The Role of Tidal Interactions and Mergers on the Evolution of Intermediate Redshift Galaxies

In this work, we present our analysis attempting to constrain the prevalence of tidal interaction and merger (TIM) events on the evolution of intermediate redshift galaxies. The main focus of this work is the effect of such events on the star formation properties of galaxies. Such an undertaking requires the precise selection of tidal interactions and mergers (TIMs), in a wide range of environments to account for environmental effects. As such, in the first part of this work we study the fraction of tidal interactions and mergers with well identified observability timescales ($f_{\rm TIM}$) in group, cluster, and accompanying field galaxies and its dependence on redshift ($z$), cluster velocity dispersion ($\sigma$), and environment. We analyze images from the Hubble Space Telescope (HST), and catalogs from the ESO Distant Cluster Survey (EDisCS) for our work. Our data sample consists of 11 clusters, 7 groups, and accompanying field galaxies at $0.4 \leq z \leq 0.8$. We select our TIM sample using both a visual classification of galaxy morphologies and an automated method, the $G-M_{20}$ method. We calibrate this method using the visual classifications that were performed on a subset of our sample. After this calibration, we label visual TIMs also picked by our $G-M_{20}$ selection criterion as \textquotedblleft $G-M_{20}$ TIM \textquotedblright, and gather our visually undisturbed galaxies plus the visual TIMs that are not $G-M_{20}$ selected under the \textquotedblleft undisturbed \textquotedblright label. Our tests indicate that these subpopulations are well-seperated in the $G-M_{20}$ space, and that our results are robust against different $G-M_{20}$ TIM selection criteria. Next, we investigate whether the fraction of $G-M_{20}$ TIMs, or $f_{\rm TIM}$, shows any strong trends with redshift ($z$), cluster velocity dispersion ($\sigma$), and the global environment the in which our galaxies reside. We find marginal evidence for a trend between $f_{\rm TIM}$ and $z$, in that higher $z$ values correspond to higher $f_{\rm TIM}$. However, we also cannot rule out the null hypothesis of no correlation at higher than 68\% confidence. No trend is present between $f_{\rm TIM}$ and $\sigma$. We find that $f_{\rm TIM}$ shows suggestive peaks in groups, and tentatively in clusters at $R > 0.5\times R_{200}$, implying that $f_{\rm TIM}$ gets boosted in these intermediate density environments. However, our analysis of the local densities of our cluster sample does not reveal a trend between $f_{\rm TIM}$ and density, except for a potential enhancement at the very highest densities. We also perform an analysis of projected radius-velocity phase space for our cluster members. Our results reveal that tidal interactions and mergers (TIM), and undisturbed galaxies only have a 6\% probability of having been drawn from the same parent population in their velocity distribution and 37\% in radii, in agreement with the modest differences obtained in $f_{\rm TIM}$ at the clusters. After classifying our sample into $G-M_{20}$ TIMs and undisturbed galaxies, we investigate the stellar populations of our sample. To this purpose, we perform a full spectral fitting on the deep EDisCS spectroscopy data. We use the publicly available pPXF code for the spectral fitting, obtaining the details of the stellar populations, and the gas present in our sample, as results of our spectral fitting. We extract the fraction of the total stellar mass contained in stellar populations of different ages in our sample from this information. We also derive age-sensitive spectral indices, the strength of the narrow 4000\mbox{\AA} break strength, $D_{n,4000}$, and the Balmer H$\mathrm{\delta}$ absorption line index using the results of the spectral fitting. The final part of our analysis attempts to combine our morphological analysis, and our stellar population analysis. We search for trends in our $G-M_{20}$ TIMs and undisturbed galaxies with respect to the ages of their stellar populations. We find that our $G-M_{20}$ TIM galaxies are predominantly star-forming, as derived from multi-band photometric data. A larger fraction of the $G-M_{20}$ TIM galaxies also have features in their galaxy spectra indicating that their light is dominated by young stars. We then analyze the mass-weighted age fractions in the last 0.5 Gyr (f_{Age 0.5\times R_{200}, implying that $f_{\rm TIM}$ gets boosted in these intermediate density environments. However, our analysis of the local densities of our cluster sample does not reveal a trend between $f_{\rm TIM}$ and density, except for a potential enhancement at the very highest densities. We also perform an analysis of projected radius-velocity phase space for our cluster members. Our results reveal that tidal interactions and mergers (TIM), and undisturbed galaxies only have a 6\% probability of having been drawn from the same parent population in their velocity distribution and 37\% in radii, in agreement with the modest differences obtained in $f_{\rm TIM}$ at the clusters. After classifying our sample into $G-M_{20}$ TIMs and undisturbed galaxies, we investigate the stellar populations of our sample. To this purpose, we perform a full spectral fitting on the deep EDisCS spectroscopy data. We use the publicly available pPXF code for the spectral fitting, obtaining the details of the stellar populations, and the gas present in our sample, as results of our spectral fitting. We extract the fraction of the total stellar mass contained in stellar populations of different ages in our sample from this information. We also derive age-sensitive spectral indices, the strength of the narrow 4000\mbox{\AA} break strength, $D_{n,4000}$, and the Balmer H$\mathrm{\delta}$ absorption line index using the results of the spectral fitting. The final part of our analysis attempts to combine our morphological analysis, and our stellar population analysis. We search for trends in our $G-M_{20}$ TIMs and undisturbed galaxies with respect to the ages of their stellar populations. We find that our $G-M_{20}$ TIM galaxies are predominantly star-forming, as derived from multi-band photometric data. A larger fraction of the $G-M_{20}$ TIM galaxies also have features in their galaxy spectra indicating that their light is dominated by young stars. We then analyze the mass-weighted age fractions in the last 0.5 Gyr ($f_{Age < 0.5~\mathrm{Gyr}}$), and between 0.5 Gyr and 1 Gyr ($f_{0.5 < Age < 1.0~\mathrm{Gyr}}$). Our results imply an enhanced $f_{Age < 0.5~\mathrm{Gyr}}$ value for the $G-M_{20}$ TIMs. This time interval is comparable in length to merger timescales reported by many studies, thereby this result is indicative of the TIM event boosting the star formation of these galaxies

Random Forests Applied to High-precision Photometry Analysis with Spitzer IRAC

We present a new method employing machine-learning techniques for measuring astrophysical features by correcting systematics in IRAC high-precision photometry using random forests. The main systematic in IRAC light-curve data is position changes due to unavoidable telescope motions coupled with an intrapixel response function. We aim to use the large amount of publicly available calibration data for the single pixel used for this type of work (the sweet-spot pixel) to make a fast, easy-to-use, accurate correction to science data. This correction on calibration data has the advantage of using an independent data set instead of the science data themselves, which has the disadvantage of including astrophysical variations. After focusing on feature engineering and hyperparameter optimization, we show that a boosted random forest model can reduce the data such that we measure the median of 10 archival eclipse observations of XO-3b to be 1459 ± 200 ppm. This is a comparable depth to the average of those in the literature done by seven different methods; however, the spread in measurements is 30%–100% larger than those literature values, depending on the reduction method. We also caution others attempting similar methods to check their results with the fiducial data set of XO-3b, as we were also able to find models providing initially great scores on their internal test data sets but whose results significantly underestimated the eclipse depth of that planet

Random Forests Applied to High-precision Photometry Analysis with Spitzer IRAC

We present a new method employing machine-learning techniques for measuring astrophysical features by correcting systematics in IRAC high-precision photometry using random forests. The main systematic in IRAC light-curve data is position changes due to unavoidable telescope motions coupled with an intrapixel response function. We aim to use the large amount of publicly available calibration data for the single pixel used for this type of work (the sweet-spot pixel) to make a fast, easy-to-use, accurate correction to science data. This correction on calibration data has the advantage of using an independent data set instead of the science data themselves, which has the disadvantage of including astrophysical variations. After focusing on feature engineering and hyperparameter optimization, we show that a boosted random forest model can reduce the data such that we measure the median of 10 archival eclipse observations of XO-3b to be 1459 ± 200 ppm. This is a comparable depth to the average of those in the literature done by seven different methods; however, the spread in measurements is 30%–100% larger than those literature values, depending on the reduction method. We also caution others attempting similar methods to check their results with the fiducial data set of XO-3b, as we were also able to find models providing initially great scores on their internal test data sets but whose results significantly underestimated the eclipse depth of that planet

Star Cluster Classification using Deep Transfer Learning with PHANGS-HST

Currently available star cluster catalogues from HST imaging of nearby galaxies heavily rely on visual inspection and classification of candidate clusters. The time-consuming nature of this process has limited the production of reliable catalogues and thus also post-observation analysis. To address this problem, deep transfer learning has recently been used to create neural network models which accurately classify star cluster morphologies at production scale for nearby spiral galaxies (D < 20 Mpc). Here, we use HST UV-optical imaging of over 20,000 sources in 23 galaxies from the Physics at High Angular Resolution in Nearby GalaxieS (PHANGS) survey to train and evaluate two new sets of models: i) distance-dependent models, based on cluster candidates binned by galaxy distance (9-12 Mpc, 14-18 Mpc, 18-24 Mpc), and ii) distance-independent models, based on the combined sample of candidates from all galaxies. We find that the overall accuracy of both sets of models is comparable to previous automated star cluster classification studies (~60-80 per cent) and show improvement by a factor of two in classifying asymmetric and multi-peaked clusters from PHANGS-HST. Somewhat surprisingly, while we observe a weak negative correlation between model accuracy and galactic distance, we find that training separate models for the three distance bins does not significantly improve classification accuracy. We also evaluate model accuracy as a function of cluster properties such as brightness, colour, and SED-fit age. Based on the success of these experiments, our models will provide classifications for the full set of PHANGS-HST candidate clusters (N ~ 200,000) for public release.Comment: 16 pages, 10 figure

Multi-Scale Stellar Associations across the Star Formation Hierarchy in PHANGS-HST Nearby Galaxies: Methodology and Properties

We develop a method to identify and determine the physical properties of stellar associations using Hubble Space Telescope (HST) NUV-U-B-V-I imaging of nearby galaxies from the PHANGS-HST survey. We apply a watershed algorithm to density maps constructed from point source catalogues Gaussian smoothed to multiple physical scales from 8 to 64 pc. We develop our method on two galaxies that span the distance range in the PHANGS-HST sample: NGC 3351 (10 Mpc), NGC 1566 (18 Mpc). We test our algorithm with different parameters such as the choice of detection band for the point source catalogue (NUV or V), source density image filtering methods, and absolute magnitude limits. We characterise the properties of the resulting multi-scale associations, including sizes, number of tracer stars, number of associations, photometry, as well as ages, masses, and reddening from Spectral Energy Distribution fitting. Our method successfully identifies structures that occupy loci in the UBVI colour-colour diagram consistent with previously published catalogues of clusters and associations. The median ages of the associations increases from log(age/yr) = 6.6 to log(age/yr) = 6.9 as the spatial scale increases from 8 pc to 64 pc for both galaxies. We find that the youngest stellar associations, with ages < 3 Myr, indeed closely trace H ii regions in H$\alpha$ imaging, and that older associations are increasingly anti-correlated with the H$\alpha$ emission. Owing to our new method, the PHANGS-HST multi-scale associations provide a far more complete census of recent star formation activity than found with previous cluster and compact association catalogues. The method presented here will be applied to the full sample of 38 PHANGS-HST galaxies.Comment: Submitted to MNRAS. Referee report received with minor comments, and "request to clarify if the smaller associations are always included in the larger ones and how this may affect the photometric fitting of the larger association if the groups have different ages." Revision in progres

PHANGS-HST Catalogs for ∼100,000 Star Clusters and Compact Associations in 38 Galaxies. I. Observed Properties

We present the largest catalog to date of star clusters and compact associations in nearby galaxies. We have performed a V-band-selected census of clusters across the 38 spiral galaxies of the PHANGS–Hubble Space Telescope (HST) Treasury Survey, and measured integrated, aperture-corrected near-ultraviolet-U-B-V-I photometry. This work has resulted in uniform catalogs that contain ∼20,000 clusters and compact associations, which have passed human inspection and morphological classification, and a larger sample of ∼100,000 classified by neural network models. Here, we report on the observed properties of these samples, and demonstrate that tremendous insight can be gained from just the observed properties of clusters, even in the absence of their transformation into physical quantities. In particular, we show the utility of the UBVI color–color diagram, and the three principal features revealed by the PHANGS-HST cluster sample: the young cluster locus, the middle-age plume, and the old globular cluster clump. We present an atlas of maps of the 2D spatial distribution of clusters and compact associations in the context of the molecular clouds from PHANGS–Atacama Large Millimeter/submillimeter Array. We explore new ways of understanding this large data set in a multiscale context by bringing together once-separate techniques for the characterization of clusters (color–color diagrams and spatial distributions) and their parent galaxies (galaxy morphology and location relative to the galaxy main sequence). A companion paper presents the physical properties: ages, masses, and dust reddenings derived using improved spectral energy distribution fitting techniques

PHANGS: Constraining Star Formation Timescales Using the Spatial Correlations of Star Clusters and Giant Molecular Clouds

In the hierarchical view of star formation, giant molecular gas clouds (GMCs) undergo fragmentation to form small-scale structures made up of stars and star clusters. Here we study the connection between young star clusters and cold gas across a range of extragalactic environments by combining the high resolution (1") PHANGS-ALMA catalogue of GMCs with the star cluster catalogues from PHANGS-HST. The star clusters are spatially matched with the GMCs across a sample of 11 nearby star-forming galaxies with a range of galactic environments (centres, bars, spiral arms, etc.). We find that after 4-6 Myr the star clusters are no longer associated with any gas clouds. Additionally, we measure the autocorrelation of the star clusters and GMCs as well as their cross-correlation to quantify the fractal nature of hierarchical star formation. Young ($\leq$ 10 Myr) star clusters are more strongly autocorrelated on kpc and smaller spatial scales than the >10 Myr stellar populations, indicating that the hierarchical structure dissolves over time.Comment: 15 pages, 11 figures, 4 tables. Accepted to MNRAS Sept 6 202

Measuring the mixing scale of the ISM within nearby spiral galaxies

The spatial distribution of metals reflects, and can be used to constrain, the processes of chemical enrichment and mixing. Using PHANGS-MUSE optical integral field spectroscopy, we measure the gas phase oxygen abundances (metallicities) across 7,138 HII regions in a sample of eight nearby disc galaxies. In Paper I (Kreckel et al. 2019) we measure and report linear radial gradients in the metallicities of each galaxy, and qualitatively searched for azimuthal abundance variations. Here, we examine the two-dimensional variation in abundances once the radial gradient is subtracted, Delta(O/H), in order to quantify the homogeneity of the metal distribution and to measure the mixing scale over which HII region metallicities are correlated. We observe low (0.03--0.05 dex) scatter in Delta(O/H) globally in all galaxies, with significantly lower (0.02--0.03 dex) scatter on small (<600 pc) spatial scales. This is consistent with the measurement uncertainties, and implies the two-dimensional metallicity distribution is highly correlated on scales of <600 pc. We compute the two point correlation function for metals in the disc in order to quantify the scale lengths associated with the observed homogeneity. This mixing scale is observed to correlate better with the local gas velocity dispersion (of both cold and ionized gas) than with the star formation rate. Selecting only HII regions with enhanced abundances relative to a linear radial gradient, we do not observe increased homogeneity on small scales. This suggests that the observed homogeneity is driven by the mixing introducing material from large scales rather than by pollution from recent and on-going star formation.Comment: 17 pages, 14 figures. Accepted for publication in MNRA

PHANGS-JWST First Results: Dust embedded star clusters in NGC 7496 selected via 3.3 μ\mum PAH emission

The earliest stages of star formation occur enshrouded in dust and are not observable in the optical. Here we leverage the extraordinary new high-resolution infrared imaging from JWST to begin the study of dust-embedded star clusters in nearby galaxies throughout the local volume. We present a technique for identifying dust-embedded clusters in NGC 7496 (18.7 Mpc), the first galaxy to be observed by the PHANGS-JWST Cycle 1 Treasury Survey. We select sources that have strong 3.3$\mu$m PAH emission based on a $\rm F300M-F335M$ color excess, and identify 67 candidate embedded clusters. Only eight of these are found in the PHANGS-HST optically-selected cluster catalog and all are young (six have SED-fit ages of $\sim1$ Myr). We find that this sample of embedded cluster candidates may significantly increase the census of young clusters in NGC 7496 from the PHANGS-HST catalog -- the number of clusters younger than $\sim$2 Myr could be increased by a factor of two. Candidates are preferentially located in dust lanes, and are coincident with peaks in PHANGS-ALMA CO (2-1) maps. We take a first look at concentration indices, luminosity functions, SEDs spanning from 2700A to 21$\mu$m, and stellar masses (estimated to be between $\sim10^4-10^5 M_{\odot}$). The methods tested here provide a basis for future work to derive accurate constraints on the physical properties of embedded clusters, characterize the completeness of cluster samples, and expand analysis to all 19 galaxies in the PHANGS-JWST sample, which will enable basic unsolved problems in star formation and cluster evolution to be addressed.Comment: 12 pages, 6 figures; accepted for publication in ApJL as part of PHANGS-JWST First Results Special Issu