Galaxy mergers are transformative events that can cause gaseous inflows capable of triggering active galactic nuclei (AGNs). Previous studies of AGNs 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 on to 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 <= z < 1, with stellar masses greater than 10(10 )M(circle dot). 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 AGNs found in post-mergers of 1 :40 <= mu < 1:4 than in matched non-merger controls, and as many as 6 times more AGNs found in major mu >= 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 AGNs in the simulation overwhelmingly occur in either post-mergers or pairs (with mu >= 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.

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 time-scale predictions of post-coalescence galaxies in the UNIONS survey, based on the Multi Model Merger Identifier deep learning framework (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-* >= 10(10) M-circle dot 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 per cent to 20 per cent per merging event, producing on average log(M-*/M-circle dot) = 9.56(-0.19)(+0.13) more mass than non-interacting star-forming galaxies solely due to the excess star formation.

Using the TNG100-1 cosmological simulations, we explore how galaxy properties, such as specific star formation rate (sSFR = SFR/M-& lowast;), gas fraction (f(gas )= M-H/M-& lowast;), and star formation efficiency (SFEH = SFR/MH), change over the course of galaxy-galaxy interactions. We identify 18 534 distinct encounters from the reconstructed orbits of a sample of massive galaxies (M-& lowast; > 10(10)M(circle dot)) with companions within a stellar mass ratio of 0.1-10. Using these encounters, we study the variation of galaxy properties over time as they approach and move away from pericentric encounters over a redshift range of 0 <= z < 1. Following the closest pericentric encounters (<= 50 kpc) of a host galaxy with its companion, we find that sSFR is enhanced by a factor of 1.6 +/- 0.1 on average within the central stellar half-mass radius (R-1/2) compared to pre-encounter values. Our results show a time delay between pericentre and maximum sSFR enhancement of similar to 0.1 Gyr with a mean galaxy separation of 75 kpc. We similarly find that f(gas) is enhanced by a factor of 1.2 +/- 0.1, and SFEH is enhanced by a factor of 1.4 +/- 0.1 following the pericentre of an encounter within the same time-scale. Additionally, we find evidence of inflowing gas towards the centre, measured by comparing the f(gas) and metallicity within the central R-1/2 to the galactic outskirts. We find that approximately 70 per cent of the peak sSFR enhancement can be attributed to the increase in SFEH, with the increase in f(gas) contributing the remaining 30 per cent.

We present interferometric radio observations of the neutral atomic gas in AGC 727130, a low-mass, gas-rich field galaxy lacking significant star formation. The atomic gas in AGC 727130 displays a pronounced asymmetry, extending well beyond the stellar disk in one direction while remaining relatively undisturbed in the other. Despite proximity to a pair of interacting dwarfs, tidal analysis suggests these neighboring galaxies are not responsible for this pronounced asymmetry. Instead, using a topological cosmic web filament finder on spectroscopic catalog data, we find AGC 727130 lies at the intersection of several large-scale cosmic web filaments, environments predicted to host diffuse, shock-heated gas. We propose that an interaction with this ambient medium is stripping gas from the galaxy via cosmic web ram pressure stripping. This mechanism, supported by recent simulations, may quench low-mass galaxies outside of massive halos and must be accounted for when comparing observed numbers of dwarf galaxies to theoretical predictions.

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.

Galaxy mergers represent the most transformative and dramatic avenue for galaxy and supermassive black hole (SMBH) evolution. Multiple active galactic nuclei (multi-AGNs) are expected to ignite, grow, and evolve alongside the host galaxies, and these represent different evolutionary stages of the SMBHs over the merger sequence. However, no comprehensive census exists of observed multi-AGN systems. Here we present the Big Multi-AGN Catalog (the Big MAC), the first literature-complete catalog of all known (confirmed and candidate) multi-AGN systems, which includes dual AGNs (separations ∼0.03–110 kpc), binary AGNs (gravitationally bound, ≲30 pc), and recoiling AGNs, gleaned from hundreds of literature articles spanning the years 1970–2020. The Big MAC is the first archive to assemble all multi-AGN systems and candidates across all selection methods, redshifts, and galaxy mass ratios, and this catalog offers a solid foundation for archival and targeted multiwavelength follow-up investigations. In this work, we provide an overview of the creation of the multi-AGN literature library and the catalog itself, present definitions for different multi-AGN classes (including new definitions for dual AGNs derived from galaxy pairs in Illustris-TNG100), describe the general properties of the catalog as a function of redshift space and separation, and we provide a thorough examination of selection and confirmation method usage within the literature. We also discuss best practices for the multi-AGN literature, and we emphasize that a diverse, multiwavelength array of selection approaches is crucial for a complete understanding of multi-AGNs and—by extension—answering long-standing, open questions regarding the importance of AGNs and galaxy mergers.

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.

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 $< \mu <$ 1:1 and a redshift between $010^{44}$ 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 $010^{45}$ erg/s, $\sim$55\% are interacting, compared with a 30\% interaction fraction in AGN with $10^{44}

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.

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.

Cosmological simulations have been used to study interacting galaxies as a function of galaxy pair separation, enabling comparisons with observational studies of galaxy pairs. The study of interacting galaxies as a function of time (i.e. merger stage) has mostly been limited to high resolution merger simulations, due to the poor time sampling available in cosmological simulations. Building on an earlier study of galaxy pairs in the IllustrisTNG cosmological simulations, we reconstruct the orbits of galaxy pairs involving massive galaxies (M_* > 10^10M_⊙) at redshifts of 0 ≤ z < 1, using a novel kinematic interpolation scheme to model the orbits in between the IllustrisTNG snapshots (which are separated by 162 Myr on average). We assess the accuracy of these interpolations using a pre-existing suite of merger simulations, and find that kinematic interpolations provide a remarkable improvement in accuracy compared with interpolations that use only radial separations or 3D positions. We find that nearly 90 per cent of the closest pairs (r < 25 kpc) have had a pericentre encounter within the past Gyr. Many of these close pairs are found on rapidly shrinking orbits, and roughly 85 per cent of these pairs will merge within 1 Gyr. However, approximately 3 per cent of these close pairs appear to be flyby systems that will never merge. These reconstructed orbits will be used in future studies to investigate how and when galaxy properties change during close encounters and mergers between galaxies in IllustrisTNG.

Low-mass galaxy pair fractions are understudied, and it is unclear whether low-mass pair fractions evolve in the same way as more massive systems over cosmic time. In the era of JWST, Roman, and Rubin, selecting galaxy pairs in a self-consistent way will be critical to connect observed pair fractions to cosmological merger rates across all mass scales and redshifts. Utilizing the Illustris TNG100 simulation, we create a sample of physically associated low-mass (10 8 < M * < 5 × 10 9 M ⊙ ) and high-mass (5 × 10 9 < M * < 10 11 M ⊙ ) pairs between z = 0 and 4.2. The low-mass pair fraction increases from z = 0 to 2.5, while the high-mass pair fraction peaks at z = 0 and is constant or slightly decreasing at z > 1. At z = 0 the low-mass major (1:4 mass ratio) pair fraction is 4× lower than high-mass pairs, consistent with findings for cosmological merger rates. We show that separation limits that vary with the mass and redshift of the system, such as scaling by the virial radius of the host halo ( r sep < 1 R vir ), are critical for recovering pair fraction differences between low-mass and high-mass systems. Alternatively, static physical separation limits applied equivalently to all galaxy pairs do not recover the differences between low- and high-mass pair fractions, even up to separations of 300 kpc. Finally, we place isolated mass analogs of Local Group galaxy pairs, i.e., Milky Way (MW)–M31, MW–LMC, LMC–SMC, in a cosmological context, showing that isolated analogs of LMC–SMC-mass pairs and low-separation (<50 kpc) MW–LMC-mass pairs are 2–3× more common at z ≳ 2–3.

Low mass galaxy pair fractions are understudied, and it is unclear whether low mass pair fractions evolve in the same way as more massive systems over cosmic time. In the era of JWST, Roman, and Rubin, selecting galaxy pairs in a self-consistent way will be critical to connect observed pair fractions to cosmological merger rates across all mass scales and redshifts. Utilizing the Illustris TNG100 simulation, we create a sample of physically associated low mass ($\rm 10^81$. At $z=0$, the low mass major (1:4 mass ratio) pair fraction is 4$\times$ lower than high mass pairs, consistent with findings for cosmological merger rates. We show that separation limits that vary with the mass and redshift of the system, such as scaling by the virial radius of the host halo ($r_{\mathrm{sep}}< 1 R_{\rm vir}$), are critical for recovering pair fraction differences between low mass and high mass systems. Alternatively, static physical separation limits applied equivalently to all galaxy pairs do not recover the differences between low and high mass pair fractions, even up to separations of $300$ kpc. Finally, we place isolated mass-analogs of Local Group galaxy pairs, i.e., Milky Way (MW)--M31, MW--LMC, LMC--SMC, in a cosmological context, showing that isolated analogs of LMC--SMC-mass pairs and low-separation ($<50$ kpc) MW--LMC-mass pairs are $2-3\times$ more common at $z\gtrsim2-3$.

ABSTRACT 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 < z < 1, with merger stellar mass ratios >1: 10 and post-merger stellar masses >1010M⊙. 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 three to four 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 per cent of post-mergers experience a luminous AGN (Lbol > 1044erg/s) within 500 Myrs after coalescence, and fewer than 10 per cent achieve a luminosity in excess of Lbol > 1045erg/s. Moreover, only ∼10 per cent of the highest luminosity (Lbol > 1045erg/s) AGN in the IllustrisTNG galaxy sample are recent mergers. Our results are therefore consistent with a picture in which mergers can (but do not always) trigger AGN activity, but where the majority of galaxies hosting high luminosity AGN are not recent mergers.

We study interacting galaxy pairs in the TNG100-1 and TNG300-1 cosmological simulations using previously generated closest companion samples. We study the specific star formation rates (sSFR) of massive ($10^{10} M_{\odot} < M_* < 10^{12} M_{\odot}$) galaxies at $z \leq 0.2$ as a function of separation from the closest companion galaxy. We split our sample based on whether the companion galaxy is star-forming or passive. We find that galaxies with close star-forming companions have sSFRs that are enhanced (on average) by a factor of $2.9 \pm 0.3$ in TNG100-1 and $2.27 \pm 0.06$ in TNG300-1 compared to controls, with enhancements present out to separations of $\sim 300$ kpc. Galaxies with passive companions in TNG300-1 exhibit mild sSFR suppression ($\sim12$ percent) at 100-300 kpc and small sSFR enhancements at separations below 50 kpc. sSFR suppression is strongest in pairs where the galaxy's stellar mass is more than 2 times that of its passive companion. By generating a stellar mass-matched ("twinned") sample in TNG300-1, we show that differences in sSFR trends between companion types are not a result of intrinsic stellar mass differences in star-forming vs. passive galaxies. We compare with an analogous sample of galaxy pairs from SDSS, finding consistent results between observations and simulations. Overall, we find that star-forming galaxies show enhanced sSFRs regardless of companion type, but that galaxies with close passive companions are more likely to be passive themselves.

The kinematic disturbances associated with major galaxy mergers are known to produce gas inflows, which in turn may trigger accretion onto the supermassive black holes (SMBH) of the participant galaxies. While this effect has been studied in galaxy pairs, the frequency of active galactic nuclei (AGN) in fully coalesced post-merger systems is poorly constrained due to the limited size or impurity of extant post-merger samples. Previously, we combined convolutional neural network (CNN) predictions with visual classifications to identify a highly pure sample of 699 post-mergers in deep r-band imaging. In the work presented here, we quantify the frequency of AGN in this sample using three metrics: optical emission lines, mid-infrared (mid- IR) colour, and radio detection of low-excitation radio galaxies (LERGs). We also compare the frequency of AGN in post-mergers to that in a sample of spectroscopically identified galaxy pairs. We find that AGN identified by narrow-line optical emission and mid-IR colour have an increased incidence rate in post-mergers, with excesses of ~4 over mass- and redshift-matched controls. The optical and mid-IR AGN excesses in post-mergers exceed the values found for galaxy pairs, indicating that AGN activity in mergers peaks after coalescence. Conversely, we recover no significant excess of LERGs in post-mergers or pairs. Finally, we find that the [OIII] luminosity (a proxy for SMBH accretion rate) in post-mergers that host an optical AGN is ~0.3 dex higher on average than in non-interacting galaxies with an optical AGN, suggesting that mergers generate higher accretion rates than secular triggering mechanisms.

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.

ABSTRACT Galaxy mergers are known to trigger both extended and central star formation. However, what remains to be understood is whether this triggered star formation is facilitated by enhanced star formation efficiencies (SFEs), or an abundance of molecular gas fuel. This work presents spatially resolved measurements of CO emission collected with the Atacama Large Millimetre Array (ALMA) for 20 merging galaxies (either pairs or post-mergers) selected from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. Eleven additional merging galaxies are selected from the ALMA MaNGA QUEnching and STar formation (ALMaQUEST) survey, resulting in a set of 31 mergers at various stages of interaction and covering a broad range of star formation rates (SFRs). We investigate galaxy-to-galaxy variations in the resolved Kennicutt–Schmidt relation, (rKS: $\Sigma _{\textrm {H}_2}$ versus ΣSFR), the resolved molecular gas main sequence (rMGMS: Σ⋆ versus $\Sigma _{\textrm {H}_2}$), and the resolved star-forming main sequence (rSFMS: Σ⋆ versus ΣSFR). We quantify offsets from these resolved relations to determine if SFR, molecular gas fraction, or/and SFE is/are enhanced in different regions of an individual galaxy. By comparing offsets in all three parameters, we can discern whether gas fraction or SFE powers an enhanced ΣSFR. We find that merger-induced star formation can be driven by a variety of mechanisms, both within a galaxy and between different mergers, regardless of interaction stage.

The importance of the post-merger epoch in galaxy evolution has been well-documented, but post-mergers are notoriously difficult to identify. While the features induced by mergers can sometimes be distinctive, they are frequently missed by visual inspection. In addition, visual classification efforts are highly inefficient because of the inherent rarity of post-mergers (~1% in the low-redshift Universe), and non-parametric statistical merger selection methods do not account for the diversity of post-mergers or the environments in which they appear. To address these issues, we deploy a convolutional neural network (CNN) which has been trained and evaluated on realistic mock observations of simulated galaxies from the IllustrisTNG simulations, to galaxy images from the Canada France Imaging Survey (CFIS), which is part of the Ultraviolet Near Infrared Optical Northern Survey (UNIONS). We present the characteristics of the galaxies with the highest CNN-predicted post-merger certainties, as well as a visually confirmed subset of 699 post-mergers. We find that post-mergers with high CNN merger probabilities (p(x)>0.8) have an average star formation rate that is 0.1 dex higher than a mass- and redshift-matched control sample. The SFR enhancement is even greater in the visually confirmed post-merger sample, a factor of two higher than the control sample.

Galaxy mergers trigger both star formation and accretion onto the central supermassive black hole. As a result of subsequent energetic feedback processes, it has long been proposed that star formation may be promptly extinguished in galaxy merger remnants. However, this prediction of widespread, rapid quenching in late stage mergers has been recently called into question with modern simulations and has never been tested observationally. Here we perform the first empirical assessment of the long-predicted end phase in the merger sequence. Based on a sample of 500 post-mergers identified from the Ultraviolet Near Infrared Optical Northern Survey (UNIONS), we show that the frequency of post-merger galaxies that have rapidly shutdown their star formation following a previous starburst is 30-60 times higher than expected from a control sample of non-merging galaxies. No such excess is found in a sample of close galaxy pairs, demonstrating that mergers can indeed lead to a rapid halt to star formation, but that this process only manifests after coalescence.