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Shoshannah Byrne-Mamahit

Publications and source records attributed to Shoshannah Byrne-Mamahit.

12 recordsLinked to original sources

SALVAGE II: no systematic molecular gas depletion in the central 2 kpc of AGN hosts

In cosmological simulations, active galactic nuclei (AGN) feedback is found to be necessary for the shutdown of galaxy-wide star-formation by heating and/or removing molecular gas. However, at low-redshift, there is little evidence of systematic large-scale gas depletion. Some recent observations have found molecular gas depletion in AGN hosts, but limited to the central regions of galaxies. In this work, we use the SDSS-ALMA Legacy-Value Archival Gas Exploration (SALVAGE) dataset, which provides molecular gas and stellar mass measurements from the inner (r < 0.5-2 kpc) and outer region of the galaxy. Using AGN diagnostics from optical emission lines, mid-IR colour, and X-ray luminosity, we identify 70 AGN at z < 0.07 and inspect their central molecular gas reservoirs with a suite of metrics compared to non-AGN controls. In agreement with global studies of low-z AGN hosts, we find that, compared to matched non-AGN, the central regions of AGN have equal molecular gas fractions and enhanced molecular gas surface densities. For the first time, we explore the central gas reservoirs of AGN identified with different selection criteria and find two optical AGN classes that show a tentative 1.5$σ$ and 1.8$σ$ signal of central molecular gas depletion. However, the AGN with central gas depletion do not occupy any specific region of the parameter space, such as AGN luminosity, that can provide a physical explanation for the depletion. If AGN are responsible for large-scale gas removal, the lack of systematic gas depletion in SALVAGE AGN sets an upper limit on the physical scale of the gas removal while the AGN remains observable.

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EMBERS I: Low redshift post-starburst galaxies are frequently depleted in molecular gas relative to star forming progenitors

The cold gas content of post-starburst galaxies (PSBs) provides important insight into the mechanisms that drive rapid quenching, but a multiphase assessment of both the atomic and molecular gas in PSBs does not yet exist. We introduce the Ensemble of Multiphase Baryons Evolving in Rapidly-quenching Systems, or EMBERS, a homogeneously selected, nearly mass- and redshift-complete survey of the global atomic (HI) and molecular gas (H2) in PSBs, observed with the Five Hundred-metre Aperture Spherical Telescope (FAST) and the Institut de radioastronomie millimetrique (IRAM) 30m telescope. We present new CO(1-0) observations for 52 PSBs with the IRAM 30m, which, combined with 9 archival observations, gives a total H2 sample of 61, of which 58/61 have ancillary HI measurements. We detect CO(1-0) in 34/61 galaxies, corresponding to molecular gas fractions (fH2 = MH2/M*) ranging from two to 250 per cent. By comparing with a stellar-mass matched star-forming (SF) control sample from xCOLD GASS, we find that PSBs on average are 0.3-0.6 dex depleted in H2. However, considering both HI and H2, individual PSBs host diverse gas reservoirs ranging from gas-rich in both phases, elevated in one phase, or gas-poor, the latter of which is common at lower stellar mass. The existence of gas-normal and gas-depleted PSBs in both phases suggests that some PSBs may rejuvenate their star formation, but the rapid shutdown of star formation in others is likely terminal. Despite this diversity, the majority of EMBERS PSBs are gas-poor compared to SF controls, with the typical PSB hosting gas reservoirs intermediate to those found in star-forming and quenched galaxies.

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Galaxy Mergers in UNIONS -- II: Predicting Timescales in the Post-Merger Regime

Galaxy mergers are critical events that influence galaxy evolution by driving processes such as enhanced star formation, quenching, and active galactic nucleus (AGN) activity. However, constraining the timescales over which these processes occur in the post-merger phase has remained a significant challenge. This study extends the MUlti-Model Merger Identifier (\textsc{Mummi}) framework to predict post-merger timescales ($T_{PM}$) for galaxies, leveraging machine learning models trained on realism-enhanced mock observations derived from the IllustrisTNG simulations. By classifying post-merger galaxies into four temporal bins spanning 0 to 1.76 Gyr after coalescence, \textsc{Mummi} achieves time classification accuracies exceeding 70 per cent. We apply this framework to the Ultraviolet Near Infrared Optical Northern Survey (UNIONS), yielding a catalog of 8,716 post-merger galaxies with $T_{PM}$ predictions and stellar masses $\log(M_*/M_\odot) \geq 10$ at redshifts 0.03 < z < 0.3. These results provide a robust methodology to connect galaxy interaction timescales with physical processes, enabling detailed studies of galaxy evolution in the post-merger regime.

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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 $μ>$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 μ< $1:4 than in matched non-merger controls, and as many as 6 times more AGN found in major $μ\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 $μ\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.

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Galaxy evolution in the post-merger regime. III -- The triggering of active galactic nuclei peaks immediately after coalescence

Galaxy mergers have been shown to trigger AGN in the nearby universe, but the timescale over which this process happens remains unconstrained. The Multi-Model Merger Identifier (MUMMI) machine vision pipeline has been demonstrated to provide reliable predictions of time post-merger (T_PM) for galaxies selected from the Ultraviolet Near Infrared and Optical Northern Survey (UNIONS) up to T_PM=1.76 Gyr after coalescence. By combining the post-mergers identified in UNIONS with pre-coalescence galaxy pairs, we can study the triggering of AGN throughout the merger sequence. AGN are identified using a range of complementary metrics: mid-IR colours, narrow emission lines and broad emission lines, which can be combined to provide insight into the demographics of dust and luminosity of the AGN population. Our main results are: 1) Regardless of the metric used, we find that the peak AGN excess (compared with a matched control sample) occurs immediately after coalescence, at 0 < T_PM < 0.16 Gyr. 2) The excess of AGN is observed until long after coalescence; both the mid-IR selected AGN and broad line AGN are more common than in the control sample even in the longest time bin of our sample (0.96 < T_PM < 1.76 Gyr). 3) The AGN excess is larger for more luminous and bolometrically dominant AGN, and we find that AGN in post-mergers are generally more luminous than secularly triggered events. 4) A deficit of broad line AGN in the pre-merger phase, that evolves into an excess in post-mergers is consistent with evolution of the covering fraction of nuclear obscuring material. Before coalescence, tidally triggered inflows increase the covering fraction of nuclear dust; in the post-merger regime feedback from the AGN clears (at least some of) this material. 5) The statistical peak in the triggering of starbursts occurs contemporaneously with AGN, within 0.16 Gyr of coalescence.

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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.

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X-ray AGNs with SRG/eROSITA: Multi-wavelength observations reveal merger triggering and post-coalescence circumnuclear blowout

Major mergers between galaxies are predicted to fuel their central supermassive black holes (SMBHs), particularly after coalescence. However, determining the prevalence of active galactic nuclei (AGNs) in mergers remains a challenge, because AGN diagnostics are sensitive to details of the central structure (e.g., nuclear gas clouds, geometry and orientation of a dusty torus) that are partly decoupled from SMBH accretion. X-rays, expected to be ubiquitous among accreting systems, are detectable through non-Compton-thick screens of obscuring material, and thus offer the potential for a more complete assessment of AGNs in mergers. But, extant statistical X-ray studies of AGNs in mergers have been limited by either sparse, heterogeneous, or shallow on-sky coverage. We use new X-ray observations from the first SRG/eROSITA all-sky data release to characterize the incidence, luminosity, and observability of AGNs in mergers. Combining machine learning and visual classification, we identify 923 post-mergers in Dark Energy Camera Legacy Survey (DECaLS) imaging and select 4,565 interacting galaxy pairs (with separations <120 kpc and mass ratios within 1:10) from the Sloan Digital Sky Survey. We find that galaxies with X-ray AGNs are 2.0+/-0.24 times as likely to be identified as post-mergers compared to non-AGN controls, and that post-mergers are 1.8+/-0.1 times as likely to host an X-ray AGN as non-interacting controls. A multi-wavelength census of X-ray, optical, and mid-IR-selected AGNs suggests a picture wherein the underlying AGN fraction increases during pair-phase interactions, that galaxy pairs within ~20 kpc become heavily obscured, and that the obscuration often clears post-coalescence.

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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.

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Interacting galaxies in the IllustrisTNG simulations -- VII: The connection between the most luminous active galactic nuclei and galaxy interactions

We investigate the connection between the most luminous active galactic nuclei (AGN), galaxy pairs, and post-mergers in the IllustrisTNG simulation. We select galaxy pairs and post-mergers with a mass ratio between 1:10 $< μ<$ 1:1 and a redshift between $0 10^{44}$ erg/s occur in $\sim $26\% of paired galaxies with a companion within 20 kpc, compared with $\sim $14\% in controls (a fractional excess of $\sim$2). The enhancement of AGN in galaxy pairs is luminosity dependent, with the highest excess (a factor of $\sim6\pm2$ at the closest separations) for AGN with $L_{\mathrm{bol}}>10^{45}$ erg/s. Additionally, pairs exhibit a modest yet statistically significant excess of luminous AGN up to $\sim$150 kpc in separation. For pairs which merge between $0 10^{45}$ erg/s, $\sim$55\% are interacting, compared with a 30\% interaction fraction in AGN with $10^{44}<L_{\mathrm{bol}}<10^{44.5}$ erg/s. Our results support a picture in which interactions play a dominant role in (but are not the sole cause of) triggering the most luminous AGN.

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The limitations (and potential) of non-parametric morphology statistics for post-merger identification

Non-parametric morphology statistics have been used for decades to classify galaxies into morphological types and identify mergers in an automated way. In this work, we assess how reliably we can identify galaxy post-mergers with non-parametric morphology statistics. Low-redshift (z<0.2), recent (t_post-merger < 200 Myr), and isolated (r > 100 kpc) post-merger galaxies are drawn from the IllustrisTNG100-1 cosmological simulation. Synthetic r-band images of the mergers are generated with SKIRT9 and degraded to various image qualities, adding observational effects such as sky noise and atmospheric blurring. We find that even in perfect quality imaging, the individual non-parametric morphology statistics fail to recover more than 55% of the post-mergers, and that this number decreases precipitously with worsening image qualities. The realistic distributions of galaxy properties in IllustrisTNG allow us to show that merger samples assembled using individual morphology statistics are biased towards low mass, high gas fraction, and high mass ratio. However, combining all of the morphology statistics together using either a linear discriminant analysis or random forest algorithm increases the completeness and purity of the identified merger samples and mitigates bias with various galaxy properties. For example, we show that in imaging similar to that of the 10-year depth of the Legacy Survey of Space and Time (LSST), a random forest can identify 89% of mergers with a false positive rate of 17%. Finally, we conduct a detailed study of the effect of viewing angle on merger observability and find that there may be an upper limit to merger recovery due to the orientation of merger features with respect to the observer.

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The interconnection between galaxy mergers, AGN activity and rapid quenching of star formation in simulated post-merger galaxies

We investigate the role of galaxy mergers on supermassive black hole (SMBH) accretion and star formation quenching in three state-of-the-art cosmological simulations with contrasting physics models: EAGLE, Illustris and IllustrisTNG. We find that recently coalesced 'post-mergers' in all three simulations have elevated SMBH accretion rates by factors of ~2-5. However, rapid (within 500 Myr of coalescence) quenching of star formation is rare, with incidence rates of 0.4% in Illustris, 4.5% in EAGLE and 10% in IllustrisTNG. The rarity of quenching in post-mergers results from substantial gas reservoirs that remain intact after the merger. The post-mergers that do successfully quench tend to be those that had both low pre-merger gas fractions as well as those that experience the largest gas losses. Although rare, the recently quenched fraction of post-mergers is still elevated compared to a control sample of non-mergers by factors of two in IllustrisTNG and 11 in EAGLE. Conversely, quenching is rarer in Illustris post-mergers than in their control. Recent observational results by Ellison et al. have found rapid quenching to be at least 30 times more common in post-mergers, a significantly higher excess than found in any of the simulations. Our results, therefore, indicate that whilst merger-induced SMBH accretion is a widespread prediction of the simulations, its link to quenching depends sensitively on the physics models, and that none of the subgrid models of the simulations studied here can fully capture the connection between mergers and rapid quenching seen in observations.

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Interacting galaxies in the IllustrisTNG simulations -- IV: Enhanced Supermassive Black Hole Accretion Rates in Post-Merger Galaxies

We present an analysis of the instantaneous supermassive black hole (SMBH) accretion rates in a collection of 1563 post-merger galaxies drawn from the IllustrisTNG simulation. Our sample consists of galaxies that have experienced a merger in the last simulation snapshot (within ~160 Myrs of coalescence) in the redshift range 0 1:10 and post-merger stellar masses > $10^{10} M_{\odot}$. We find that, on average, the accretion rates of the post-mergers are ~1.7 times higher than in a control sample and that post-mergers are 3-4 times more likely to experience a luminous active galactic nuclei (AGN) phase than isolated galaxies. SMBH accretion rate enhancements persist for ~2 Gyrs after coalescence, significantly exceeding the ~500 Myr lifetime of star formation rate enhancements. We find that the presence of simultaneous enhancements in both the star formation and SMBH accretion rates depends on both the mass ratio of the merger and on the gas mass of the post-merger galaxy. Despite these accretion rate enhancements, only ~35% of post-mergers experience a luminous AGN ($L_{bol}>10^{44}$ erg/s) within 500 Myrs after coalescence, and fewer than 10\% achieve a luminosity in excess of $L_{bol}>10^{45}$ erg/s. Moreover, only ~10\% of the highest luminosity ($L_{bol}>10^{45}$ erg/s) AGN in the IllustrisTNG galaxy sample are recent mergers. Our results are therefore consistent with a picture in which mergers can (but don't always) trigger AGN activity, but where the majority of galaxies hosting high luminosity AGN are not recent mergers.

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