Kinematic classifications of local interacting galaxies: implications for the merger/disk classifications at high-z

The classification of galaxy mergers and isolated disks is key for understanding the relative importance of galaxy interactions and secular evolution during the assembly of galaxies. The kinematic properties of galaxies as traced by emission lines have been used to suggest the existence of a significant population of high-z star-forming galaxies consistent with isolated rotating disks. However, recent studies have cautioned that post-coalescence mergers may also display disk-like kinematics. To further investigate the robustness of merger/disk classifications based on kinematic properties, we carry out a systematic classification of 24 local (U)LIRGs spanning a range of galaxy morphologies: from isolated spiral galaxies, ongoing interacting systems, to fully merged remnants. We artificially redshift the WiFeS observations of these local (U)LIRGs to z=1.5 to make a realistic comparison with observations at high-z, and also to ensure that all galaxies have the same spatial sampling of ~900 pc. Using both kinemetry-based and visual classifications, we find that the reliability of kinematic classification shows a strong trend with the interaction stage of galaxies. Mergers with two nuclei and tidal tails have the most distinct kinematic properties compared to isolated disks, whereas a significant population of the interacting disks and merger remnants are indistinguishable from isolated disks. The high fraction of late-stage mergers showing disk-like kinematics reflects the complexity of the dynamics during galaxy interactions. However, the exact fractions of misidentified disks and mergers depend on the definition of kinematic asymmetries and the classification threshold when using kinemetry-based classifications. Our results suggest that additional indicators such as morphologies traced by stars or molecular gas are required to further constrain the merger/disk classifications at high-z.Comment: 16 pages, 5 figures, ApJ accepte

The Recent Burstiness of Star Formation in Galaxies at z ~ 4.5 from Hα Measurements

The redshift range z = 4–6 marks a transition phase between primordial and mature galaxy formation in which galaxies considerably increase their stellar mass, metallicity, and dust content. The study of galaxies in this redshift range is therefore important to understanding early galaxy formation and the fate of galaxies at later times. Here, we investigate the burstiness of the recent star formation history (SFH) of 221z ~ 4.5 main-sequence galaxies at log(M/M⊙) > 9.7 by comparing their ultra-violet (UV) continuum, Hα luminosity, and Hα equivalent-width (EW). The Hα properties are derived from the Spitzer [3.6 μm]−[4.5 μm] broadband color, thereby properly taking into account model and photometric uncertainties. We find a significant scatter between Hα- and UV-derived luminosities and star formation rates (SFRs). About half of the galaxies show a significant excess in Hα compared to expectations from a constant smooth SFH. We also find a tentative anticorrelation between Hα EW and stellar mass, ranging from 1000 Å at log(M/M⊙) 11. Consulting models suggests that most z ~ 4.5 galaxies had a burst of star formation within the last 50 Myr, increasing their SFRs by a factor of >5. The most massive galaxies on the other hand might decrease their SFRs and may be transitioning to a quiescent stage by z = 4. We identify differential dust attenuation (f) between stars and nebular regions as the main contributor to the uncertainty. With local galaxies selected by increasing Hα EW (reaching values similar to high-z galaxies), we predict that f approaches unity at z > 4, consistent with the extrapolation of measurements out to z = 2

The Effects of Heterospecific Mating Frequency on the Strength of Cryptic Reproductive Barriers

Heterospecific mating frequency is critical to hybrid zone dynamics and can directly impact the strength of reproductive barriers and patterns of introgression. The effectiveness of post-mating prezygotic (PMPZ) reproductive barriers, which include reduced fecundity via heterospecific matings and conspecific sperm precedence, may depend on the number, identity and order of mates. Studies of PMPZ barriers suggest that they may be important in many systems, but whether these barriers are effective at realistic heterospecific mating frequencies has not been tested. Here, we evaluate the strength of cryptic reproductive isolation in two leaf beetles (Chrysochus auratus and C. cobaltinus) in the context of a range of heterospecific mating frequencies observed in natural populations. We found both species benefited from multiple matings, but the benefits were greater in C. cobaltinus and extended to heterospecific matings. We found that PMPZ barriers greatly limited hybrid production by C. auratus females with moderate heterospecific mating frequencies, but that their effectiveness diminished at higher heterospecific mating frequencies. In contrast, there was no evidence for PMPZ barriers in C. cobaltinus females at any heterospecific mating frequency. We show that integrating realistic estimates of cryptic isolation with information on relative abundance and heterospecific mating frequency in the field substantially improves our understanding of the strong directional bias in F1 production previously documented in the Chrysochus hybrid zone. Our results demonstrate that heterospecific mating frequency is critical to understanding the impact of cryptic post-copulatory barriers on hybrid zone structure and dynamics, and that future studies of such barriers should incorporate field-relevant heterospecific mating frequencies

Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles

The stability, activity, and solubility of a protein sequence are determined by a delicate balance of molecular interactions in a variety of conformational states. Even so, most computational protein design methods model sequences in the context of a single native conformation. Simulations that model the native state as an ensemble have been mostly neglected due to the lack of sufficiently powerful optimization algorithms for multistate design. Here, we have applied our multistate design algorithm to study the potential utility of various forms of input structural data for design. To facilitate a more thorough analysis, we developed new methods for the design and high-throughput stability determination of combinatorial mutation libraries based on protein design calculations. The application of these methods to the core design of a small model system produced many variants with improved thermodynamic stability and showed that multistate design methods can be readily applied to large structural ensembles. We found that exhaustive screening of our designed libraries helped to clarify several sources of simulation error that would have otherwise been difficult to ascertain. Interestingly, the lack of correlation between our simulated and experimentally measured stability values shows clearly that a design procedure need not reproduce experimental data exactly to achieve success. This surprising result suggests potentially fruitful directions for the improvement of computational protein design technology

Spectral Energy Distributions of Local Luminous And Ultraluminous Infrared Galaxies

Luminous and ultraluminous infrared galaxies ((U)LIRGs) are the most extreme star forming galaxies in the universe. The local (U)LIRGs provide a unique opportunity to study their multi-wavelength properties in detail for comparison to their more numerous counterparts at high redshifts. We present common large aperture photometry at radio through X-ray wavelengths, and spectral energy distributions (SEDs) for a sample of 53 nearby LIRGs and 11 ULIRGs spanning log (LIR/Lsun) = 11.14-12.57 from the flux-limited Great Observatories All-sky LIRG Survey (GOALS). The SEDs for all objects are similar in that they show a broad, thermal stellar peak and a dominant FIR thermal dust peak, where nuLnu(60um) / nuLnu(V) increases from ~2-30 with increasing LIR. When normalized at IRAS-60um, the largest range in the luminosity ratio, R(lambda)=log[nuLnu(lambda)/nuLnu(60um)] observed over the full sample is seen in the Hard X-rays (HX=2-10 keV). A small range is found in the Radio (1.4GHz), where the mean ratio is largest. Total infrared luminosities, LIR(8-1000um), dust temperatures, and dust masses were computed from fitting thermal dust emission modified blackbodies to the mid-infrared (MIR) through submillimeter SEDs. The new results reflect an overall ~0.02 dex lower luminosity than the original IRAS values. Total stellar masses were computed by fitting stellar population synthesis models to the observed near-infrared (NIR) through ultraviolet (UV) SEDs. Mean stellar masses are found to be log(M/Msun) = 10.79+/-0.40. Star formation rates have been determined from the infrared (SFR_IR~45Msun/yr) and from the monochromatic UV luminosities (SFR_UV~1.3Msun/yr), respectively. Multiwavelength AGN indicators have be used to select putative AGN: about 60% of the ULIRGs would have been classified as an AGN by at least one of the selection criteria.Comment: 39 pages, including 12 figures and 11 tables; accepted for publication in ApJ

Deep transfer learning for star cluster classification: I. application to the PHANGS–HST survey

We present the results of a proof-of-concept experiment that demonstrates that deep learning can successfully be used for production-scale classification of compact star clusters detected in Hubble Space Telescope(HST) ultraviolet-optical imaging of nearby spiral galaxies (⁠D≲20Mpc⁠) in the Physics at High Angular Resolution in Nearby GalaxieS (PHANGS)–HST survey. Given the relatively small nature of existing, human-labelled star cluster samples, we transfer the knowledge of state-of-the-art neural network models for real-object recognition to classify star clusters candidates into four morphological classes. We perform a series of experiments to determine the dependence of classification performance on neural network architecture (ResNet18 and VGG19-BN), training data sets curated by either a single expert or three astronomers, and the size of the images used for training. We find that the overall classification accuracies are not significantly affected by these choices. The networks are used to classify star cluster candidates in the PHANGS–HST galaxy NGC 1559, which was not included in the training samples. The resulting prediction accuracies are 70 per cent, 40 per cent, 40–50 per cent, and 50–70 per cent for class 1, 2, 3 star clusters, and class 4 non-clusters, respectively. This performance is competitive with consistency achieved in previously published human and automated quantitative classification of star cluster candidate samples (70–80 per cent, 40–50 per cent, 40–50 per cent, and 60–70 per cent). The methods introduced herein lay the foundations to automate classification for star clusters at scale, and exhibit the need to prepare a standardized data set of human-labelled star cluster classifications, agreed upon by a full range of experts in the field, to further improve the performance of the networks introduced in this study

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