相关论文: Spiral-Elliptical automated galaxy morphology clas…

We present a method to simulate deep sky images, including realistic galaxy morphologies and telescope characteristics. To achieve a wide diversity of simulated galaxy morphologies, we first use the shapelets formalism to parametrize the…

We suggest a set of morphological measures that we believe can help in quantifying the shapes of two-dimensional cosmological images such as galaxies, clusters, and superclusters of galaxies. The method employs non-parametric morphological…

The optical morphology of galaxies is strongly related to galactic environment, with the fraction of early-type galaxies increasing with local galaxy density. In this work we present the first analysis of the galaxy morphology-density…

Classification of galaxies is traditionally associated with their morphologies through visual inspection of images. The amount of data to come renders this task inhuman and Machine Learning (mainly Deep Learning) has been called to the…

One of the most important properties of a galaxy is the total stellar mass, or equivalently the stellar mass-to-light ratio (M/L). It is not directly observable, but can be estimated from stellar population synthesis. Currently, a galaxy's…

Structural properties posses valuable information about the formation and evolution of galaxies, and are important for understanding the past, present, and future universe. Here we use unsupervised machine learning methodology to analyze a…

We devise improved photometric parameters for the morphological classification of galaxies using a bright sample from the First Data Release of the Sloan Digital Sky Survey. In addition to using an elliptical aperture concentration index…

We applied computer analysis to classify the broad morphological type of ~3,000,000 SDSS galaxies. The catalog provides for each galaxy the DR8 object ID, right ascension, declination, and the certainty of the automatic classification to…

We describe a system for the automatic quantification of structure in spiral galaxies. This enables translation of sky survey images into data needed to help address fundamental astrophysical questions such as the origin of spiral…

(abridged) In the last decade, the advent of enormous galaxy surveys has motivated the development of automated morphological classification schemes to deal with large data volumes. Existing automated schemes can successfully distinguish…

Morphology is the starting point for understanding galaxies. Elmegreen et al. classified spiral galaxies into flocculent, multiple-arm, and grand-design galaxies based on the regularity of their spiral arm structure. With the release of a…

We address the problem of morphological classification of galaxies from the Galaxy Zoo DECaLS dataset using classical machine learning techniques. Our approach employs a dimensionality reduction method followed by a classical classifier to…

We train three convolutional neural networks (CNNs) to classify galaxies with Galaxy Zoo 2 dataset and extract the activations from the last fully connected layer or the last average pooling layer of CNNs to study the high-dimensional…

Understanding morphological types of galaxies is a key parameter for studying their formation and evolution. Neural networks that have been used previously for galaxy morphology classification have some disadvantages, such as not being…

The correlation between a galaxy's morphology and its observed optical spectrum is investigated. As an example, 4000 galaxies from the 2dF Galaxy Redshift Survey, which possess both good quality spectra and have visually determined…

By applying our previously developed two-step scheme for galaxy morphology classification, we present a catalog of galaxy morphology for H-band selected massive galaxies in the COSMOS-DASH field, which includes 17292 galaxies with stellar…

We develop a straightforward and quantitative two-step method for spectroscopically classifying galaxies from the low signal-to-noise (S/N) optical spectra typical of galaxy redshift surveys. First, using \chi^2-fitting of characteristic…

Galaxy morphology offers significant insights into the evolutionary pathways and underlying physics of galaxies. As astronomical data grows with surveys such as Euclid and Vera C. Rubin , there is a need for tools to classify and analyze…

A major goal of contemporary astrophysics is understanding the origin of the most massive galaxies in the universe, particularly nearby ellipticals and spirals. Theoretical models of galaxy formation have existed for many decades, although…

The morphological diversity of galaxies is a relevant probe of galaxy evolution and cosmological structure formation. However, in large sky surveys, even the morphological classification of galaxies into two classes, like late-type (LT) and…