相关论文: Detection of Bars in Galaxies using a Deep Convolu…
We present the first deep learning model for segmenting galactic spiral arms and bars. In a blinded assessment by expert astronomers, our predicted spiral arm masks are preferred over both current automated methods (99% of evaluations) and…
Despite the increasing number of studies of barred galaxies at intermediate and high redshifts, double-barred (S2B) systems have only been identified in the nearby (z<0.04) universe thus far. In this feasibility study we demonstrate that…
There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a…
In the framework of the European VO-Tech project, we are implementing new machine learning methods specifically tailored to match the needs of astronomical data mining. In this paper, we shortly present the methods and discuss an…
A full ring is a form of galaxy morphology that is not associated with a specific stage on the Hubble sequence. Digital sky surveys can collect many millions of galaxy images, and therefore even rare forms of galaxies are expected to be…
This paper demonstrates that the stellar masses of galaxies in the Galaxy and Mass Assembly (GAMA) survey, originally derived via stellar population synthesis modelling, can be accurately predicted using only their absolute magnitudes and…
Because of the 3D nature of galaxies, an algorithm for constructing spatial density distribution models of galaxies on the basis of galaxy images has many advantages over surface density distribution approximations. We present a method for…
We have analyzed the redshift-dependent fraction of galactic bars over 0.2<z<0.84 in 2,157 luminous face-on spiral galaxies from the COSMOS 2-square degree field. Our sample is an order of magnitude larger than that used in any previous…
Recently, machine learning methods presented a viable solution for automated classification of image-based data in various research fields and business applications. Scientists require a fast and reliable solution to be able to handle the…
We present first results from Galaxy Zoo 2, the second phase of the highly successful Galaxy Zoo project (www.galaxyzoo.org). Using a volume-limited sample of 13665 disk galaxies (0.01< z < 0.06 and M_r<-19.38), we study the fraction of…
We present a study of the connection between the galactic spin parameter $\lambda_{d}$ and the bar fraction in a volume-limited sample of 10,674 disk galaxies drawn from the Sloan Digital Sky Survey Data Release 7. The galaxies in our…
We developed an iterative technique to better characterize stellar populations and the central activity of barred galaxies using evolutionary synthesis codes and OASIS data. The case of NGC5430 is presented here. Our results are reinforcing…
A simple, fully connected neural network with a single hidden layer is used to estimate stellar masses for star-forming galaxies. The model is trained on broad-band photometry - from far-ultraviolet to mid-infrared wavelengths - generated…
We study a sample of bar-like galaxies in the Illustris TNG100 simulation, in which almost the whole stellar component is in the form of a prolate spheroid. The sample is different from the late-type barred galaxies studied before. In…
Modern surveys such as Euclid report a decline in the fraction of barred galaxies from the local Universe to $z \sim 1$, whereas the TNG50 simulation predicts higher bar fractions, in tension with observations. This discrepancy may be due…
Distinguishing active galaxies from star-forming galaxies is essential for understanding galaxy evolution. Diagnostic methods like the BPT (Baldwin, Phillips, and Terlevich) diagram use optical emission-line ratios to separate galaxies.…
We apply a new deep learning technique to detect, classify, and deblend sources in multi-band astronomical images. We train and evaluate the performance of an artificial neural network built on the Mask R-CNN image processing framework, a…
The scale of ongoing and future electromagnetic surveys pose formidable challenges to classify astronomical objects. Pioneering efforts on this front include citizen science campaigns adopted by the Sloan Digital Sky Survey (SDSS). SDSS…
Understanding the role of galactic scale bars in disk galaxy evolution requires detailed measurements of bar properties across galaxies hosting bars at many redshifts. We present measurements of bar lengths and widths in a sample of 8230…
We have undertaken a dedicated program of automatic source classification in the WISE database merged with SuperCOSMOS scans, comprehensively identifying galaxies, quasars and stars on most of the unconfused sky. We use the Support Vector…