arXiv subjects

Connor Bottrell

Publications and source records attributed to Connor Bottrell.

At least 19 recordsLinked to original sources

arXiv2026

Widespread Inflows Reveal Baryonic Cycling in Star-forming and Quiescent Galaxies

Cool-gas inflows, required to sustain star formation, have been fundamental in simulations yet remained observationally elusive. Using DESI spectroscopy of ~30,000 galaxies, we identify coherent inflowing gas (~100 km/s) in 20-50% of the sample, yielding a population-level census of gas flows. We uncover a striking inversion: inflows are detected in quiescent galaxies, whereas star-forming systems are dominated by gravitationally bound outflows. At fixed age, galaxies with inflows, outflows, or no/weak flows share similar masses, environments, and structures, indicating that these properties do not differentiate flow states. Instead, gas-flow state is linked to stellar population age and recent evolutionary history, consistent with age-dependent gas flows in two regimes. In some star-forming galaxies, elevated star formation surface densities drive outflows that recycle on ~0.5 Gyr timescales, consistent with a galactic fountain. In quiescent systems, low-level ``drizzling'' inflows persist, consistent with slowly cooling enriched halo gas and weak radio-mode nuclear activity. Broad gas-phase metallicity distributions---and absence of a pristine dilution signature---indicate that detected inflows are predominantly recycled or enriched. Detectability is modulated by dust, ionization, and geometry: in star-forming disks, inflowing gas lies near the disk plane and is obscured or ionized, while outflow hosts exhibit higher dust and metal content. As star formation declines, cold-outflow signatures weaken, and recycled or slowly cooling gas is more readily detected as inflow. Post-starburst galaxies provide snapshots of this transition. Our results resolve the scarcity of observed inflows, provide evidence for widespread gas accretion and recycling in present day galaxies, and establish an observational framework linking gas flows to star formation, chemical evolution, and galaxy structure.

astro-ph.GA↗

arXiv2026

The Structural Abundance Crisis of Massive Galaxies in Current Cosmological Simulations

The internal structure of galaxies encodes the complex baryon cycle driven by gas accretion, star formation, and feedback, together with secular evolution and environmentally driven processes such as mergers and tidal interactions. We present a population-level census of massive nearby galaxies ($\log(M_\star/M_\odot) > 10$) by comparing Hyper Suprime-Cam Subaru Strategic Program observations with matched mock images from IllustrisTNG, EAGLE, and SIMBA. Using a consistent, like-for-like imaging pipeline, we construct structural abundance functions (SAFs) for key morphological parameters, revealing a structural abundance crisis. Across S\'{e}rsic index, concentration, size, and ellipticity, all simulations exhibit large, systematic discrepancies ($>5\sigma$; RMSE $\sim 0.2$--$1.8$\,dex), typically corresponding to abundance differences of factors of several. While individual simulations display diverse failures---underproducing or overproducing compact spheroids, extended or round galaxies ---all underproduce highly flattened disks. Although TNG shows the closest agreement and SIMBA the largest offsets, this shared failure indicates that current models---despite matching global demographics such as the stellar mass function---do not uniquely constrain internal galaxy structure. Our results demonstrate that agreement in integrated observables can mask fundamental shortcomings in the modelling of mass and angular momentum redistribution. We therefore establish SAFs as a stringent, multidimensional, and observationally accessible benchmark for testing and calibrating next-generation galaxy formation models in the era of upcoming deep, wide-field surveys.

astro-ph.GA↗

arXiv2026

Formation of globular cluster-rich ultra-diffuse galaxies through mergers

We use high-resolution, idealized hydrodynamic simulations of gas-rich dwarf-galaxy mergers to test whether such encounters can form ultra-diffuse galaxies (UDGs) with globular cluster (GC) systems. We simulate 1:1 and 1:2 mergers alongside an isolated control model and identify stellar overdensities as GC candidates (GCCs). The remnants evolve into dispersion-supported, UDG-like systems with three-dimensional stellar half-mass radii $r^{3D} \sim 1.9-2.6$ kpc, while the isolated dwarf remains rotationally supported and forms no GCCs. Tidal heating and stellar feedback expel a large fraction of the gas beyond the dark matter (DM) halo, leaving stellar-dominated remnants whose DM haloes remain cuspy. Merger-driven star formation is highly clustered: the fraction of newly formed stellar mass bound in massive clusters exceeds 0.5 after the first pericentric passage and remains elevated thereafter. By the final snapshot, the remnants host GC populations numbering 20 (1:1) and 39 (1:2), more centrally concentrated than the field stars and consistent with the observed GC number-halo mass relation. The GCCs match observed star clusters in the planes of mass versus size, velocity dispersion, and density. More massive clusters exhibit stronger internal rotation and broader metallicity spreads. In one case, the merger produces a nucleated UDG via cluster inspiral followed by sustained in-situ star formation. These results demonstrate that gas-rich dwarf mergers are a viable pathway to GC-rich (and sometimes nucleated) UDGs, and predict correlated cluster mass, rotation, and metallicity-dispersion trends testable with observations.

astro-ph.GA↗

arXiv2026

The COLIBRE-SKIRT pipeline: Calibration-free dust radiative transfer postprocessing for cosmological simulations

Context. Three-dimensional dust radiative transfer provides a powerful framework to connect cosmological galaxy simulations to multiwavelength observations. Until recently, in large-volume simulations, the formation of a cold ISM phase was prevented and dust was not evolved self-consistently. This required calibration of dust-to-metal ratios and extra subgrid dust attenuation in birth clouds, thereby reducing the predictive power. Aims. We present the COLIBRE-SKIRT pipeline, a calibration-free dust radiative transfer framework for the novel COLIBRE suite of large-volume cosmological simulations, which include a live dust model and directly simulate the multiphase ISM. Our primary aim is to establish a reference pipeline for generating multiwavelength mock observables from these simulations. As a first application, we produce far-ultraviolet (FUV) to far-infrared (FIR) spatially integrated spectra and assess them by comparison with the observed low-redshift cosmic spectral energy distribution (CSED). Methods. We apply the SKIRT dust radiative transfer code to the COLIBRE simulations. Dust masses and species fractions are taken directly from the simulation, and no birth cloud model is added in postprocessing. We introduce a "split & scale" approach that maps the simulated two-size, multi-species dust distribution onto continuous grain size distributions without introducing free parameters. Results. We find that, for the first time, a large-volume cosmological simulation directly reproduces the local Universe CSED without calibrating the postprocessing routine a priori. Residual tensions in the mid-infrared (~0.2 dex) point towards insufficient heating of the hottest dust components and uncertainties in the modelling of the PAH-emission carriers. This framework can be readily applied at low and high redshift to create synthetic spectra and images from the FUV to the FIR.

astro-ph.GA↗

arXiv2026

Cosmological Galaxy Formation Modelling in the Era of the Square Kilometre Array

Over the past decade, galaxy formation simulations have advanced dramatically, transforming our ability to model the interstellar medium (ISM) and predict galaxies' radio emission. Yet the challenge of bridging physical scales--from sub-parsec star formation to gigaparsec cosmic structure--remains. The Square Kilometre Array (SKA) will map the cold gas and radio continuum of galaxies across cosmic time, demanding models that couple physical realism with cosmological reach. This chapter reviews the state-of-the-art in cosmological galaxy formation modelling in preparation for the SKA. We outline progress in simulating atomic hydrogen (HI), molecular gas, and radio continuum emission from both star formation and active galactic nuclei, highlighting how cosmological hydrodynamical simulations and semi-analytic models now jointly reproduce many observed gas properties. We emphasise the need for a coordinated, ``wedding-cake'' strategy that unites simulations of different scales, for forward modelling of observables to ensure fair comparison with data, and for the integration of new technologies such as AI-driven emulators to accelerate progress. Together, these efforts will enable theoretical models to both interpret and guide SKA science, turning simulations from passive interpreters into active engines for discovery.

astro-ph.GA↗

arXiv2026

HaloFlow II: Robust Galaxy Halo Mass Inference with Domain Adaptation

Precise halo mass ($M_h$) measurements are crucial for cosmology and galaxy formation. HaloFlow introduced a simulation-based inference (SBI) framework that uses state-of-the-art simulated galaxy images to precisely infer $M_h$. However, for HaloFlow to be applied to observations, it must be generalizable even when the underlying galaxy formation physics differ from those in the simulations on which it was trained. Without this generalization, HaloFlow produces biased and overconfident $M_h$ posteriors when applied to simulations with different physics. We introduce HaloFlow$^{\rm DA}$, an extension of HaloFlow that integrates domain adaptation (DA) with SBI to mitigate these cross-simulation shifts. Using synthetic galaxy images forward-modeled from the IllustrisTNG, EAGLE, and SIMBA simulations, we test two DA methods: Domain-Adversarial Neural Networks (DANN) and Maximum Mean Discrepancy (MMD). Incorporating DA significantly reduces bias and improves calibration, with MMD achieving the most stable performance, lowering the normalized residual metric, $\beta$, by an average of 31% and up to 57% when trained and tested on different simulations. Overall, HaloFlow$^{\rm DA}$ produces more robust, less biased with similar precision, $M_h$ constraints than the standard approach using the stellar-to-halo mass relation. HaloFlow$^{\rm DA}$ enables consistent, simulation-trained inference models to generalize across domains, establishing a foundation for robust $M_h$ inference from real HSC-SSP observations.

astro-ph.GA↗

arXiv2026

Galaxy and black hole coevolution in dark matter haloes not captured by cosmological simulations

Star formation in galaxies is governed by internal and environmental processes, yet their relative roles are not well understood. In particular, uncertainties in measurements of active galactic nuclei (AGN) host galaxies, combined with modeling limitations, obfuscate the impact of supermassive black hole feedback across environments and over time. Here we address this with a comprehensive analysis of ~60,000 nearby AGNs (z < 0.15 and new environment and halo-mass measurements for ~500,000 AGN and non-AGN host galaxies. This benchmark enables unified comparisons with three prominent cosmological simulations--SIMBA, TNG, and EAGLE--and reveals major, contrasting shortcomings. Simulations fail to reproduce observed trends linking star formation, quiescence, AGN luminosity, stellar mass, and halo mass. While simulations qualitatively capture that AGNs are more common in low-mass halos than in rich groups or clusters, detailed host demographics diverge strongly from observations. Partial agreement exists in the stellar mass distribution within large-scale structures, yet all simulations overproduce quenched low-mass satellites in massive halos, while misrepresenting quenched fractions of massive central galaxies and those in low-density environments, which are sensitive to feedback implementation. Improved AGN physics and modeling of multi-phase gas cooling and flows are required to capture the observed interplay between black holes, galaxies, and halos.

astro-ph.GA↗

arXiv2026

Merger Driven or Internal Evolution? A New Morphological Study of Tidal Disruption Event Host Galaxies

The host galaxies of tidal disruption events (TDEs) show enhanced central stellar concentration and are preferentially found in poststarburst and green valley populations. This connection has led to the proposal that TDE host galaxies likely have gone through recent mergers. We conduct a new morphological study of 14 TDE host galaxies, using the r-band images from the Sloan Digital Sky Survey (SDSS), Dark Energy Camera Legacy Survey, and Ultraviolet Near-Infrared Optical Northern Survey, with the images from the latter two surveys having much higher depth and resolution than SDSS. We examine galaxy structures using conventional methods and also apply diagnostics of merger activity from a suite of machine learning models. Consistent with previous studies, our results show that TDE host galaxies are ~16% more centrally concentrated when compared to non-TDE-host controls. However, surprisingly, TDE hosts lack any indication of significant recent merger activity from both morphological analysis and the machine learning merger classifier. Instead, our results reveal that TDE host galaxies in the green valley are approximately 1.5-3 times more likely to have bar-like or ringlike structures compared to their controls. Based on these results, we propose that bar-driven secular evolution, instead of mergers, likely dominates the recent evolution of the TDE hosts found in the green valley, which can simultaneously explain their distinctive nuclear properties and enhanced TDE rates.

astro-ph.HE↗

arXiv2026

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

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

astro-ph.GA↗

arXiv2025

Interacting galaxies in the IllustrisTNG simulations - IX: Mini mergers trigger AGN in cosmological simulations

Galaxy mergers are transformative events that can cause gaseous inflows capable of triggering active galactic nuclei (AGN). Previous studies of AGN in simulations have mainly focused on major interactions (i.e. between approximately equal mass galaxies), which produce the strongest inflows and, therefore, would be the most likely to trigger AGN activity. However, minor interactions are far more common and may still enhance accretion onto supermassive black holes. We present an analysis of post-merger galaxies from the IllustrisTNG simulation with stellar mass ratios of $\mu>$1:100. We select post-mergers from the TNG50-1 simulation, from redshifts $0\leq z< 1$, with stellar masses greater than $10^{10}M_{\odot}$. We find an AGN excess in post-mergers with a stellar mass ratio as low as 1:40. The AGN excess is mass ratio and luminosity dependent, with 1.2-1.6 times more AGN found in post-mergers of 1:40$\leq \mu < $1:4 than in matched non-merger controls, and as many as 6 times more AGN found in major $\mu \geq$1:4 post-mergers. The AGN excess is long lived, between 500 Myr to 1 Gyr post-coalescence, across all of the mass ratio regimes. We demonstrate that the most luminous AGN in the simulation overwhelmingly occur in either post-mergers or pairs (with $\mu \geq $1:40). Finally, we demonstrate that mini mergers are likely to be overlooked in observational studies due to the weakness of features usually associated with recent merger activity, such as tidal streams and shells, making it challenging to completely account for merger-induced AGN activity even in deep galaxy surveys.

astro-ph.GA↗

arXiv2025

The Tremaine-Weinberg method at high redshifts

This paper examines the reliability of the Tremaine-Weinberg (TW) method in measuring the pattern speed of barred galaxies at high redshifts. Measuring pattern speeds at high redshift may help to shed light on the time evolution of interactions between galactic bars and dark matter halos. The TW method has been extensively employed for nearby galaxies, and its accuracy in determining bar pattern speeds has been validated through numerical simulations. For nearby galaxies, the method yields acceptable results when the inclination angle of the galaxy and the position angle of the bar fall within appropriate ranges. However, the application of the TW method to high-redshift galaxies remains unexplored in both observations and simulations. For this study we generated mock observations of barred galaxies from the TNG50 cosmological simulation. These simulated observations were tailored to mimic the integral field unit (IFU) spectroscopy data that the Near-Infrared Spectrograph (NIRSpec) on the James Webb Space Telescope (JWST) would capture at a redshift of $z\simeq 1.2$. By applying the TW method to these mock observations and comparing the results with the known pattern speeds, we demonstrate that the TW method performs adequately for barred galaxies whose bars are sufficiently long to be detected by JWST at high redshifts. This work opens a new avenue for applying the TW method to investigate the properties of high-redshift barred galaxies.

astro-ph.GA↗

arXiv2025

The connection between galaxy mergers, star formation and AGN activity in the HSC-SSP

Internal gas inflows driven by galaxy mergers are considered to enhance star formation rates (SFR), fuel supermassive black hole growth and stimulate active galactic nuclei (AGN). However, quantifying these phenomena remains a challenge, due to difficulties both in classifying mergers and in quantifying galaxy and AGN properties. We quantitatively examine the merger-SFR-AGN connection using Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) galaxies using novel methods for both galaxy classification and property measurements.} {Mergers in HSC-SSP observational images are identified through fine-tuning Zoobot, a pretrained deep representation learning model, using images and labels based on the Galaxy Cruise project. We use galaxy and AGN properties that were produced by fitting Galaxy and Mass Assembly (GAMA) spectra using the SED fitting code ProSpect, which fits panchromatically across the far-UV through far-infrared wavelengths and obtains galaxy and AGN properties simultaneously.} \textbf{{Little differences are seen in SFR and AGN activity between mergers and controls, with $\Delta \mathrm{SFR}=-0.009\pm 0.003$ dex, $\Delta f_{\mathrm{AGN}}=-0.010\pm0.033$ dex and $\Delta L_{\mathrm{AGN}}=0.002\pm0.025$ dex. After further visual purification of the merger sample, we find $\Delta \mathrm{SFR}=-0.033\pm0.014$ dex, $\Delta f_{\mathrm{AGN}}=-0.024\pm0.170$ dex, and $\Delta L_{\mathrm{AGN}}=0.019\pm0.129$ dex for pairs, and $\Delta \mathrm{SFR}=-0.057\pm0.024$ dex, $\Delta f_{\mathrm{AGN}}=0.286\pm0.270$ dex, and $\Delta L_{\mathrm{AGN}}=0.329\pm0.195$ dex for postmergers. These numbers suggest secular processes being an important driver for SF and AGN activity, and present a cautionary tale when using longer timescale tracers.

astro-ph.GA↗

arXiv2024

Galaxy evolution in the post-merger regime I -- Most merger-induced in-situ stellar mass growth happens post-coalescence

Galaxy mergers can enhance star formation rates throughout the merger sequence, with this effect peaking around the time of coalescence. However, owing to a lack of information about their time of coalescence, post-mergers could only previously be studied as a single, time-averaged population. We use timescale predictions of post-coalescence galaxies in the UNIONS survey, based on the Multi-Model Merger Identifier deep learning framework (\textsc{Mummi}) that predicts the time elapsed since the last merging event. For the first time, we capture a complete timeline of star formation enhancements due to galaxy mergers by combining these post-merger predictions with data from pre-coalescence galaxy pairs in SDSS. Using a sample of $564$ galaxies with $M_* \geq 10^{10} M_\odot$ at $0.005 < z < 0.3$ we demonstrate that: 1) galaxy mergers enhance star formation by, on average, up to a factor of two; 2) this enhancement peaks within 500 Myr of coalescence; 3) enhancements continue for up to 1~Gyr after coalescence; and 4) merger-induced star formation significantly contributes to galaxy mass assembly, with galaxies increasing their final stellar masses by, $10\%$ to $20\%$ per merging event, producing on average $\log(M_*/M_\odot) = {9.56_{-0.19}^{+0.13}}$ more mass than non-interacting star-forming galaxies solely due to the excess star formation.

astro-ph.GA↗

arXiv2024

The effect of image quality on galaxy merger identification with deep learning

Studies have shown that the morphologies of galaxies are substantially transformed following coalescence after a merger, but post-mergers are notoriously difficult to identify, especially in imaging that is shallow or low-resolution. We train convolutional neural networks (CNNs) to identify simulated post-merger galaxies in a range of image qualities, modelled after five real surveys: the Sloan Digital Sky Survey (SDSS), the Dark Energy Camera Legacy Survey (DECaLS), the Canada-France Imaging Survey (CFIS), the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP), and the Legacy Survey of Space and Time (LSST). Holding constant all variables other than imaging quality, we present the performance of the CNNs on reserved test set data for each image quality. The success of CNNs on a given dataset is found to be sensitive to both imaging depth and resolution. We find that post-merger recovery generally increases with depth, but that limiting 5 sigma point-source depths in excess of ~25 mag, similar to what is achieved in CFIS, are only marginally beneficial. Finally, we present the results of a cross-survey inference experiment, and find that CNNs trained on a given image quality can sometimes be applied to different imaging data to good effect. The work presented here therefore represents a useful reference for the application of CNNs for merger searches in both current and future imaging surveys.

astro-ph.GA↗

arXiv2024

Supermassive black hole feedback quenches disc galaxies and suppresses bar formation in TNG50

We use the cosmological magneto-hydrodynamical simulation TNG50 to study the relationship between black hole feedback, the presence of stellar bars, and star formation quenching in Milky Way-like disc galaxies. Of our sample of 198 discs, about 63 per cent develop stellar bars that last until z=0. After the formation of their bars, the majority of these galaxies develop persistent 3-15 kpc wide holes in the centres of their gas discs. Tracking their evolution from z=4 to 0, we demonstrate that barred galaxies tend to form within dark matter haloes that become centrally disc dominated early on (and are thus unstable to bar formation) whereas unbarred galaxies do not; barred galaxies also host central black holes that grow more rapidly than those of unbarred galaxies. As a result, most barred galaxies eventually experience kinetic wind feedback that operates when the mass of the central supermassive black hole exceeds $M_{BH} > 10^8 M_{\odot}$. This feedback ejects gas from the central disc into the circumgalactic medium and rapidly quenches barred galaxies of their central star formation. If kinetic black hole feedback occurs in an unbarred disc it suppresses subsequent star formation and inhibits its growth, stabilising the disc against future bar formation. Consequently, most barred galaxies develop black hole-driven gas holes, though a gas hole alone does not guarantee the presence of a stellar bar. This subtle relationship between black hole feedback, cold gas disc morphology, and stellar bars may provide constraints on subgrid physics models for supermassive black hole feedback.

astro-ph.GA↗

arXiv2024

IllustrisTNG in the HSC-SSP: No Shortage of Thin Disk Galaxies in TNG50

We perform a thorough analysis of the projected shapes of nearby galaxies in both observations and cosmological simulations. We implement a forward-modeling approach to overcome the limitations in previous studies, which hinder accurate comparisons between observations and simulations. We measure axis ratios of $z=0$ (snapshot 99) TNG50 galaxies from their synthetic Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) images and compare them with those obtained from real HSC-SSP images of a matched galaxy sample. Remarkably, the comparison shows excellent agreement between the observations and the TNG50 simulation, challenging previous claims that $\Lambda$CDM models underproduced the abundance of thin galaxies. Specifically, for galaxies with stellar masses $10\leq \log (M_{\star}/M_{\odot}) \leq 11.5$, we find $\lesssim 0.1\sigma$ tensions between the observations and the simulation, a stark contrast to the previously reported $\gtrsim 10\sigma$ tensions. We reveal that low-mass galaxies ($M_{\star}\lesssim 10^{9.5}\,M_{\odot}$) in TNG50 are thicker than their observed counterparts in HSC-SSP and attribute this to the spurious dynamical heating effects that artificially puff up galaxies. We also find that, despite the overall broad agreement, TNG50 galaxies are more concentrated than the HSC-SSP ones at the low- and high-mass end of the stellar mass range of $9.0\leq \log (M_{\star}/M_{\odot}) \leq 11.2$ and are less concentrated at intermediate stellar masses. But we argue that the higher concentrations of the low-mass TNG50 galaxies are not likely the cause of their thicker/rounder appearances. Our study underscores the critical importance of conducting mock observations of simulations and applying consistent measurement methodologies to facilitate proper comparison with observations.

astro-ph.GA↗

arXiv2024

Galaxy Mergers in UNIONS -- I: A Simulation-driven Hybrid Deep Learning Ensemble for Pure Galaxy Merger Classification

Merging and interactions can radically transform galaxies. However, identifying these events based solely on structure is challenging as the status of observed mergers is not easily accessible. Fortunately, cosmological simulations are now able to produce more realistic galaxy morphologies, allowing us to directly trace galaxy transformation throughout the merger sequence. To advance the potential of observational analysis closer to what is possible in simulations, we introduce a supervised deep learning Convolutional Neural Network (CNN) and Vision Transformer (ViT) hybrid framework, Mummi (MUlti Model Merger Identifier). Mummi is trained on realism-added synthetic data from IllustrisTNG100-1, and is comprised of a multi-step ensemble of models to identify mergers and non-mergers, and to subsequently classify the mergers as interacting pairs or post-mergers. To train this ensemble of models, we generate a large imaging dataset of 6.4 million images targeting UNIONS with RealSimCFIS. We show that Mummi offers a significant improvement over many previous machine learning classifiers, achieving 95% pure classifications even at Gyr long timescales when using a jury-based decision making process, mitigating class imbalance issues that arise when identifying real galaxy mergers from $z=0$ to $0.3$. Additionally, we can divide the identified mergers into pairs and post-mergers at 96% success rate. We drastically decrease the false positive rate in galaxy merger samples by 75%. By applying Mummi to the UNIONS DR5-SDSS DR7 overlap, we report a catalog of 13,448 high confidence galaxy merger candidates. Finally, we demonstrate that Mummi produces powerful representations solely using supervised learning, which can be used to bridge galaxy morphologies in simulations and observations.

astro-ph.GA↗

arXiv2024

Rich and diverse molecular gas environments of closely-separated dual quasars viewed by ALMA

We present a study of the molecular gas in five closely-spaced ($R_{\perp}<20$ kpc) dual quasars ($L_{\rm bol}\gtrsim10^{44}~\mathrm{erg~s}^{-1}$) at redshifts $0.4<z<0.8$ with the Atacama Large Millimeter/submillimeter Array. The dual quasar phase represents a distinctive stage during the interaction between two galaxies for investigating quasar fueling and feedback effects on the gas reservoir. The dual quasars were selected from the Sloan Digital Sky Survey and Subaru/Hyper Suprime-Cam Subaru Strategic Program, with confirmatory spectroscopic validation. Based on the detection of the CO J=2--1 emission line with Band 4, we derived key properties including CO luminosities, line widths, and molecular gas masses for these systems. Among the ten quasars of the five pairs, eight have line detections exceeding $5\sigma$. The detected sources prominently harbor substantial molecular gas reservoirs, with molecular gas masses ($M_{\text{molgas}}$) between $10^{9.6-10.5}~\mathrm{M_{\odot}}$, and molecular gas-to-stellar mass ratios ($\mu_{\text{molgas}}$) spanning $18-97\%$. The overall $\mu_{\text{molgas}}$ of these dual quasars agrees with that of inactive star-forming main-sequence galaxies at comparable redshifts, indicating no clear evidence of quenching. However, intriguing features in each individual system show possible evidence of AGN feedback, matter transfer, and compaction processes.

astro-ph.GA↗