half}$ is the radius containing half the BCG+ICL mass, the ICL fraction is nearly independent of $M_{200}$, $c_{200}$, and $z_{50}$ with values $M_{\ast,\rm ICL}/(M_{\ast,\rm ICL}+M_{\ast,\rm BCG})= 0.33\pm0.03$. Including the stellar mass of the satellites, the fraction $M_{\ast,\rm ICL}/(M_{\ast,\rm ICL}+M_{\ast,\rm BCG}+M_{\rm \ast,sat})$ weakly anticorrelates with $M_{200}$ and strongly correlates with $c_{200}$, $z_{50}$, and $ΔM_{\rm \ast, 4th}$, suggesting that in more concentrated/earlier assembled/more relaxed clusters more stellar mass is lost from the satellites (by tidal stripping, and mergers) in favour of the ICL and BCG. Indeed, we find that ex-situ stars dominate both in the BCG and ICL masses, with mergers contributing more to the BCG, while tidal stripping contributes more to the ICL. We find that the difference between the projected and 3D ICL fractions are only a few per cent and suggest using $2r_{\rm half}$ to separate the ICL from the BCG in observed clusters.

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arXiv2025

Classifying merger stages with adaptive deep learning and cosmological hydrodynamical simulations

Hierarchical merging of galaxies plays an important role in galaxy formation and evolution. Mergers could trigger key evolutionary phases such as starburst activities and active accretion periods onto supermassive black holes at the centres of galaxies. We aim to detect mergers and merger stages (pre- and post-mergers) across cosmic history and test whether it is better to detect mergers and their merger stages simultaneously or hierarchically. In addition, we want to test the impact of merger time relative to the coalescence of merging galaxies. First, we generated realistic mock JWST images of simulated galaxies selected from the IllustrisTNG cosmological hydrodynamical simulations. Then we trained deep learning (DL) models in the Zoobot Python package to classify galaxies into merging/non-merging galaxies and their merger stages. We used two different set-ups: (i) two-stage, in which we classify galaxies into mergers and non-mergers and then classify the mergers into pre-mergers and post-mergers, and (ii) one-stage, in which merger/non-merger and merger stages are classified simultaneously. We found that the one-stage classification set-up moderately outperforms the two-stage set-up, offering better overall accuracy and precision, particularly for the non-merger class. Pre-mergers can be classified with the highest precision in both set-ups, possibly due to the more recognisable merging features and the presence of merging companions. The image signal-to-noise ratio affects the performance of the DL classifiers, but not much after a certain threshold is crossed. Both precision and recall of the classifiers depend strongly on merger time, finding it more difficult to identify true mergers observed at stages that are more distant to coalescence. For pre-mergers, we recommend selecting mergers which will merge in the next 0.4 Gyrs, to achieve a good balance between precision and recall.

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arXiv2024

The mass and redshift dependence of halo star clustering

We adopt the two point correlation function (2PCF) as a statistical tool to quantify the spatial clustering of halo stars, for galaxy systems spanning a wide range in host halo virial mass ($11.25<\log_{10}M_{200c}/\mathrm{M}_\odot<15$) and redshifts ($0<z<1.5$) from the IllustrisTNG simulations. Consistent with a previous study \cite[][Paper I]{2024ApJ...961..223Z}, we identify clear correlations between the strength of the 2PCF signals and galaxy formation redshifts, but over a much wider mass range. We find that such correlations are slightly stronger at higher redshifts, and get weakened with the increase of host halo mass. We demonstrate that the spatial clustering of halo stars is affected by two factors: 1) the clustering gets gradually weakened as time passes (phase mixing); 2) newly accreted stars at more recent times would increase the clustering. For more massive galaxy systems, they assemble late and the newly accreted stars would increase the clustering. The late assembly of massive systems may also help to explain the weaker correlations between the 2PCF signals and the galaxy formation redshifts in massive halos, as their 2PCFs are affected more by recently accreted stars, while formation redshift characterizes mass accretion on a much longer timescale. We find that the orbits of satellite galaxies in more massive halos maintain larger radial anisotropy, reflecting the more active accretion state of their hosts while also contributing to their stronger mass loss rates.

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arXiv2024

RMS asymmetry: a robust metric of galaxy shapes in images with varied depth and resolution

Structural disturbances, such as galaxy mergers or instabilities, are key candidates for driving galaxy evolution, so it is important to detect and quantify galaxies hosting these disturbances spanning a range of masses, environments, and cosmic times. Traditionally, this is done by quantifying the asymmetry of a galaxy as part of the concentration-asymmetry-smoothness system, $A_{\rm{CAS}}$, and selecting galaxies above a certain threshold as merger candidates. However, in this work, we show that $A_{\rm{CAS}}$, is extremely dependent on imaging properties -- both resolution and depth -- and thus defining a single $A_{\rm{CAS}}$ threshold is impossible. We analyze an alternative root-mean-squared asymmetry, $A_{\rm{RMS}}$, and show that it is independent of noise down to the average SNR per pixel of 1. However, both metrics depend on the resolution. We argue that asymmetry is, by design, always a scale-dependent measurement, and it is essential to define an asymmetry at a given physical resolution, where the limit should be defined by the size of the smallest features one wishes to detect. We measure asymmetry of a set of $z\approx0.1$ galaxies observed with HST, HSC, and SDSS, and show that after matching the resolution of all images to 200 pc, we are able to obtain consistent $A_{\rm{RMS, 200pc}}$ measurements with all three instruments despite the vast differences in the original resolution or depth. We recommend that future studies use $A_{\rm{RMS, x pc}}$ measurement when evaluating asymmetry, where $x$ is defined by the physical size of the features of interest, and is kept consistent across the dataset, especially when the redshift or image properties of galaxies in the dataset vary.

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arXiv2024

A Physically Motivated Framework to Compare Merger Timescales of Isolated Low- and High-Mass Galaxy Pairs Across Cosmic Time

The merger timescales of isolated low-mass pairs ($\rm 10^8<M_*<5\times10^9\,M_{\odot}$) on cosmologically motivated orbits have not yet been studied in detail, though isolated high-mass pairs ($\rm 5\times10^9<M_*<10^{11}\,M_{\odot}$) have been studied extensively. It is common to apply the same separation criteria and expected merger timescales of high-mass pairs to low-mass systems, however, it is unclear if their merger timescales are similar, or if they evolve similarly with redshift. We use the Illustris TNG100 simulation to quantify the merger timescales of isolated low-mass and high-mass major pairs as a function of cosmic time, and explore how different selection criteria impact the mass and redshift dependence of merger timescales. In particular, we present a physically-motivated framework for selecting pairs via a scaled separation criteria, wherein pair separations are scaled by the virial radius of the primary's FoF group halo ($r_{\mathrm{sep}}< 1 R_{vir}$). Applying these scaled separation criteria yields equivalent merger timescales for both mass scales at all redshifts. Alternatively, static physical separation selections applied equivalently to all galaxy pairs at all redshifts leads to a difference in merger rates of up to $\rm \sim 1\, Gyr$ between low- and high-mass pairs, particularly for $\rm r_{sep}<150\, kpc$. As a result, applying the same merger timescales to physical separation-selected pairs will lead to a bias that systematically over-predicts low-mass galaxy merger rates.

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arXiv2024

Environmental effects on Low Surface Brightness Galaxies in the IllustrisTNG simulation

Employing the TNG100 run of the IllustrisTNG project, we characterize the environment of Low Surface Brightness Galaxies (LSBGs) across varying scales, from their associated dark matter halos to their distribution within the broader cosmic structure. We find no significant differences in the halo concentration index $c_{200}$ between LSBGs and their High Surface Brightness (HSBGs) counterparts, with LSBGs residing in halos with higher spin parameter $λ$ and slightly more spherical shapes than HSBGs. LSBGs show a stronger alignment between the dark and stellar angular momentum vectors than their high surface brightness counterparts. The relative abundance of LSBGs within groups and clusters displays a central deficit, hinting at potential destruction upon reaching these core regions. Studying the density field, we find a preference for rotation-dominated LSBGs to reside in low-density environments, while dispersion-dominated LSBGs thrive in high-density regions where galaxy interactions govern their evolution, an observation corroborated by our analysis of the two-point correlation function $ξ(r)$. Our examination of the cosmic web reveals no significant differences in the distance to the closest large-scale structure, barring a few exceptions. This suggests a limited impact of large-scale spatial distribution on mechanisms driving LSBG evolution. All together, we conclude that the halo vicinity and local environment at the scale of galaxy clusters, where mechanisms such as galaxy mergers and tidal stripping, as well as stellar and gas accretion take place, is the most likely environment that favour the emergence of LSBGs with different morphologies, mostly driven by the presence or absence of important local interaction phenomena.

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arXiv2024

How does the velocity anisotropy of halo stars, dark matter and satellite galaxies depend on host halo properties?

We investigate the mass ($M_{200}$) and concentration ($c_{200}$) dependencies of the velocity anisotropy ($β$) profiles for different components in the dark matter halo, including halo stars, dark matter and subhalos, using systems from the IllustrisTNG simulations. Beyond a critical radius, $β$ becomes more radial with the increase of $M_{200}$, reflecting more prominent radial accretion around massive halos. The critical radius is $r\sim r_s$, $0.3~r_s$ and $r_s$ for halo stars, dark matter and subhalos, with $r_s$ the scale radius of host halos. This dependence on $M_{200}$ is the strongest for subhalos, and the weakest for halo stars. In central regions, $β$ of halo stars and dark matter particles gets more isotropic with the increase of $M_{200}$ in TNG300 due to baryons. By contrast, $β$ of dark matter from the dark matter only TNG300-Dark run shows much weaker dependence on $M_{200}$ within $r_s$. Dark matter in TNG300 is slightly more isotropic than in TNG300-Dark at $0.2~r_s r_s$ as $β_\mathrm{star}-β_\mathrm{DM}=(-0.028 \pm 0.008)\log_{10}M_{200}/M_\odot + (0.690\pm0.010)$.

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arXiv2024

ERGO-ML: Comparing IllustrisTNG and HSC galaxy images via contrastive learning

Modern cosmological hydrodynamical galaxy simulations provide tens of thousands of reasonably realistic synthetic galaxies across cosmic time. However, quantitatively assessing the level of realism of simulated universes in comparison to the real one is difficult. In this paper of the ERGO-ML series (Extracting Reality from Galaxy Observables with Machine Learning), we utilize contrastive learning to directly compare a large sample of simulated and observed galaxies based on their stellar-light images. This eliminates the need to specify summary statistics and allows to exploit the whole information content of the observations. We produce survey-realistic galaxy mock datasets resembling real Hyper Suprime-Cam (HSC) observations using the cosmological simulations TNG50 and TNG100. Our focus is on galaxies with stellar masses between $10^9$ and $10^{12} M_\odot$ at $z=0.1-0.4$. This allows us to evaluate the realism of the simulated TNG galaxies in comparison to actual HSC observations. We apply the self-supervised contrastive learning method NNCLR to the images from both simulated and observed datasets (g, r, i - bands). This results in a 256-dimensional representation space, encoding all relevant observable galaxy properties. Firstly, this allows us to identify simulated galaxies that closely resemble real ones by seeking similar images in this multi-dimensional space. Even more powerful, we quantify the alignment between the representations of these two image sets, finding that the majority ($\gtrsim 70$ per cent) of the TNG galaxies align well with observed HSC images. However, a subset of simulated galaxies with larger sizes, steeper Sersic profiles, smaller Sersic ellipticities, and larger asymmetries appears unrealistic. We also demonstrate the utility of our derived image representations by inferring properties of real HSC galaxies using simulated TNG galaxies as the ground truth.

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arXiv2024

A physically motivated framework to compare pair fractions of isolated low and high mass galaxies across cosmic time

Low mass galaxy pair fractions are understudied, and it is unclear whether low mass pair fractions evolve in the same way as more massive systems over cosmic time. In the era of JWST, Roman, and Rubin, selecting galaxy pairs in a self-consistent way will be critical to connect observed pair fractions to cosmological merger rates across all mass scales and redshifts. Utilizing the Illustris TNG100 simulation, we create a sample of physically associated low mass ($\rm 10^8 1$. At $z=0$, the low mass major (1:4 mass ratio) pair fraction is 4$\times$ lower than high mass pairs, consistent with findings for cosmological merger rates. We show that separation limits that vary with the mass and redshift of the system, such as scaling by the virial radius of the host halo ($r_{\mathrm{sep}}< 1 R_{\rm vir}$), are critical for recovering pair fraction differences between low mass and high mass systems. Alternatively, static physical separation limits applied equivalently to all galaxy pairs do not recover the differences between low and high mass pair fractions, even up to separations of $300$ kpc. Finally, we place isolated mass-analogs of Local Group galaxy pairs, i.e., Milky Way (MW)--M31, MW--LMC, LMC--SMC, in a cosmological context, showing that isolated analogs of LMC--SMC-mass pairs and low-separation ($<50$ kpc) MW--LMC-mass pairs are $2-3\times$ more common at $z\gtrsim2-3$.

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arXiv2024

The TNG50-SKIRT Atlas: post-processing methodology and first data release

Galaxy morphology is a powerful diagnostic to assess the realism of cosmological hydrodynamical simulations. Determining the morphology of simulated galaxies requires the generation of synthetic images through 3D radiative transfer post-processing that properly accounts for different stellar populations and interstellar dust attenuation. We use the SKIRT code to generate the TNG50-SKIRT Atlas, a synthetic UV to near-infrared broadband image atlas for a complete stellar-mass selected sample of 1154 galaxies extracted from the TNG50 cosmological simulation at $z=0$. The images have a high spatial resolution (100 pc) and a wide field of view (160 kpc). In addition to the dust-obscured images, we also release dust-free images and physical parameter property maps with matching characteristics. As a sanity check and preview application we discuss the UVJ diagram of the galaxy sample. We investigate the effect of dust attenuation on the UVJ diagram and find that it affects both the star-forming and the quiescent galaxy populations. The quiescent galaxy region is polluted by younger and star-forming highly inclined galaxies, while dust attenuation induces a separation in inclination of the star-forming galaxy population, with low-inclination galaxies remaining at the blue side of the diagram and high-inclination galaxies systematically moving towards the red side. This image atlas can be used for a variety of other applications, including galaxy morphology studies and the investigation of local scaling relations. We publicly release the images and parameter maps, and we invite the community to use them.

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