31 research outputs found
Bulge plus disc and S\'ersic decomposition catalogues for 16,908 galaxies in the SDSS Stripe 82 co-adds: A detailed study of the structural measurements
Quantitative characterization of galaxy morphology is vital in enabling
comparison of observations to predictions from galaxy formation theory.
However, without significant overlap between the observational footprints of
deep and shallow galaxy surveys, the extent to which structural measurements
for large galaxy samples are robust to image quality (e.g., depth, spatial
resolution) cannot be established. Deep images from the Sloan Digital Sky
Survey (SDSS) Stripe 82 co-adds provide a unique solution to this problem -
offering magnitudes improvement in depth with respect to SDSS Legacy
images. Having similar spatial resolution to Legacy, the co-adds make it
possible to examine the sensitivity of parametric morphologies to depth alone.
Using the Gim2D surface-brightness decomposition software, we provide public
morphology catalogs for 16,908 galaxies in the Stripe 82 co-adds. Our
methods and selection are completely consistent with the Simard et al. (2011)
and Mendel et al. (2014) photometric decompositions. We rigorously compare
measurements in the deep and shallow images. We find no systematics in total
magnitudes and sizes except for faint galaxies in the -band and the
brightest galaxies in each band. However, characterization of bulge-to-total
fractions is significantly improved in the deep images. Furthermore, statistics
used to determine whether single-S\'ersic or two-component (e.g., bulge+disc)
models are required become more bimodal in the deep images. Lastly, we show
that asymmetries are enhanced in the deep images and that the enhancement is
positively correlated with the asymmetries measured in Legacy images.Comment: 27 pages, 14 figures. MNRAS accepted. Our catalogs are available in
TXT and SQL formats at
http://orca.phys.uvic.ca/~cbottrel/share/Stripe82/Catalogs
A definitive merger-AGN connection at z~0 with CFIS: mergers have an excess of AGN and AGN hosts are more frequently disturbed
The question of whether galaxy mergers are linked to the triggering of active
galactic nuclei (AGN) continues to be a topic of considerable debate. The issue
can be broken down into two distinct questions: 1) Can galaxy mergers trigger
AGN? 2) Are galaxy mergers the dominant AGN triggering mechanism? A complete
picture of the AGN-merger connection requires that both of these questions are
addressed with the same dataset. In previous work, we have shown that galaxy
mergers selected from the Sloan Digital Sky Survey (SDSS) show an excess of
both optically-selected, and mid-IR colour-selected AGN, demonstrating that the
answer to the first of the above questions is affirmative. Here, we use the
same optical and mid-IR AGN selection to address the second question, by
quantifying the frequency of morphological disturbances in low surface
brightness r-band images from the Canada France Imaging Survey (CFIS). Only ~30
per cent of optical AGN host galaxies are morphologically disturbed, indicating
that recent interactions are not the dominant trigger. However, almost 60 per
cent of mid-IR AGN hosts show signs of visual disturbance, indicating that
interactions play a more significant role in nuclear feeding. Both mid-IR and
optically selected AGN have interacting fractions that are a factor of two
greater than a mass and redshift matched non-AGN control sample, an excess that
increases with both AGN luminosity and host galaxy stellar mass.Comment: Accepted for publication in MNRA
A machine learning approach to assessing the presence of substructure in quasar host galaxies using the Hyper Suprime-Cam Subaru Strategic Program
The conditions under which galactic nuclear regions become active are largely
unknown, although it has been hypothesized that secular processes related to
galaxy morphology could play a significant role. We investigate this question
using optical i-band images of 3096 SDSS quasars and galaxies at 0.3<z<0.6 from
the Hyper Suprime-Cam Subaru Strategic Program, which possess a unique
combination of area, depth and resolution, allowing the use of residual images,
after removal of the quasar and smooth galaxy model, to investigate internal
structural features. We employ a variational auto-encoder which is a generative
model that acts as a form of dimensionality reduction. We analyze the lower
dimensional latent space in search of features which correlate with nuclear
activity. We find that the latent space does separate images based on the
presence of nuclear activity which appears to be associated with more
pronounced components (i.e., arcs, rings and bars) as compared to a matched
control sample of inactive galaxies. These results suggest the importance of
secular processes, and possibly mergers (by their remnant features) in
activating or sustaining black hole growth. Our study highlights the breadth of
information available in ground-based imaging taken under optimal seeing
conditions and having accurate characterization of the point spread function
(PSF) thus demonstrating future science to come from the Rubin Observatory
The merger fraction of post-starburst galaxies in UNIONS
Funding information: CB gratefully acknowledges support from the Natural Sciences and Engineering Council of Canada (NSERC) as part of their post-doctoral fellowship program (PDF-546234-2020) and VW acknowledges STFC grant ST/V000861/1.Post-starburst galaxies (PSBs) are defined as having experienced a recent burst of star formation, followed by a prompt truncation in further activity. Identifying the mechanism(s) causing a galaxy to experience a post-starburst phase therefore provides integral insight into the causes of rapid quenching. Galaxy mergers have long been proposed as a possible post-starburst trigger. Effectively testing this hypothesis requires a large spectroscopic galaxy survey to identify the rare PSBs as well as high-quality imaging and robust morphology metrics to identify mergers. We bring together these critical elements by selecting PSBs from the overlap of the Sloan Digital Sky Survey and the Canada–France Imaging Survey and applying a suite of classification methods: non-parametric morphology metrics such as asymmetry and Gini-M20, a convolutional neural network trained to identify post-merger galaxies, and visual classification. This work is therefore the largest and most comprehensive assessment of the merger fraction of PSBs to date. We find that the merger fraction of PSBs ranges from 19 per cent to 42 per cent depending on the merger identification method and details of the PSB sample selection. These merger fractions represent an excess of 3–46× relative to non-PSB control samples. Our results demonstrate that mergers play a significant role in generating PSBs, but that other mechanisms are also required. However, applying our merger identification metrics to known post-mergers in the IllustrisTNG simulation shows that 70 per cent of recent post-mergers (≲200 Myr) would not be detected. Thus, we cannot exclude the possibility that nearly all PSBs have undergone a merger in their recent past.Publisher PDFPeer reviewe
Molecular gas and star formation in nearby starburst galaxy mergers
We employ the Feedback In Realistic Environments (FIRE-2) physics model to
study how the properties of giant molecular clouds (GMCs) evolve during galaxy
mergers. We conduct a pixel-by-pixel analysis of molecular gas properties in
both the simulated control galaxies and galaxy major mergers. The simulated
GMC-pixels in the control galaxies follow a similar trend in a diagram of
velocity dispersion () versus gas surface density
() to the one observed in local spiral galaxies in the
Physics at High Angular resolution in Nearby GalaxieS (PHANGS) survey. For
GMC-pixels in simulated mergers, we see a significant increase of factor of 5 -
10 in both and , which puts these pixels
above the trend of PHANGS galaxies in the vs
diagram. This deviation may indicate that GMCs in the simulated mergers are
much less gravitationally bound compared with simulated control galaxies with
virial parameter () reaching 10 - 100. Furthermore, we
find that the increase in happens at the same time as
the increase in global star formation rate (SFR), which suggests stellar
feedback is responsible for dispersing the gas. We also find that the gas
depletion time is significantly lower for high GMCs
during a starburst event. This is in contrast to the simple physical picture
that low GMCs are easier to collapse and form stars on
shorter depletion times. This might suggest that some other physical mechanisms
besides self-gravity are helping the GMCs in starbursting mergers collapse and
form stars.Comment: 22 pages, 11 figures. Accepted to ApJ. Link to animation update
What shapes a galaxy? - Unraveling the role of mass, environment and star formation in forming galactic structure
We investigate the dependence of galaxy structure on a variety of galactic
and environmental parameters for ~500,000 galaxies at z<0.2, taken from the
Sloan Digital Sky Survey data release 7 (SDSS-DR7). We utilise bulge-to-total
stellar mass ratio, (B/T)_*, as the primary indicator of galactic structure,
which circumvents issues of morphological dependence on waveband. We rank
galaxy and environmental parameters in terms of how predictive they are of
galaxy structure, using an artificial neural network approach. We find that
distance from the star forming main sequence (Delta_SFR), followed by stellar
mass (M_*), are the most closely connected parameters to (B/T)_*, and are
significantly more predictive of galaxy structure than global star formation
rate (SFR), or any environmental metric considered (for both central and
satellite galaxies). Additionally, we make a detailed comparison to the
Illustris hydrodynamical simulation and the LGalaxies semi-analytic model. In
both simulations, we find a significant lack of bulge-dominated galaxies at a
fixed stellar mass, compared to the SDSS. This result highlights a potentially
serious problem in contemporary models of galaxy evolution.Comment: Accepted to MNRAS. 31 pages, 15 figure
ERGO-ML -- Comparing IllustrisTNG and HSC galaxy images via contrastive learning
Modern cosmological hydrodynamical galaxy simulations provide tens of
thousands of reasonably realistic synthetic galaxies across cosmic time.
However, quantitatively assessing the level of realism of simulated universes
in comparison to the real one is difficult. In this paper of the ERGO-ML series
(Extracting Reality from Galaxy Observables with Machine Learning), we utilize
contrastive learning to directly compare a large sample of simulated and
observed galaxies based on their stellar-light images. This eliminates the need
to specify summary statistics and allows to exploit the whole information
content of the observations. We produce survey-realistic galaxy mock datasets
resembling real Hyper Suprime-Cam (HSC) observations using the cosmological
simulations TNG50 and TNG100. Our focus is on galaxies with stellar masses
between and at . This allows us to evaluate
the realism of the simulated TNG galaxies in comparison to actual HSC
observations. We apply the self-supervised contrastive learning method NNCLR to
the images from both simulated and observed datasets (g, r, i - bands). This
results in a 256-dimensional representation space, encoding all relevant
observable galaxy properties. Firstly, this allows us to identify simulated
galaxies that closely resemble real ones by seeking similar images in this
multi-dimensional space. Even more powerful, we quantify the alignment between
the representations of these two image sets, finding that the majority
( per cent) of the TNG galaxies align well with observed HSC
images. However, a subset of simulated galaxies with larger sizes, steeper
Sersic profiles, smaller Sersic ellipticities, and larger asymmetries appears
unrealistic. We also demonstrate the utility of our derived image
representations by inferring properties of real HSC galaxies using simulated
TNG galaxies as the ground truth.Comment: 26 pages, 17 figures. Submitted to MNRAS. Comments are welcome.
Highlights in Fig. 3, 7 and 1