Understanding Of Galaxy Evolution Research Articles

Unveiling the formation channels of stellar halos through their chemical fingerprints

Stellar halos around galaxies contain key information about their formation and assembly history. Using simulations, we can trace the origins of different stellar populations in these halos, contributing to our understanding of galaxy evolution. We aim to investigate the assembly of stellar halos and their chemical abundances in 28 galaxies from cosmological hydrodynamical zoom-in simulations, spanning a broad range of stellar masses, $ Stellar halos were identified using the AM-E method, focusing on the outer regions between the 1.5 optical radius and the virial radius. We divided the stellar populations based on their formation channel: ex-situ, endo-debris, and in-situ, and analyzed their chemical abundances, ages, and spatial distributions. Additionally, we explored correlations between halo mass, metallicity, and alpha-element enrichment. simulations reveal that stellar halos are predominantly composed of accreted material, including both ex-situ and endo-debris stars, in agreement with previous works. The mass fraction of these populations is independent of stellar halo mass, though their metallicities scale linearly with it. Ex-situ stars tend to dominate the outskirts and be more alpha -rich and older, while endo-debris stars are more prevalent at lower radii and tend to be less alpha -rich and slightly younger. Massive stellar halos ($ require a median of five additional satellites to build 90<!PCT!> of their mass, compared to lower-mass halos, which typically need fewer (median of 2.5) and lower-mass satellites and are assembled earlier. The diversity of accreted satellite histories results in well-defined stellar halo mass-metallicity and alpha /Fe Fe/H relations, offering a detailed view of the chemical evolution and assembly history of stellar halos. We find that the alpha /Fe Fe/H is more sensitive to the characteristics and star formation history of the contributing satellites than the stellar halo mass-metallicity relationship.

Identification of ram pressure stripping features in galaxies using citizen science

Our aim is to explore the efficacy of citizen science classifications in identifying ram pressure stripped galaxies, and use this to aid in motivating new potential samples of ram pressure stripped candidates. We compiled a sample of over 200 known ram pressure stripped galaxies from the existing literature, with morphological classifications obtained from Galaxy Zoo. We compared these galaxies with magnitude and redshift-matched comparison cluster and field galaxies. Additionally, we created a sample of SDSS cluster galaxies, with morphological classifications similar to known ram pressure stripped galaxies, and compared the fraction of potential new RPS candidates against control samples. We find that ram pressure stripped galaxies exhibit a higher proportion of `odd' and `irregular' morphological classifications compared to field and cluster comparison samples. This trend is particularly pronounced in galaxies displaying strong optical ram pressure stripping features, but absent from galaxies with only radio tails. We find that SDSS galaxies with Galaxy Zoo classifications consistent with the known RPS galaxies have a higher fraction of visible ram pressure stripping features ($19<!PCT!>$) compared with other cluster galaxies ($12<!PCT!>$) when classified by experts. We identify 101 new ram pressure stripping candidate galaxies through these expert classifications. We demonstrate that indirect morphological classifications from citizen science projects can increase the efficiency with which new stripping candidates are found. Projects such as Galaxy Zoo can aid in the identification of ram pressure stripped galaxies that are key to understanding galaxy evolution in clusters.

Morphologies of galaxies within voids

Among the largest structures in which matter is distributed in the Universe, we find cosmic voids, which are large, under-dense regions almost devoid of galaxies. The study of these structures and the galaxies that inhabit them, the void galaxies, provides key information for understanding galaxy evolution. In this work we investigate the effects of the environment on the evolution of void galaxies. In particular, we study their morphology and explore its dependence on the location within the void where the galaxies reside, as well as on the properties of the void, such as its size and the galaxy number density. The sample of void galaxies that we use in this study is based on the catalogue of cosmic voids and void galaxies in the Sloan Digital Sky Survey Data Release 7 (SDSS-DR7). As we are interested in studying the morphology of void galaxies, we select galaxies in the redshift range of 0.005\,leq \,z\,leq \,0.080, and use the public galaxy morphologies of the SDSS sample together with deep learning algorithms to divide the sample into early- and late-type void galaxies. We analyse the fractions of galaxies of each morphological type as a function of the void-centric distance, the size of the voids, and the density of galaxies in each void. There is a higher abundance of late-type galaxies with respect to early-type galaxies within voids, which remains nearly constant from the inner to the outer part of the voids. We do not find any dependence of the fraction of early- and late-type galaxies on void size or on the number-density of galaxies in the voids. Galaxies in voids follow the morphology--density relation, in the sense that the majority of the galaxies in voids (the most under-dense large-scale environments) are late-type galaxies. However, we find no difference between voids with lower or higher volume number-density of galaxies: the fractions of early- and late-type galaxies do not depend on the density of the voids. The physical processes responsible for the evolution from late towards earlier types (such as external environmental quenching) are not sufficiently effective in voids or are so slow (internal secular quenching) that their contributions do not appear in the morphology--density relation.

Mergers, Radio Jets, and Quenching Star Formation in Massive Galaxies: Quantifying Their Synchronized Cosmic Evolution and Assessing the Energetics

The existence of a population of massive quiescent galaxies with little to no star formation poses a challenge to our understanding of galaxy evolution. The physical process that quenched the star formation in these galaxies is debated, but the most popular possibility is that feedback from supermassive black holes lifts or heats the gas that would otherwise be used to form stars. In this paper, we evaluate this idea in two ways. First, we compare the cumulative growth in the cosmic inventory of the total stellar mass in quiescent galaxies to the corresponding growth in the amount of kinetic energy carried by radio jets. We find that these two inventories are remarkably well-synchronized, with about 50% of the total amounts being created in the epoch from z ≈ 1 to 2. We also show that these agree extremely well with the corresponding growth in the cumulative number of major mergers that result in massive (>1011 M ʘ) galaxies. We therefore argue that major mergers trigger the radio jets and also transform the galaxies from disks to spheroids. Second, we evaluate the total amount of kinetic energy delivered by jets and compare it to the baryonic binding energy of the galaxies. We find the jet kinetic energy is more than sufficient to quench star formation, and the quenching process should be more effective in more massive galaxies. We show that these results are quantitatively consistent with recent measurements of the Sunyaev–Zel’dovich effect seen in massive galaxies at z ≈ 1.

Euclid preparation

The Euclid space mission will cover over 14 000 deg2 with two optical and near-infrared spectro-photometric instruments, and is expected to detect around ten million active galactic nuclei (AGN). This unique data set will make a considerable impact on our understanding of galaxy evolution in general, and AGN in particular. For this work we identified the best colour selection criteria for AGN, based only on Euclid photometry or including ancillary photometric observations, such as the data that will be available with the Rubin Legacy Survey of Space and Time (LSST) and observations already available from Spitzer/IRAC. The analysis was performed for unobscured AGN, obscured AGN, and composite (AGN and star-forming) objects. We made use of the spectro-photometric realisations of infrared-selected targets at all-z (SPRITZ) to create mock catalogues mimicking both the Euclid Wide Survey (EWS) and the Euclid Deep Survey (EDS). Using these mock catalogues, we estimated the best colour selection, maximising the harmonic mean (F1) of: (a) completeness, that is, the fraction of AGN correctly selected with respect to the total AGN sample; and (b) purity, that is, the fraction of AGN inside the selection with respect to the selected sample. The selection of unobscured AGN in both Euclid surveys (Wide and Deep) is possible with Euclid photometry alone with F1 = 0.22–0.23 (Wide and Deep), which can increase to F1 = 0.43–0.38 (Wide and Deep) if we limit out study to objects at z > 0.7. Such a selection is improved once the Rubin/LSST filters, that is, a combination of the u, g, r, or z filters, are considered, reaching an F1 score of 0.84 and 0.86 for the EDS and EWS, respectively. The combination of a Euclid colour with the [3.6]−[4.5] colour, which is possible only in the EDS, results in an F1 score of 0.59, improving the results using only Euclid filters, but worse than the selection combining Euclid and LSST colours. The selection of composite (fAGN = 0.05–0.65 at 8–40 μm) and obscured AGN is challenging, with F1 ≤ 0.3 even when including Rubin/LSST or IRAC filters. This is unsurprising since it is driven by the similarities between the broad-band spectral energy distribution of these AGN and star-forming galaxies in the wavelength range 0.3–5 μm.

Exploring the Central Region of NGC 1365 in the Ultraviolet Domain

Active galactic nuclei (AGN) feedback and its impact on their host galaxies are critical to our understanding of galaxy evolution. Here, we present a combined analysis of new high resolution ultraviolet (UV) data from the Ultraviolet Imaging Telescope (UVIT) on AstroSat and archival optical spectroscopic data from the Very Large Telescope/MUSE, for the Seyfert galaxy, NGC 1365. Concentrating on the central 5 kpc region, the UVIT images in the far- and near-UV show bright star-forming knots in the circumnuclear ring as well as a faint central source. After correcting for extinction, we found the star formation rate (SFR) surface density of the circumnuclear 2 kpc ring to be similar to other starbursts, despite the presence of an AGN outflow, as seen in [O iii] 5007 Å. On the other hand, we found fainter UV and thus lower SFR in the direction southeast of the AGN relative to northwest in agreement with observations at other wavelengths from JWST and Atacama Large Millimeter/submillimeter Array. The AGN outflow velocity is found to be lesser than the escape velocity, suggesting that the outflowing gas will rain back into the galaxy. The deep UV data have also revealed diffuse UV emission in the direction of the AGN outflow. By combining [O iii] and UV data, we found the diffuse emission to be of AGN origin.

A Break in the Size–Stellar Mass Relation: Evidence for Quenching and Feedback in Dwarf Galaxies

Mapping stars and gas in nearby galaxies is fundamental for understanding their growth and the impact of their environment. This issue is addressed by comparing the stellar “edges” of galaxies D stellar, defined as the outermost diameter where in situ star formation significantly drops, with the gaseous distribution parameterized by the neutral atomic hydrogen diameter measured at 1 M ⊙ pc−2, D HI. By sampling a broad H i mass range 105 M ⊙ < M HI < 1011 M ⊙, we find several dwarf galaxies with M HI < 109 M ⊙ from the field and Fornax Cluster that are distinguished by D stellar ≫ D HI. For the cluster dwarfs, the average H i surface density near D stellar is ∼0.3 M ⊙ pc−2, reflecting the impact of quenching and outside-in gas removal from ram pressure and tidal interactions. In comparison, D stellar/D HI ranges between 0.5 and 2 in dwarf field galaxies, consistent with the expectations from stellar feedback. Only more massive disk galaxies in the field can thus be characterized by the common assumption that D stellar ≲ D HI. We discover a break in the D stellar–M ⋆ relation at m break ∼ 4 × 108 M ⊙ that potentially differentiates the low-mass regime, where the influence of stellar feedback and environmental processes more prominently regulates the sizes of nearby galaxies. Our results highlight the importance of combining deep optical and H i imaging for understanding galaxy evolution.

Validating full-spectrum fitting with a synthetic integral-field spectroscopic observation of the milky way

Abstract Ongoing deep IFS observations of disk galaxies provide opportunities for comparison with the Milky Way (MW) to understand galaxy evolution. However, such comparisons are marred by many challenges such as selection effects, differences in observations and methodology, and proper validation of full-spectrum fitting methods. In this study, we present a novel code GalCraft to address these challenges by generating mock IFS data cubes of the MW using simple stellar population models and a mock MW stellar catalog derived from E-Galaxia. We use the widely adopted full-spectrum fitting code pPXF to investigate the ability to recover kinematics and stellar populations for an edge-on mock MW IFS observation. We confirm that differences in kinematics, mean age, [M/H], and [α/Fe] between thin and thick disks can be distinguished. However, the age distribution is overestimated in the ranges between 2 − 4 and 12 − 14 Gyr compared to the expected values. This is likely due to the age spacing and degeneracy of SSP templates. We find systematic offsets in the recovered kinematics due to insufficient spectral resolution and the variation of line-of-sight velocity distribution with age and [M/H]. With future higher resolution and multi-[α/Fe] SSP templates, GalCraft will be useful to validate key signatures such as [α/Fe]-[M/H] distribution at different R and |z| and potentially infer radial migration and kinematic heating efficiency to study detailed chemodynamical evolution of MW-like galaxies.

The H i Reservoir in Central Spiral Galaxies and the Implied Star Formation Process ∗ ∗ This is the fourth paper in the “From Halos to Galaxies” series.

The cold interstellar medium (ISM) as the raw material for star formation is critical to understanding galaxy evolution. It is generally understood that galaxies stop making stars when, in one way or another, they run out of gas. However, here we provide evidence that central spiral galaxies remain rich in atomic gas even if their star formation rate (SFR) and molecular gas fraction have dropped significantly compared to “normal” star-forming galaxies of the same mass. Since H i is sensitive to external processes, here we investigate central spiral galaxies using a combined sample from the Sloan Digital Sky Survey, Arecibo Legacy Fast ALFA survey, and the extended GALEX Arecibo SDSS Survey. After proper incompleteness corrections, we find that the key H i scaling relations for central spirals show significant but regular systematic dependence on stellar mass. At any given stellar mass, the H i gas mass fraction is about constant with changing specific star formation rate (sSFR), which suggests that H i reservoir is ubiquitous in central spirals with any star formation status down to M * ∼ 109 M ⊙. Together with the tight correlation between the molecular gas mass fraction and sSFR for galaxies across a wide range of different properties, it suggests that the decline of SFR of all central spirals in the local Universe is due to the halt of H2 supply, though there is plenty of H i gas around. These hence provide critical observations of the dramatically different behavior of the cold multiphase ISM, and a key to understand the star formation process and quenching mechanism.

SDSS-IV MaNGA: Stellar rotational support in disk galaxies vs. central surface density and stellar population age

Abstract We investigate how the stellar rotational support changes as a function of spatially resolved stellar population age ($\rm D_n4000$) and relative central stellar surface density (ΔΣ1) for MaNGA isolated/central disk galaxies. We find that the galaxy rotational support indicator $\lambda _{R_\mathrm{e}}$ varies smoothly as a function of ΔΣ1 and $\rm D_n4000$. $\rm D_n4000$ vs. ΔΣ1 follows a ‘J-shape’, with $\lambda _{R_\mathrm{e}}$ contributing to the scatters. In this ‘J-shaped’ pattern rotational support increases with central $\rm D_n4000$ when ΔΣ1 is low but decreases with ΔΣ1 when ΔΣ1 is high. Restricting attention to low-ΔΣ1 (i.e, large-radius) galaxies, we suggest that the trend of increasing rotational support with $\rm D_n4000$ for these objects is produced by a mix of two different processes, a primary trend characterized by growth in $\lambda _{R_\mathrm{e}}$ along with mass through gas accretion, on top of which disturbance episodes are overlaid, which reduce rotational support and trigger increased star formation. An additional finding is that star forming galaxies with low ΔΣ1 have relatively larger radii than galaxies with higher ΔΣ1 at fixed stellar mass. Assuming that these relative radii rankings are preserved while galaxies are star forming then implies clear evolutionary paths in central $\rm D_n4000$ vs. ΔΣ1. The paper closes with comments on the implications that these paths have for the evolution of pseudo-bulges vs. classical-bulges. The utility of using $\rm D_n4000$-ΔΣ1 to study $\lambda _{R_\mathrm{e}}$ reinforces the notion that galaxy kinematics correlate both with structure and with stellar-population state, and indicates the importance of a multi-dimensional description for understanding bulge and galaxy evolution.

The Radio Galaxy Environment Reference Survey (RAGERS): a submillimetre study of the environments of massive radio-quiet galaxies at z = 1–3

ABSTRACT Measuring the environments of massive galaxies at high redshift is crucial to understanding galaxy evolution and the conditions that gave rise to the distribution of matter we see in the Universe today. While high-z radio galaxies (HzRGs) and quasars tend to reside in protocluster-like systems, the environments of their radio-quiet counterparts are relatively unexplored, particularly in the submillimetre, which traces dust-obscured star formation. In this study, we search for 850 μm-selected submillimetre galaxies (SMGs) in the environments of massive ($M_{\star }$$\gt 10^{11}$${\rm M}_{\odot }$), radio-quiet ($L_{500 {\rm MHz}}$$\lesssim 10^{25}$ WHz$^{-1}$) galaxies at $z \sim 1\!-\!3$ using data from the SCUBA-2 COSMOS (S2COSMOS) survey. By constructing number counts in circular regions of radius 1–6 arcmin and comparing with blank-field measurements, we find no significant overdensities of SMGs around massive radio-quiet galaxies at any of these scales, despite being sensitive down to overdensities of $\delta \sim 0.4$. To probe deeper than the catalogue we also examine the distribution of peaks in the SCUBA-2 signal-to-noise (SNR) map, which reveals only tentative signs of any difference in the SMG densities of the radio-quiet galaxy environments compared to the blank field, and only on smaller scales (1 arcmin radii, corresponding to $\sim 0.5$ Mpc) and higher SNR thresholds. We conclude that massive, radio-quiet galaxies at cosmic noon are typically in environments with $\delta \lesssim 0.4$, which are either consistent with the blank field or contain only weak overdensities spanning sub-Mpc scales. The contrast between our results and studies of HzRGs with similar stellar masses and redshifts implies an intrinsic link between the wide-field environment and the radio luminosity of the active galactic nucleus at high redshift.

Automatic Search for Low-surface-brightness Galaxies from Sloan Digital Sky Survey Images Using Deep Learning

Low-surface-brightness (LSB) galaxies play a crucial role in our understanding of galaxy evolution and dark matter cosmology. However, efficiently detecting them in large-scale surveys is challenging, due to their dim appearance. In this study, we propose a two-step detection method based on deep learning to address this issue. First, an object detection model called GalCenterNet was designed to detect LSB galaxy candidates in astronomical images. The model was trained using a data set of 665 Sloan Digital Sky Survey (SDSS) images, which contained 667 LSB galaxies. On the test set, the model achieved an accuracy of 95.05% and a recall of 96.00%. Next, an anomaly detection technique known as Deep Support Vector Data Description was applied to identify abnormal sources, thus refining the LSB candidates. By applying the two-step detection method to SDSS images, we have obtained a sample of 37,536 LSB galaxy candidates. This wide-area sample contains diverse and abundant LSB galaxies, which are valuable for studying the properties of LSB galaxies and the role that the environment plays in their evolution. The proposed detection method enables end-to-end detection from the SDSS images to the final detection results. This approach will be further employed to efficiently identify objects in the upcoming Chinese Survey Space Telescope sky survey.

The Correlation Luminosity-Velocity Dispersion of Galaxies and Active Galactic Nuclei

In this work we discuss the correlation between luminosity L and velocity dispersion σ observed in different astrophysical contexts, in particular that of early-type galaxies (ETGs; Faber–Jackson (FJ) law) and that of active galactic nuclei (AGN). Our data for the ETGs confirm the bending of the FJ at high masses and the existence of similar curvatures in the projections of the Fundamental Plane (FP) approximately at the mass scale of ∼1010M⊙. We provide an explanation for such curvatures and for the presence of the Zone of Exclusion (ZoE) in these diagrams. The new prospected theory for the FJ law introduces a new framework to understand galaxy evolution in line with the hierarchical structure of the Universe. The classic analysis carried out for a class of type 1 AGN accreting gas at very high rates, confirms that a FJ law of the form L=L0σ4 is roughly consistent with the observations, with a slope quite similar to that of ETGs. We discuss the physics behind the FJ law for the AGN in different contexts and also examine the biases affecting both the luminosity and the velocity dispersion, paying particular attention to the effects induced by the spherical symmetry of the emitting sources on the accuracy of the luminosity estimates.

NGC 1856: Using Machine Learning Techniques to Uncover Detailed Stellar Abundances from MUSE Data

We present the first application of the novel approach based on data-driven machine learning methods applied to Multi-Unit Spectroscopic Explorer (MUSE) field data to derive stellar abundances of star clusters. MUSE has been used to target more than 10,000 fields, and it is unique in its ability to study dense stellar fields such as stellar clusters providing spectra for each individual star. We use MUSE data of the extragalactic young stellar cluster NGC 1856, located in the Large Magellanic Cloud (LMC). We present the individual stellar [Fe/H] abundance of 327 cluster members in addition to [Mg/Fe], [Si/Fe], [Ti/Fe], [C/Fe], [Ni/Fe], and [Cr/Fe] abundances of subsample sets. Our results match the LMC abundances obtained in the literature for [Mg/Fe], [Ti/Fe], [Ni/Fe], and [Cr/Fe]. This study is the first to derive [Si/Fe] and [C/Fe] abundances for this cluster. The revolutionary combination of integral-field spectroscopy and data-driven modeling will allow us to understand the chemical enrichment of star clusters and their host galaxies in greater detail expanding our understanding of galaxy evolution.

H i discs of L* galaxies as probes of the baryonic physics of galaxy evolution

ABSTRACT Understanding what shapes the cold gas component of galaxies, which both provides the fuel for star formation and is strongly affected by the subsequent stellar feedback, is a crucial step towards a better understanding of galaxy evolution. Here, we analyse the H i properties of a sample of 46 Milky Way halo-mass galaxies, drawn from cosmological simulations (EMP-Pathfinder and Firebox). This set of simulations comprises galaxies evolved self-consistently across cosmic time with different baryonic sub-grid physics: three different star formation models [constant star formation efficiency (SFE) with different star formation eligibility criteria, and an environmentally dependent, turbulence-based SFE] and two different feedback prescriptions, where only one sub-sample includes early stellar feedback. We use these simulations to assess the impact of different baryonic physics on the H i content of galaxies. We find that the galaxy-wide H i properties agree with each other and with observations. However, differences appear for small-scale properties. The thin H i discs observed in the local universe are only reproduced with a turbulence-dependent SFE and/or early stellar feedback. Furthermore, we find that the morphology of H i discs is particularly sensitive to the different physics models: galaxies simulated with a turbulence-based SFE have discs that are smoother and more rotationally symmetric, compared to those simulated with a constant SFE; galaxies simulated with early stellar feedback have more regular discs than supernova-feedback-only galaxies. We find that the rotational asymmetry of the H i discs depends most strongly on the underlying physics model, making this a promising observable for understanding the physics responsible for shaping the interstellar medium of galaxies.

A JWST investigation into the bar fraction at redshifts 1 ≤ z ≤ 3

ABSTRACT The presence of a stellar bar in a disc galaxy indicates that the galaxy hosts in its main part a dynamically settled disc and that bar-driven processes are taking place in shaping its evolution. Studying the cosmic evolution of the bar fraction in disc galaxies is therefore essential to understand galaxy evolution in general. Previous studies have found, using the Hubble Space Telescope (HST), that the bar fraction significantly declines from the local Universe to redshifts near one. Using the first four pointings from the JWST Cosmic Evolution Early Release Science Survey and the initial public observations for the Public Release Imaging for Extragalactic Research, we extend the studies of the bar fraction in disc galaxies to redshifts 1 ≤ $z$ ≤ 3, that is, for the first time beyond redshift two. We only use galaxies that are also present in the Cosmic Assembly Near-IR Deep Extragalactic Legacy Survey on the Extended Groth Strip and Ultra Deep Survey HST observations. An optimized sample of 368 close-to-face-on galaxies is visually classified to find the fraction of bars in disc galaxies in two redshift bins: 1 ≤ $z$ ≤ 2 and 2 &amp;lt; $z$ ≤ 3. The bar fraction decreases from $\approx 17.8^{+ 5.1}_{- 4.8}$ per cent to $\approx 13.8^{+ 6.5}_{- 5.8}$ per cent (from the lower to the higher redshift bin), but is about twice the bar fraction found using bluer HST filters. Our results show that bar-driven evolution might commence at early cosmic times and that dynamically settled discs are already present at a lookback time of ∼11 Gyr.

Pre-supernova stellar feedback in nearby starburst dwarf galaxies

Stellar feedback in dwarf galaxies remains, to date, poorly explored, yet is crucial to understanding galaxy evolution in the early Universe. In particular, pre-supernova feedback has recently been found to play a significant role in regulating and disrupting star formation in larger spiral galaxies, but it remains uncertain if it also plays this role in dwarfs. We study the ionised gas properties and stellar content of individual star-forming regions across three nearby, low-metallicity ($12+ O/H 7.5$), dwarf ($M_* odot $), starburst ($ SFR -2.8$) galaxies (J0921, KKH046, and Leo P) to investigate how massive stars influence their surroundings and how this influence changes as a function of environment. We extracted integrated spectra of 30 HII regions from archival VLT/MUSE integral field spectroscopic observations of these three dwarf starburst galaxies. We fitted the HII regions' main emission lines with Gaussian profiles to derive their oxygen abundances, electron densities, and luminosities, and we used the Stochastically Ligthing Up Galaxies ( SLUG ) code to derive the stellar mass, age, and bolometric luminosity of the stellar populations driving the HII regions. We quantified two pre-supernova stellar feedback mechanisms, namely the direct radiation pressure and photoionisation feedback, and explored how feedback strength varies with HII region properties. Our findings suggest that stellar feedback has less of an impact on evolved regions, with both the pressure of the ionised gas and the direct radiation pressure decreasing as a function of HII region size (i.e. the evolutionary stage). We find that these stellar feedback mechanisms are also dependent on the metallicity of the HII regions. These findings extend results from stellar feedback studies of more massive star-forming galaxies to the low-mass, low-metallicity regime. In addition, we conclude that the use of stochastic stellar population models significantly affects the relationships found between feedback-related pressure terms and HII region properties, and in particular that non-stochastic models can severely underestimate the bolometric luminosity of low-mass stellar populations.

Shedding light on low-surface-brightness galaxies in dark energy surveys with transformer models

Context. Low-surface-brightness galaxies (LSBGs), which are defined as galaxies that are fainter than the night sky, play a crucial role in our understanding of galaxy evolution and in cosmological models. Upcoming large-scale surveys, such as Rubin Observatory Legacy Survey of Space and Time and Euclid, are expected to observe billions of astronomical objects. In this context, using semiautomatic methods to identify LSBGs would be a highly challenging and time-consuming process, and automated or machine learning-based methods are needed to overcome this challenge. Aims. We study the use of transformer models in separating LSBGs from artefacts in the data from the Dark Energy Survey (DES) Data Release 1. Using the transformer models, we then search for new LSBGs from the DES that the previous searches may have missed. Properties of the newly found LSBGs are investigated, along with an analysis of the properties of the total LSBG sample in DES. Methods. We created eight different transformer models and used an ensemble of these eight models to identify LSBGs. This was followed by a single-component Sérsic model fit and a final visual inspection to filter out false positives. Results. Transformer models achieved an accuracy of ~94% in separating the LSBGs from artefacts. In addition, we identified 4083 new LSBGs in DES, adding an additional ~17% to the LSBGs already known in DES. This also increased the number density of LSBGs in DES to 5.5 deg−2. The new LSBG sample consists of mainly blue and compact galaxies. We performed a clustering analysis of the LSBGs in DES using an angular two-point auto-correlation function and found that LSBGs cluster more strongly than their high-surface-brightness counterparts. This effect is driven by the red LSBG. We associated 1310 LSBGs with galaxy clusters and identified 317 ultradiffuse galaxies among them. We found that these cluster LSBGs are getting bluer and larger in size towards the edge of the clusters when compared with those in the centre. Conclusions. Transformer models have the potential to be equivalent to convolutional neural networks as state-of-the-art algorithms in analysing astronomical data. The significant number of LSBGs identified from the same dataset using a different algorithm highlights the substantial impact of our methodology on our capacity to discover LSBGs. The reported number density of LSBGs is only a lower estimate and can be expected to increase with the advent of surveys with better image quality and more advanced methodologies.

Star Formation Efficiency in Nearby Galaxies Revealed with a New CO-to-H2 Conversion Factor Prescription

Determining how the galactic environment, especially the high gas densities and complex dynamics in bar-fed galaxy centers, alters the star formation efficiency (SFE) of molecular gas is critical to understanding galaxy evolution. However, these same physical or dynamical effects also alter the emissivity properties of CO, leading to variations in the CO-to-H2 conversion factor (α CO) that impact the assessment of the gas column densities and thus of the SFE. To address such issues, we investigate the dependence of α CO on the local CO velocity dispersion at 150 pc scales using a new set of dust-based α CO measurements and propose a new α CO prescription that accounts for CO emissivity variations across galaxies. Based on this prescription, we estimate the SFE in a sample of 65 galaxies from the PHANGS–Atacama Large Millimeter/submillimeter Array survey. We find increasing SFE toward high-surface-density regions like galaxy centers, while using a constant or metallicity-based α CO results in a more homogeneous SFE throughout the centers and disks. Our prescription further reveals a mean molecular gas depletion time of 700 Myr in the centers of barred galaxies, which is overall three to four times shorter than in nonbarred galaxy centers or the disks. Across the galaxy disks, the depletion time is consistently around 2–3 Gyr, regardless of the choice of α CO prescription. All together, our results suggest that the high level of star formation activity in barred centers is not simply due to an increased amount of molecular gas, but also to an enhanced SFE compared to nonbarred centers or disk regions.

Deep learning prediction of galaxy stellar populations in the low-redshift Universe

ABSTRACT The increasing size and complexity of data provided by both ongoing and planned galaxy surveys greatly contribute to our understanding of galaxy evolution. Deep learning methods are particularly well suited for handling the complex and massive data. We train a convolutional neural network (CNN) to simultaneously predict the stellar populations in galaxies: age, metallicity, colour excess E(B − V), and central velocity dispersion (VD) using spectra with redshift ≤ 0.3 from the Sloan Digital Sky Survey. This is the first time to use spectra based on deep learning to derive the four galaxy properties. The testing results show that our CNN predictions of galaxy properties are in good consistent with values by the traditional stellar population synthesis method with little scatters (0.11 dex for age and metallicity, 0.018 mag for E(B − V), and 31 km s−1 for VD). In terms of the computational time, our method reduces by more than 10 times compared to traditional method. We further evaluate the performance of our CNN prediction model using spectra with different signal-to-noise ratios (S/Ns), redshifts, and spectral classes. We find that our model generally exhibits good performance, although the errors at different S/Ns, redshifts, and spectral classes vary slightly. Our well-trained CNN model and related codes are publicly available on https://github.com/sddzwll/CNNforStellarp.