319 research outputs found
The Evolution of Spiral Galaxies in the Group Environment
Although the process by which galaxies obtain the gas needed for star-formation is amongst the
most fundamental processes related to the formation of baryonic structure in the universe, there
is very little in the way of empirical evidence with which to constrain theoretical models. In particular,
the postulated environmental dependencies of this process, although widely modeled,
remain largely unconstrained. In this work, I present the first detailed, quantitative analysis
of the environmental effects on the process of gas-fueling in which the relevant effects of the
galaxy - intergalactic medium interaction have been isolated from other potential environmental
in
uences. In the context of this analysis, a new robust method for selecting morphologically
defined samples of galaxies by photometric proxies is developed, as well a powerful new method
for correcting the UV/optical emission of samples of spiral galaxies for the effects of attenuation
by dust located in their disks. Combining these tools with the data from the GAMA
survey, in particular the galaxy group catalog, I present a detailed analysis of the environmental
dependencies of gas-fueling. The results obtained require a fundamental re-evaluation of the
assumptions concerning the fueling of satellite galaxies and the effects of active galactic nuclei
CGC: a scalable Python package for co- and tri-clustering of geodata cubes
Clustering Geo-Data Cubes (CGC) is a Python package to perform clustering analysis for multidimensional geospatial data. The included tools allow the user to efficiently run tasks in parallel on local and distributed systems
Fast and Credible Likelihood-Free Cosmology with Truncated Marginal Neural Ratio Estimation
Sampling-based inference techniques are central to modern cosmological data
analysis; these methods, however, scale poorly with dimensionality and
typically require approximate or intractable likelihoods. In this paper we
describe how Truncated Marginal Neural Ratio Estimation (TMNRE) (a new approach
in so-called simulation-based inference) naturally evades these issues,
improving the efficiency, scalability, and trustworthiness
of the inferred posteriors. Using measurements of the Cosmic Microwave
Background (CMB), we show that TMNRE can achieve converged posteriors using
orders of magnitude fewer simulator calls than conventional Markov Chain Monte
Carlo (MCMC) methods. Remarkably, the required number of samples is effectively
independent of the number of nuisance parameters. In addition, a property
called \emph{local amortization} allows the performance of rigorous statistical
consistency checks that are not accessible to sampling-based methods. TMNRE
promises to become a powerful tool for cosmological data analysis, particularly
in the context of extended cosmologies, where the timescale required for
conventional sampling-based inference methods to converge can greatly exceed
that of simple cosmological models such as CDM. To perform these
computations, we use an implementation of TMNRE via the open-source code
\texttt{swyft}.Comment: v2: accepted journal version. v1: 37 pages, 13 figures.
\texttt{swyft} is available at https://github.com/undark-lab/swyft, and
demonstration code for cosmological examples is available at
https://github.com/acole1221/swyft-CM
A radiative transfer model for the spiral galaxy M33
We present the first radiative transfer (RT) model of a non-edge-on disk galaxy in which the large-scale geometry of stars and dust is self-consistently derived through fitting of multiwavelength imaging observations from the UV to the submm. To this end we used the axi-symmetric RT model of Popescu et al. and a new methodology for deriving geometrical parameters, and applied this to decode the{spectral energy distribution (SED) of M33. We successfully account for both the spatial and spectral energy distribution, with residuals typically within 7% in the profiles of surface brightness and within 8% in the spatially-integrated SED. We predict well the energy balance between absorption and re-emission by dust, with no need to invoke modified grain properties, and we find no submm emission that is in excess of our model predictions. We calculate that 80±8% of the dust heating is powered by the young stellar populations. We identify several morphological components in M33, a nuclear, an inner, a main and an outer disc, showing a monotonic trend in decreasing star-formation surface-density (ΣSFR) from the nuclear to the outer disc. In relation to surface density of stellar mass, the ΣSFR of these components define a steeper relation than the "main sequence" of star-forming galaxies, which we call a "structurally resolved main sequence". Either environmental or stellar feedback mechanisms could explain the slope of the newly defined sequence. We find the star-formation rate to be SFR=0.28+0.02−0.01M⊙yr−1
Radiocarbon intercomparison program for Chauvet Cave
We present the first results of an accelerator mass spectrometry (AMS) radiocarbon intercomparison program on 3 different charcoal samples collected in one of the hearths of the Megaceros gallery of Chauvet Cave (Ardeche, France). This cave, rich in parietal decoration, is important for the study of the appearance and evolution of prehistoric art because certain drawings have been C-14 dated to the Aurignacian period at the beginning of the Upper Paleolithic. The new dates indicate an age of about 32,000 BP, which is consistent with this attribution and in agreement with the results from the same sector of the cave measured previously at the Laboratoire des Sciences du Climat et de l'Environnement (LSCE). Six laboratories were involved in the intercomparison. Samples were measured in 4 AMS facilities: Center for Isotope Research, Groningen University, the Netherlands; the Oxford Radiocarbon Accelerator Unit, UK; the Centre de datation par le carbone 14, Univ. Claude Bernard Lyon 1, France (measured by AMS facilities of Poznan University, Poland); and the LSCE, UMR CEA-CNRS-UVSQ, France (measured by the Leibniz-Labor of Christian-Albrechts-Universitat Kiel, Germany).</p
Galaxy and Mass Assembly (GAMA): formation and growth of elliptical galaxies in the group environment
There are many proposed mechanisms driving the morphological transformation of disc galaxies to elliptical galaxies. In this paper, we determine if the observed transformation in low-mass groups can be explained by the merger histories of galaxies. We measured the group mass– morphology relation for groups from the Galaxy and Mass Assembly group catalogue with masses from 1011 to 1015 M. Contrary to previous studies, the fraction of elliptical galaxies in our more complete group sample increases significantly with group mass across the full range of group mass. The elliptical fraction increases at a rate of 0.163 ± 0.012 per dex of group mass for groups more massive than 1012.5 M. If we allow for uncertainties in the observed group masses, our results are consistent with a continuous increase in elliptical fraction from group masses as low as 1011 M. We tested if this observed relation is consistent with the merger activity using a GADGET-2 dark matter simulation of the galaxy groups. We specified that a simulated galaxy would be transformed to an elliptical morphology either if it experienced a major merger or if its cumulative mass gained from minor mergers exceeded 30 per cent of its final mass. We then calculated a group mass–morphology relation for the simulations. The position and slope of the simulated relation were consistent with the observational relation, with a gradient of 0.184 ± 0.010 per dex of group mass. These results demonstrate a strong correlation between the frequency of merger events and disc-to-elliptical galaxy transformation in galaxy group environments.This research was conducted by the Australian Research Council Centre of Excellence for All-sky Astrophysics (CAASTRO),
through project number CE110001020. SB acknowledges funding
support from the Australian Research Council through a Future Fellowship (FT140101166). GAMA is a joint European-Australasian
project based around a spectroscopic campaign using the AAT. The
GAMA input catalogue is based on data taken from the SDSS and
the UKIRT Infrared Deep Sky Survey. Complementary imaging of
the GAMA regions is being obtained by a number of independent
survey programmes including GALEX MIS, VST KIDS, VISTA
VIKING, WISE, Herschel-ATLAS, GMRT and ASKAP providing
ultraviolet to radio coverage. GAMA is funded by the STFC (UK),
the ARC (Australia), the AAO and the participating institutions.
The GAMA web site is http://www.gama-survey.org/
Galaxy And Mass Assembly (GAMA): Self-Organizing Map Application on Nearby Galaxies
Galaxy populations show bimodality in a variety of properties: stellar mass,
colour, specific star-formation rate, size, and S\'ersic index. These
parameters are our feature space. We use an existing sample of 7556 galaxies
from the Galaxy and Mass Assembly (GAMA) survey, represented using five
features and the K-means clustering technique, showed that the bimodalities are
the manifestation of a more complex population structure, represented by
between 2 and 6 clusters.
Here we use Self Organizing Maps (SOM), an unsupervised learning technique
which can be used to visualize similarity in a higher dimensional space using a
2D representation, to map these five-dimensional clusters in the feature space
onto two-dimensional projections. To further analyze these clusters, using the
SOM information, we agree with previous results that the sub-populations found
in the feature space can be reasonably mapped onto three or five clusters. We
explore where the "green valley" galaxies are mapped onto the SOM, indicating
multiple interstitial populations within the green valley population.
Finally, we use the projection of the SOM to verify whether morphological
information provided by GalaxyZoo users, for example, if features are visible,
can be mapped onto the SOM-generated map. Voting on whether galaxies are
smooth, likely ellipticals, or "featured" can reasonably be separated but
smaller morphological features (bar, spiral arms) can not. SOMs promise to be a
useful tool to map and identify instructive sub-populations in multidimensional
galaxy survey feature space, provided they are large enough.Comment: 14 pages, 14 figures, accepted by MNRA
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