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Register a new userRing Galaxies Through Off-center Minor Collisions by Tuning Bulge-to-disk Mass Ratio of Progenitors
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Collisional ring galaxies (CRGs) are formed through off-center collisions between a target galaxy and an intruder dwarf galaxy. We study the mass distribution and kinematics of the CRGs by tuning the bulge-to-disk mass ratio ($B/D$) for the progenitor; i.e., the target galaxy. We find that the lifetime of the ring correlates with the initial impact velocity vertical to the disk plane (i.e., $v_{z0}$). Three orbits for the collisional galaxy pair, on which clear and asymmetric rings form after collisions, are selected to perform the textit{N}-body simulations at different values of $B/D$ for the progenitor. It is found that the ring structures are the strongest for the CRGs with small values of $B/D$. The S{e}rsic index, $n$, of the central remnant in the target galaxy becomes larger after collision. Moreover, the S{e}rsic index of a central remnant strongly correlates with the initial value of $B/D$ for the progenitor. A bulge-less progenitor results in a late-type object in the center of the ring galaxy, whereas a bulge-dominated progenitor leads to an early-type central remnant. Progenitors with $B/Din [0.1,~0.3]$ (i.e., minor bulges) leave central remnants with $napprox 4$. These results provide a possible explanation for the formation of a recently observed CRG with an early-type central nucleus, SDSS J1634+2049. In addition, we find that the radial and azimuthal velocity profiles for a ring galaxy are more sensitive to the $B/D$ than the initial relative velocity of the progenitor.
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We combine Spitzer $3.6mu$ observations of a sample of disk galaxies spanning over 10 magnitudes in luminosity with optical luminosities and colors to test population synthesis prescriptions for computing stellar mass. Many commonly employed models fail to provide self-consistent results: the stellar mass estimated from the luminosity in one band can differ grossly from that of another band for the same galaxy. Independent models agree closely in the optical ($V$-band), but diverge at longer wavelengths. This effect is particularly pronounced in recent models with substantial contributions from TP-AGB stars. We provide revised color--mass-to-light ratio relations that yield self-consistent stellar masses when applied to real galaxies. The $B-V$ color is a good indicator of the mass-to-light ratio. Some additional information is provided by $V-I$, but neither it nor $J-K_s$ are particularly useful for constraining the mass-to-light ratio on their own. In the near-infrared, the mass-to-light ratio depends weakly on color, with typical values of $0.6; mathrm{M}_{odot}/mathrm{L}_{odot}$ in the $K_s$-band and $0.47; mathrm{M}_{odot}/mathrm{L}_{odot}$ at $3.6mu$.
We investigate the formation of RE galaxies (i.e. of collisional ring galaxies with an empty ring), with N-body/SPH simulations. The simulations employ a recipe for star formation (SF) and feedback that has been shown to be crucial to produce realistic galaxies in a cosmological context. We show that RE galaxies can form via off-centre collisions (i.e. with a non-zero impact parameter), even for small inclination angles. The ring can be either a complete ring or an arc, depending on the initial conditions (especially on the impact parameter). In our simulations, the nucleus of the target galaxy is displaced from the dynamical centre of the galaxy and is buried within the ring, as a consequence of the off-centre collision. We find that the nucleus is not vertically displaced from the plane of the ring. We study the kinematics of the ring, finding agreement with the predictions by the analytic theory. The SF history of the simulated galaxies indicates that the interaction enhances the SF rate. We compare the results of our simulations with the observations of Arp 147, that is the prototype of RE galaxies.
The role of disk instabilities, such as bars and spiral arms, and the associated resonances, in growing bulges in the inner regions of disk galaxies have long been studied in the low-redshift nearby Universe. There it has long been probed observationally, in particular through peanut-shaped bulges. This secular growth of bulges in modern disk galaxies is driven by weak, non-axisymmetric instabilities: it mostly produces pseudo-bulges at slow rates and with long star-formation timescales. Disk instabilities at high redshift (z>1) in moderate-mass to massive galaxies (10^10 to a few 10^11 Msun of stars) are very different from those found in modern spiral galaxies. High-redshift disks are globally unstable and fragment into giant clumps containing 10^8-10^9 Msun of gas and stars each, which results in highly irregular galaxy morphologies. The clumps and other features associated to the violent instability drive disk evolution and bulge growth through various mechanisms, on short timescales. The giant clumps can migrate inward and coalesce into the bulge in a few 10^8 yr. The instability in the very turbulent media drives intense gas inflows toward the bulge and nuclear region. Thick disks and supermassive black holes can grow concurrently as a result of the violent instability. This chapter reviews the properties of high-redshift disk instabilities, the evolution of giant clumps and other features associated to the instability, and the resulting growth of bulges and associated sub-galactic components.
We present the results from a study of the morphologies of moderate luminosity X-ray selected AGN host galaxies in comparison to a carefully mass-matched control sample at 0.5 < z < 3 in the CANDELS GOODS-S field. We apply a multi-wavelength morphological decomposition analysis to these two samples and report on the differences between the morphologies as fitted from single Sersic and multiple Sersic models, and models which include an additional nuclear point-source component. Thus, we are able to compare the widely adopted single Sersic fits from previous studies to the results from a full morphological decomposition, and address the issue of how biased the inferred properties of AGN hosts are by a potential nuclear contribution from the AGN itself. We find that the AGN hosts are mixed systems which have higher bulge fractions than the control sample in our highest redshift bins at the >99.7% confidence level, according to all model fits even those which adopt a point-source component. This serves to alleviate concerns that previous, purely single Sersic, analyses of AGN hosts could have been spuriously biased towards higher bulge fractions. This dataset allows us to further probe the physical nature of these point-source components; we find no strong correlation between the point-source component and AGN activity, and that these point-source components are best modelled physically by nuclear starbursts. Our analysis of the bulge and disk fractions of these AGN hosts in comparison to a mass-matched control sample reveals a similar morphological evolutionary track for both the active and non-active populations, providing further evidence in favour of a model where AGN activity is triggered by secular processes.
We present a deep learning model to predict the r-band bulge-to-total light ratio (B/T) of nearby galaxies using their multi-band JPEG images alone. Our Convolutional Neural Network (CNN) based regression model is trained on a large sample of galaxies with reliable decomposition into the bulge and disk components. The existing approaches to estimate the B/T use galaxy light-profile modelling to find the best fit. This method is computationally expensive, prohibitively so for large samples of galaxies, and requires a significant amount of human intervention. Machine learning models have the potential to overcome these shortcomings. In our CNN model, for a test set of 20000 galaxies, 85.7 per cent of the predicted B/T values have absolute error (AE) less than 0.1. We see further improvement to 87.5 per cent if, while testing, we only consider brighter galaxies (with r-band apparent magnitude < 17) with no bright neighbours. Our model estimates B/T for the 20000 test galaxies in less than a minute. This is a significant improvement in inference time from the conventional fitting pipelines, which manage around 2-3 estimates per minute. Thus, the proposed machine learning approach could potentially save a tremendous amount of time, effort and computational resources while predicting B/T reliably, particularly in the era of next-generation sky surveys such as the Legacy Survey of Space and Time (LSST) and the Euclid sky survey which will produce extremely large samples of galaxies.
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