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The evolution of star-forming galaxies at high redshifts is very sensitive to the strength and nature of stellar feedback. Using two sets of cosmological, zoom-in simulations from the VELA suite, we compare the effects of two different models of feedback: with and without kinetic feedback from the expansion of supernovae shells and stellar winds. At a fixed halo mass and redshift, the stellar mass is reduced by a factor of 1-3 in the models with stronger feedback, so the stellar-mass-halo-mass relation is in better agreement with abundance matching results. On the other hand, the three-dimensional shape of low-mass galaxies is elongated along a major axis in both models. At a fixed stellar mass, Ms 300 Myr), quenched, stellar (or gas-poor) clumps is absent in the model with strong feedback. On the other hand, giant star-forming clumps with intermediate ages (age_c= 100 - 300 Myr) can survive for several disc dynamical times, independently of feedback strength. The evolution through compaction followed by quenching in the plane of central surface density and specific star-formation rate is similar under the two feedback models., 14 pages, 12 figures, accepted version at MNRAS

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., 17 pages, 6 figures, 3 tables, ApJL in press. Summary of changes from original submission: Improvements in astrometry generated a weak detection in F150W that reduces the photo-z to 11.8 but does not increase the likelihood of lower-z solutions. A full discussion of changes from the original version is available at: https://web.corral.tacc.utexas.edu/ceersdata/papers/Maisie_update.pdf

The 3D-Drift And SHift (3D-DASH) program is a \textit{Hubble Space Telescope} WFC3 F160W imaging and G141 grism survey of the equatorial COSMOS field. 3D-DASH extends the legacy of HST near-infrared imaging and spectroscopy to degree-scale swaths of the sky, enabling the identification and study of distant galaxies ($z>2$) that are rare or in short-lived phases of galaxy evolution at rest-frame optical wavelengths. Furthermore, when combined with existing ACS/F814W imaging, the program facilitates spatially-resolved studies of the stellar populations and dust content of intermediate-redshift ($0.5, Comment: The 3D-DASH mosaic, PSF and cutout generator tool, and the image explorer are available at archive.stsci.edu/hlsp/3d-dash and at www.lamiyamowla.com/3d-dash. Accepted for publication in Astrophysical Journal. arXiv admin note: text overlap with arXiv:1808.04379

A significant fraction of high redshift star-forming disc galaxies are known to host giant clumps, whose nature and role in galaxy evolution are yet to be understood. In this work we first present a new method based on neural networks to detect clumps in galaxy images. We use this method to detect clumps in the rest-frame optical and UV images of a complete sample of $\sim1500$ star forming galaxies at $1, Comment: Accepted for publication in MNRAS - This is the final version

We present a sample of 24 local star-forming galaxies observed with broadband and narrowband photometry from the Hubble Space Telescope (HST) that are part of the Great Observatories All-sky Luminous Infrared Galaxies Survey of local luminous and ultraluminous infrared galaxies. With narrowband filters around the emission lines Hα (and [N ii]) and Paβ, we obtain robust estimates of the dust attenuation affecting the gas in each galaxy, probing higher attenuation than can be traced by the optical Balmer decrement Hα/Hβ alone by a factor of >1 mag. We also infer the dust attenuation toward the stars via a spatially resolved spectral energy distribution fitting procedure that uses all available HST imaging filters. We use various indicators to obtain the star formation rate (SFR) per spatial bin and find that Paβ traces star-forming regions where the Hα and the optical stellar continuum are heavily obscured. The dust-corrected Paβ SFR recovers the 24 μm inferred SFR with a ratio of −0.14 ± 0.32 dex and the SFR inferred from the 8 to 1000 μm infrared luminosity at −0.04 ± 0.23 dex. Both in a spatially resolved and integrated sense, rest-frame near-infrared recombination lines can paint a more comprehensive picture of star formation across cosmic time, particularly with upcoming JWST observations of Paschen-series line emission in galaxies as early as the epoch of reionization.

We present and analyze a series of synthetic galaxy survey fields based on the IllustrisTNG Simulation suite. With the Illustris public data release and JupyterLab service, we generated a set of twelve lightcone catalogs covering areas from 5 to 365 square arcminutes, similar to several JWST Cycle 1 programs, including JADES, CEERS, PRIMER, and NGDEEP. From these catalogs, we queried the public API to generate simple mock images in a series of broadband filters used by JWST-NIRCam and the Hubble Space Telescope cameras. This procedure generates wide-area simulated mosaic images that can support investigating the predicted evolution of galaxies alongside real data. Using these mocks, we demonstrate a few simple science cases, including morphological evolution and close pair selection. We publicly release the catalogs and mock images through MAST, along with the code used to generate these projects, so that the astrophysics community can make use of these products in their scientific analyses of JWST deep field observations., Comment: Accepted to MNRAS

Using the TNG50 cosmological simulation and observations from the Kilo-Degree Survey (KiDS), we investigate the connection between galaxy mergers and optical morphology in the local Universe over a wide range of galaxy stellar masses ($8.5\leqslant\log(M_\ast/\text{M}_\odot)\leqslant11$). To this end, we have generated over 16,000 synthetic images of TNG50 galaxies designed to match KiDS observations, including the effects of dust attenuation and scattering, and used the $\mathrm{\mathtt{statmorph}}$ code to measure various image-based morphological diagnostics in the $r$-band for both data sets. Such measurements include the Gini-$M_{20}$ and concentration-asymmetry-smoothness statistics. Overall, we find good agreement between the optical morphologies of TNG50 and KiDS galaxies, although the former are slightly more concentrated and asymmetric than their observational counterparts. Afterwards, we trained a random forest classifier to identify merging galaxies in the simulation (including major and minor mergers) using the morphological diagnostics as the model features, along with merger statistics from the merger trees as the ground truth. We find that the asymmetry statistic exhibits the highest feature importance of all the morphological parameters considered. Thus, the performance of our algorithm is comparable to that of the more traditional method of selecting highly asymmetric galaxies. Finally, using our trained model, we estimate the galaxy merger fraction in both our synthetic and observational galaxy samples, finding in both cases that the galaxy merger fraction increases steadily as a function of stellar mass., Comment: 18 pages, 12 figures. Accepted for publication in MNRAS

We use the Illustris-1 simulation to explore the capabilities of the $\textit{Hubble}$ and $\textit{James Webb Space Telescope}$ data to analyze the stellar populations in high-redshift galaxies, taking advantage of the combined depth, spatial resolution, and wavelength coverage. For that purpose, we use simulated broad-band ACS, WFC3 and NIRCam data and 2-dimensional stellar population synthesis (2D-SPS) to derive the integrated star formation history (SFH) of massive (M$_{\ast}>10^{10}\,$M$_{\odot}$) simulated galaxies at $110^{11}\,$M$_{\odot}$ galaxy. In particular, we explore the potential of HST and JWST datasets reaching a depth similar to those of the CANDELS and ongoing CEERS observations, respectively, and concentrate on determining the capabilities of this dataset for characterizing the first episodes in the SFH of local M$_{\ast}>10^{11}\,$M$_{\odot}$ galaxies by studying their progenitors at $z>1$. The 2D-SPS method presented in this paper has been calibrated to robustly recover the cosmic times when the first star formation episodes occurred in massive galaxies, i.e., the first stages in their integrated SFHs. In particular, we discuss the times when the first 1% to 50% of their total stellar mass formed in the simulation. We demonstrate that we can recover these ages with typical median systematic offset of less than 5% and scatter around 20%-30%. According to our measurements on Illustris data, we are able to recover that local M$_{\ast}>10^{11}\,$M$_{\odot}$ galaxies would have started their formation by $z=16$, forming the first 5% of their stellar mass present at $z \sim 1$ by $z=4.5$, 10% by $z=3.7$, and 25% by $z=2.7$., Comment: 28 pages, 13 figures, 4 tables. ApJ in press. Summary of changes from original submission: the major change is that we now include in Sec. 6 the comparison of the results obtained for our sample of massive 1 < z < 4 progenitors with those obtained by considering all massive galaxies at 1 < z < 4 in the simulated images. Several figures and sections have been updated

We present a new measurement of the gas-phase mass-metallicity relation (MZR), and its dependence on star formation rates (SFRs) at 1.3 < z < 2.3. Our sample comprises 1056 galaxies with a mean redshift of z = 1.9, identified from the Hubble Space Telescope Wide Field Camera 3 (WFC3) grism spectroscopy in the Cosmic Assembly Near-Infrared Deep Extragalactic Survey (CANDELS) and the WFC3 Infrared Spectroscopic Parallel Survey (WISP). This sample is four times larger than previous metallicity surveys at z ~ 2, and reaches an order of magnitude lower in stellar mass (10^8 M_sun). Using stacked spectra, we find that the MZR evolves by 0.3 dex relative to z ~ 0.1. Additionally, we identify a subset of 49 galaxies with high signal-to-noise (SNR) spectra and redshifts between 1.3 < z < 1.5, where H-alpha emission is observed along with [OIII] and [OII]. With accurate measurements of SFR in these objects, we confirm the existence of a mass-metallicity-SFR (M-Z-SFR) relation at high redshifts. These galaxies show systematic differences from the local M-Z-SFR relation, which vary depending on the adopted measurement of the local relation. However, it remains difficult to ascertain whether these differences could be due to redshift evolution, as the local M-Z-SFR relation is poorly constrained at the masses and SFRs of our sample. Lastly, we reproduced our sample selection in the IllustrisTNG hydrodynamical simulation, demonstrating that our line flux limit lowers the normalization of the simulated MZR by 0.2 dex. We show that the M-Z-SFR relation in IllustrisTNG has an SFR dependence that is too steep by a factor of around three., Accepted for publication in ApJ; 41 pages, 20 figures

We present the results from a new search for candidate galaxies at z ~ 8.5-11 discovered over the 850 arcmin^2 area probed by the Cosmic Assembly Near-Infrared Deep Extragalactic Legacy Survey (CANDELS). We use a photometric redshift selection including both Hubble and Spitzer Space Telescope photometry to robustly identify galaxies in this epoch at F160W < 26.6. We use a detailed vetting procedure, including screening for persistence, stellar contamination, inclusion of ground-based imaging, and followup space-based imaging to build a robust sample of 11 candidate galaxies, three presented here for the first time. The inclusion of Spitzer/IRAC photometry in the selection process reduces contamination, and yields more robust redshift estimates than Hubble alone. We constrain the evolution of the rest-frame ultraviolet luminosity function via a new method of calculating the observed number densities without choosing a prior magnitude bin size. We find that the abundance at our brightest probed luminosities (M_UV=-22.3) is consistent with predictions from simulations which assume that galaxies in this epoch have gas depletion times at least as short as those in nearby starburst galaxies. Due to large Poisson and cosmic variance uncertainties we cannot conclusively rule out either a smooth evolution of the luminosity function continued from z=4-8, or an accelerate decline at z > 8. We calculate that the presence of seven galaxies in a single field (EGS) is an outlier at the 2-sigma significance level, implying the discovery of a significant overdensity. These scenarios will be imminently testable to high confidence within the first year of observations of the James Webb Space Telescope., 47 figures, 25 pages, 10 tables, Accepted to the Astrophysical Journal. Photometric catalogs available via email request to lead author

How do galaxies transform from blue, star-forming spirals to red, quiescent early-type galaxies? To answer this question, we analyzed a set of 26 gas-rich, shocked post-starburst galaxies with Hubble Space Telescope (HST) imaging in B, I, and H bands, and Sloan Digital Sky Survey (SDSS) i-band imaging of similar depth but lower resolution. We found that post-starbursts in our sample have intermediate morphologies between disk- and bulge-dominated (S\'ersic n$=1.7^{+0.3}_{-0.0}$) and have red bulges, likely due to dust obscuration in the cores. Majority of galaxies in our sample are more morphologically disturbed than regular galaxies (88%, corresponding to >3$\sigma$ significance) when observed with HST, with asymmetry and S\'ersic residual flux fraction being the most successful measures of disturbance. Most disturbances are undetected at the lower resolution of SDSS imaging. Although ~27% galaxies are clear merger remnants, we found that disturbances in another ~30% of the sample are internal, caused by small-scale perturbations or dust substructures rather than tidal features, and require high-resolution imaging to detect. We found a 2.8$\sigma$ evidence that asymmetry features fade on timescales ~200 Myr, and may vanish entirely after ~750 Myr, so we do not rule out a possible merger origin of all post-starbursts given that asymmetric features may have already faded. This work highlights the importance of small-scale disturbances, detected only in high-resolution imaging, in understanding structural evolution of transitioning galaxies., Comment: 31 pages, 19 figures, 2 figure sets, 1 machine-readable table; accepted to ApJ

In astronomy, neural networks are often trained on simulation data with the prospect of being used on telescope observations. Unfortunately, training a model on simulation data and then applying it to instrument data leads to a substantial and potentially even detrimental decrease in model accuracy on the new target dataset. Simulated and instrument data represent different data domains, and for an algorithm to work in both, domain-invariant learning is necessary. Here we employ domain adaptation techniques$-$ Maximum Mean Discrepancy (MMD) as an additional transfer loss and Domain Adversarial Neural Networks (DANNs)$-$ and demonstrate their viability to extract domain-invariant features within the astronomical context of classifying merging and non-merging galaxies. Additionally, we explore the use of Fisher loss and entropy minimization to enforce better in-domain class discriminability. We show that the addition of each domain adaptation technique improves the performance of a classifier when compared to conventional deep learning algorithms. We demonstrate this on two examples: between two Illustris-1 simulated datasets of distant merging galaxies, and between Illustris-1 simulated data of nearby merging galaxies and observed data from the Sloan Digital Sky Survey. The use of domain adaptation techniques in our experiments leads to an increase of target domain classification accuracy of up to ${\sim}20\%$. With further development, these techniques will allow astronomers to successfully implement neural network models trained on simulation data to efficiently detect and study astrophysical objects in current and future large-scale astronomical surveys., Submitted to MNRAS; 21 pages, 9 figures, 9 tables

We present Powderday, a flexible, fast, open-source dust radiative transfer package designed to interface with galaxy formation simulations. Powderday builds on FSPS population synthesis models, Hyperion dust radiative transfer, and employs yt to interface between different software packages. We include our stellar population synthesis modeling on the fly, which allows for significant run-time flexibility in the assumed stellar physics. We include a model for nebular line emission that can employ either precomputed Cloudy lookup tables (for efficiency), or direct photoionization calculations for all young stars (for flexibility). The dust content follows either observationally-motivated prescriptions, direct modeling from galaxy formation simulations, or a novel approach that includes the dust content via learning-based algorithms from the SIMBA cosmological galaxy formation simulation. AGN can additionally be included via a range of prescriptions. The output of these models are broadband SEDs, as well as filter-convolved images. Powderday is designed to eliminate last-mile efforts by researchers that employ different hydrodynamic galaxy formation models, and seamlessly interfaces with GIZMO, AREPO, GASOLINE, CHANGA, and ENZO. We demonstrate the capabilities of the code via three applications: a model for the star formation rate (SFR) - infrared luminosity relation in galaxies (including the impact of AGN); the impact of circumstellar dust around AGB stars on the mid-infrared emission from galaxy SEDs; and the impact of galaxy inclination angle on dust attenuation laws., Submitted to ApJ; comments welcome

We use deep learning to explore the nature of observed giant clumps in high-redshift disc galaxies, based on their identification and classification in cosmological simulations. Simulated clumps are detected using the 3D gas and stellar densities in the VELA zoom-in cosmological simulation suite, with $\sim \!\! 25\ \!\rm{pc}$ maximum resolution, targeting main sequence galaxies at $1\!, Comment: 17 pages, 13 figures. Accepted for publication in MNRAS

Galaxy interactions and mergers are thought to play an important role in the evolution of galaxies. Studies in the nearby universe show a higher fraction of active galactic nuclei (AGNs) in interacting and merging galaxies than in their isolated counterparts, indicating that such interactions are important contributors to black hole growth. To investigate the evolution of this role at higher redshifts, we have compiled the largest known sample of major spectroscopic galaxy pairs (2381 with ΔV < 5000 km s-1) at 0.5 < z < 3.0 from observations in the COSMOS and CANDELS surveys. We identify X-ray and IR AGNs among this kinematic pair sample, a visually identified sample of mergers and interactions, and a mass-, redshift-, and environment-matched control sample for each in order to calculate AGN fractions and the level of AGN enhancement as a function of relative velocity, redshift, and X-ray luminosity. While we see a slight increase in AGN fraction with decreasing projected separation, overall, we find no significant enhancement relative to the control sample at any separation. In the closest projected separation bin (< 25 kpc, ΔV < 1000 km s-1), we find enhancements of a factor of ${0.94}_{-0.16}^{+0.21}$ and ${1.00}_{-0.31}^{+0.58}$ for X-ray and IR-selected AGNs, respectively. While we conclude that galaxy interactions do not significantly enhance AGN activity on average over 0.5 < z < 3.0 at these separations, given the errors and the small sample size at the closest projected separations, our results would be consistent with the presence of low-level AGN enhancement....

We study ram pressure stripping in simulated Milky Way-like halos at z>=2 from the Figuring Out Gas & Galaxies In Enzo (FOGGIE) project. These simulations reach exquisite resolution in their circumgalactic medium (CGM) gas owing to FOGGIE's novel refinement scheme. The CGM of each halo spans a wide dynamic range in density and velocity over its volume---roughly 6 dex and 1000 km/s, respectively---translating into a 5 dex range in ram pressure imparted to interacting satellites. The ram pressure profiles of the simulated CGM are highly stochastic, owing to kpc-scale variations of the density and velocity fields of the CGM gas. As a result, the efficacy of ram pressure stripping depends strongly on the specific path a satellite takes through the CGM. The ram-pressure history of a single satellite is generally unpredictable and not well correlated with its approach vector with respect to the host galaxy. The cumulative impact of ram pressure on the simulated satellites is dominated by only a few short strong impulses---on average, 90% of the total surface momentum gained through ram pressure is imparted in 20% or less of the total orbital time. These results reveal an erratic mode of ram pressure stripping in Milky-Way like halos at high redshift---one that is not captured by a smooth spherically-averaged model of the circumgalactic medium., 18 pages, 10 figures. Submitted to ApJ

We have generated synthetic images of $\sim$27,000 galaxies from the IllustrisTNG and the original Illustris hydrodynamic cosmological simulations, designed to match Pan-STARRS observations of $\log_{10}(M_{\ast}/{\rm M}_{\odot}) \approx 9.8$-$11.3$ galaxies at $z \approx 0.05$. Most of our synthetic images were created with the SKIRT radiative transfer code, including the effects of dust attenuation and scattering, and performing the radiative transfer directly on the Voronoi mesh used by the simulations themselves. We have analysed both our synthetic and real Pan-STARRS images with the newly developed $\tt{statmorph}$ code, which calculates non-parametric morphological diagnostics -- including the Gini-$M_{20}$ and concentration-asymmetry-smoothness (CAS) statistics -- and performs two-dimensional S\'ersic fits. Overall, we find that the optical morphologies of IllustrisTNG galaxies are in good agreement with observations, and represent a substantial improvement compared to the original Illustris simulation. In particular, the locus of the Gini-$M_{20}$ diagram is consistent with that inferred from observations, while the median trends with stellar mass of all the morphological, size and shape parameters considered in this work lie within the $\sim$1$\sigma$ scatter of the observational trends. However, the IllustrisTNG model has some difficulty with more stringent tests, such as producing a strong morphology-colour relation. This results in a somewhat higher fraction of red discs and blue spheroids compared to observations. Similarly, the morphology-size relation is problematic: while observations show that discs tend to be larger than spheroids at a fixed stellar mass, such a trend is not present in IllustrisTNG., Comment: 21 pages, 11 figures. Published in MNRAS. Code available at https://statmorph.readthedocs.io

Galaxy mergers are expected to have a significant role in the mass assembly of galaxies in the early Universe, but there are very few observational constraints on the merger history of galaxies at $z>2$. We present the first study of galaxy major mergers (mass ratios $>$ 1:4) in mass-selected samples out to $z\approx6$. Using all five fields of the HST/CANDELS survey and a probabilistic pair count methodology that incorporates the full photometric redshift posteriors and corrections for stellar mass completeness, we measure galaxy pair-counts for projected separations between 5 and 30 kpc in stellar mass selected samples at $9.7 < \log_{10}(\rm{M}_{*}/\rm{M}_{\odot}) < 10.3$ and $\log_{10}(\rm{M}_{*}/\rm{M}_{\odot}) > 10.3$. We find that the major merger pair fraction rises with redshift to $z\approx6$ proportional to $(1+z)^{m}$, with $m = 0.8\pm0.2$ ($m = 1.8\pm0.2$) for $\log_{10}(\rm{M}_{*} / \rm{M}_{\odot}) > 10.3$ ($9.7 < \log_{10}(\rm{M}_{*}/\rm{M}_{\odot}) < 10.3$). Investigating the pair fraction as a function of mass ratio between 1:20 and 1:1, we find no evidence for a strong evolution in the relative numbers of minor to major mergers out to $z 10.3$. The corresponding co-moving major merger rate density remains roughly constant during this time, with rates of $��\approx 10^{-4}$ Gyr$^{-1}$ Mpc$^{-3}$. Based on the observed merger rates per galaxy, we infer specific mass accretion rates from major mergers that are comparable to the specific star-formation rates for the same mass galaxies at $z>3$ - observational evidence that mergers are as important a mechanism for building up mass at high redshift as in-situ star-formation., 36 pages, 17 figures. Accepted for publication in ApJ

The majority of massive star-forming galaxies at $z\sim2$ have velocity gradients suggestive of rotation, in addition to large amounts of disordered motions. In this paper, we demonstrate that it is challenging to distinguish the regular rotation of a disk galaxy from the orbital motions of merging galaxies with seeing-limited data. However, the merger fractions at $z\sim2$ are likely too low for this to have a large effect on measurements of disk fractions. To determine how often mergers pass for disks, we look to galaxy formation simulations. We analyze $\sim$24000 synthetic images and kinematic maps of 31 high-resolution simulations of isolated galaxies and mergers at $z\sim2$. We determine if the synthetic observations pass criteria commonly used to identify disk galaxies, and whether the results are consistent with their intrinsic dynamical states. Galaxies that are intrinsically mergers pass the disk criteria for anywhere from 0 to 100$\%$ of sightlines. The exact percentage depends strongly on the specific disk criteria adopted, and weakly on the separation of the merging galaxies. Therefore, one cannot tell with certainty whether observations of an individual galaxy indicate a merger or a disk. To estimate the fraction of mergers passing as disks in current kinematics samples, we combine the probability that a merger will pass as a disk with theoretical merger fractions from a cosmological simulation. Taking the latter at face-value, the observed disk fractions are overestimated by small amounts: at most by $5\%$ at high stellar mass ($10^{10-11}$ M$_{\odot}$) and $15\%$ at low stellar mass ($10^{9-10}$ M$_{\odot}$)., 15 pages, 10 figures, accepted for publication in ApJ

The role of major mergers in galaxy evolution remains a key open question. Existing empirical merger identification methods use non-parametric and subjective visual classifications which can pose systematic challenges to constraining merger histories. As a first step towards overcoming these challenges, we develop and share publicly a new Python-based software tool that identifies and extracts the flux-wise and area-wise significant contiguous regions from the model-subtracted "residual" images produced by popular parametric light-profile fitting tools (e.g., GALFIT). Using Hubble Space Telescope ($HST$) $H$-band single-S\'ersic residual images of $17$ CANDELS galaxies, we demonstrate the tool's ability to measure the surface brightness and improve the qualitative identification of a variety of common residual features (disk structures, spiral substructures, plausible tidal features, and strong gravitational arcs). We test our method on synthetic $HST$ observations of a $z\sim 1.5$ major merger from the VELA hydrodynamic simulations. We extract $H$-band residual features corresponding to the birth, growth, and fading of tidal features during different stages and viewing orientations at CANDELS depths and resolution. We find that the extracted features at shallow depths have noisy visual appearance and are susceptible to viewing angle effects. For a VELA $z\sim 3$ major merger, we find that James Webb Space Telescope NIRCam observations can probe high-redshift tidal features with considerable advantage over existing $HST$ capabilities. Further quantitative analysis of plausible tidal features extracted with our new software hold promise for the robust identification of hallmark merger signatures and corresponding improvements to merger rate constraints., Comment: 18 pages, 11 Figures, and accepted for publication in MNRAS. The data products discussed in this paper along with the software are publicly available at https://github.com/AgentM-GEG/residual_feature_extraction

We analyze the optical morphologies of galaxies in the IllustrisTNG simulation at $z\sim0$ with a Convolutional Neural Network trained on visual morphologies in the Sloan Digital Sky Survey. We generate mock SDSS images of a mass complete sample of $\sim12,000$ galaxies in the simulation using the radiative transfer code SKIRT and include PSF and noise to match the SDSS r-band properties. The images are then processed through the exact same neural network used to estimate SDSS morphologies to classify simulated galaxies in four morphological classes (E, S0/a, Sab, Scd). The CNN model finds that $\sim95\%$ of the simulated galaxies fall in one the four main classes with high confidence. The mass-size relations of the simulated galaxies divided by morphological type also reproduce well the slope and the normalization of observed relations which confirms the realism of optical morphologies in the TNG suite. However, the Stellar Mass Functions decomposed into different morphologies still show significant discrepancies with observations both at the low and high mass end. We find that the high mass end of the SMF is dominated in TNG by massive disk galaxies while early-type galaxies dominate in the observations according to the CNN classifications. The present work highlights the importance of detailed comparisons between observations and simulations in comparable conditions., Comment: submitted to MNRAS, comments welcome

Expanding on the work of Snyder et al., we present merger pair analysis of mock surveys from the IllustrisTNG suite of 3D cosmological simulations. Our results, shown in the context of previous work with Illustris-1, are consistent with a flattening of the pair fraction curve at a redshift of z = 2.

Important but rare and subtle processes driving galaxy morphology and star-formation may be missed by traditional spiral, elliptical, irregular or S\'ersic bulge/disk classifications. To overcome this limitation, we use a principal component analysis of non-parametric morphological indicators (concentration, asymmetry, Gini coefficient, $M_{20}$, multi-mode, intensity and deviation) measured at rest-frame $B$-band (corresponding to HST/WFC3 F125W at 1.4 $< z 10^{10} M_{\odot}$) galaxy morphologies. Principal component analysis (PCA) quantifies the correlations between these morphological indicators and determines the relative importance of each. The first three principal components (PCs) capture $\sim$75 per cent of the variance inherent to our sample. We interpret the first principal component (PC) as bulge strength, the second PC as dominated by concentration and the third PC as dominated by asymmetry. Both PC1 and PC2 correlate with the visual appearance of a central bulge and predict galaxy quiescence. PC1 is a better predictor of quenching than stellar mass, as as good as other structural indicators (S\'ersic-n or compactness). We divide the PCA results into groups using an agglomerative hierarchical clustering method. Unlike S\'ersic, this classification scheme separates compact galaxies from larger, smooth proto-elliptical systems, and star-forming disk-dominated clumpy galaxies from star-forming bulge-dominated asymmetric galaxies. Distinguishing between these galaxy structural types in a quantitative manner is an important step towards understanding the connections between morphology, galaxy assembly and star-formation., Comment: 31 pages, 24 figures, accepted for publication in MNRAS

The morphology-density relationship states that dense cosmic environments such as galaxy clusters have an overabundance of quiescent elliptical galaxies, but it is unclear at which redshift this relationship is first established. We study the morphology of 4 clusters with $1.2

We investigate and demonstrate the use of convolutional neural networks (CNNs) for the task of distinguishing between merging and non-merging galaxies in simulated images, and for the first time at high redshifts (i.e., z = 2 ). We extract images of merging and non-merging galaxies from the Illustris-1 cosmological simulation and apply observational and experimental noise that mimics that from the Hubble Space Telescope; the data without noise form a “pristine” data set and that with noise form a “noisy” data set. The test set classification accuracy of the CNN is 79% for pristine and 76% for noisy. The CNN outperforms a Random Forest classifier, which was shown to be superior to conventional one- or two-dimensional statistical methods (Concentration, Asymmetry, the Gini, M 20 statistics etc.), which are commonly used when classifying merging galaxies. We also investigate the selection effects of the classifier with respect to merger state and star formation rate, finding no bias. Finally, we extract Grad-CAMs (Gradient-weighted Class Activation Mapping) from the results to further assess and interrogate the fidelity of the classification model.

We study the stellar angular momentum of thousands of galaxies in the Illustris cosmological simulation, which captures gravitational and gas dynamics within galaxies, as well as feedback from stars and black holes. We find that the angular momentum of the simulated galaxies matches observations well, and in particular two distinct relations are found for late-type versus early-type galaxies. The relation for late-type galaxies corresponds to the value expected from full conservation of the specific angular momentum generated by cosmological tidal torques. The relation for early-type galaxies corresponds to retention of only ~30% of that, but we find that those early-type galaxies with low angular momentum at z=0 nevertheless reside at high redshift on the late-type relation. Some of them abruptly lose angular momentum during major mergers. To gain further insight, we explore the scaling relations in simulations where the galaxy formation physics is modified with respect to the fiducial model. We find that galactic winds with high mass-loading factors are essential for obtaining the high angular momentum relation typical for late-type galaxies, while AGN feedback largely operates in the opposite direction. Hence, feedback controls the stellar angular momentum of galaxies, and appears to be instrumental for establishing the Hubble sequence., Comment: Updated to match accepted ApJL version (minor modifications). 7 pages, 4 figures

We use machine learning to identify in color images of high-redshift galaxies an astrophysical phenomenon predicted by cosmological simulations. This phenomenon, called the blue nugget (BN) phase, is the compact star-forming phase in the central regions of many growing galaxies that follows an earlier phase of gas compaction and is followed by a central quenching phase. We train a Convolutional Neural Network (CNN) with mock "observed" images of simulated galaxies at three phases of evolution: pre-BN, BN and post-BN, and demonstrate that the CNN successfully retrieves the three phases in other simulated galaxies. We show that BNs are identified by the CNN within a time window of $\sim0.15$ Hubble times. When the trained CNN is applied to observed galaxies from the CANDELS survey at $z=1-3$, it successfully identifies galaxies at the three phases. We find that the observed BNs are preferentially found in galaxies at a characteristic stellar mass range, $10^{9.2-10.3} M_\odot$ at all redshifts. This is consistent with the characteristic galaxy mass for BNs as detected in the simulations, and is meaningful because it is revealed in the observations when the direct information concerning the total galaxy luminosity has been eliminated from the training set. This technique can be applied to the classification of other astrophysical phenomena for improved comparison of theory and observations in the era of large imaging surveys and cosmological simulations., Comment: Accepted for publication in ApJ

Modern cosmological simulations model the universe with increasing sophistication and at higher spatial and temporal resolutions. These enhancements permit detailed comparisons between the simulation outputs and real observational data. Recent projects such as Illustris are capable of producing simulated images that are comparable to those obtained from local surveys. This paper tests how well Illustris achieves this goal across a diverse population of galaxies using visual morphologies derived from Galaxy Zoo citizen scientists. Morphological classifications provided by volunteers for simulated galaxies are compared with similar data for a compatible sample of images drawn from the SDSS Legacy Survey. This paper investigates how simple morphological characterization by human volunteers asked to distinguish smooth from featured systems differs between simulated and real galaxy images. Differences are identified, which are likely due to the limited resolution of the simulation, but which could be revealing real differences in the dynamical evolution of populations of galaxies in the real and model universes. Specifically, for stellar masses $M_{\star}\lesssim10^{11}M_{\odot}$, a larger proportion of Illustris galaxies that exhibit disk-like morphology or visible substructure, relative to their SDSS counterparts. Toward higher masses, simulated and observed galaxies converge and exhibit similar morphology distributions. The stellar mass threshold indicated by this divergent behavior confirms recent works using parametric measures of morphology from Illustris simulated images. When $M_{\star}\gtrsim10^{11}M_{\odot}$, the Illustris dataset contains fewer galaxies that classifiers regard as unambiguously featured. These results suggest that comparison between the detailed properties of observed and simulated galaxies, even when limited to reasonably massive systems, may be misleading., Comment: 12 pages, 7 figures, to be published in The Astrophysical Journal