相关论文: Automatic unsupervised classification of all SDSS/…

Modern spectroscopic surveys can only target a small fraction of the vast amount of photometrically cataloged sources in wide-field surveys. Here, we report the development of a generative AI method capable of predicting optical galaxy…

Methods. We used different galaxy classification techniques: human labeling, multi-photometry diagrams, Naive Bayes, Logistic Regression, Support Vector Machine, Random Forest, k-Nearest Neighbors, and k-fold validation. Results. We present…

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…

A sample of nearly 9000 early-type galaxies, in the redshift range 0.01 < z < 0.3, was selected from the Sloan Digital Sky Survey using morphological and spectral criteria. This paper describes how the sample was selected, presents examples…

Studies of galaxy populations classified according to their kinematic behaviours and dynamical state using the Projected Phase Space Diagram (PPSD) are affected by misclassification and contamination, leading to systematic errors in…

We used the galaxy spectra obtained in the ESO Nearby Abell Cluster Survey (ENACS) to separate early- and late-type galaxies in the ENACS clusters, by applying a Principal Component Analysis (PCA) in combination with an Artificial Neural…

A new method for classification of galaxy spectra is presented, based on a recently introduced information theoretical principle, the `Information Bottleneck'. For any desired number of classes, galaxies are classified such that the…

Stellar spectroscopic classification has been successfully automated by a number of groups. Automated classification and parameterization work best when applied to a homogeneous data set, and thus these techniques primarily have been…

We present the results of an analysis of a well-selected sample of galaxies with active and inactive galactic nuclei from the Sloan Digital Sky Survey, in the range 0.01 < z < 0.16. The SDSS galaxy catalogue was split into two classes of…

We present a novel unsupervised learning approach to automatically segment and label images in astronomical surveys. Automation of this procedure will be essential as next-generation surveys enter the petabyte scale: data volumes will…

To investigate the dependence of the occurrence of active galactic nuclei (AGNs) on local galaxy density, we study the nuclear properties of ~5000 galaxies in the Coma Supercluster whose density spans 2 orders of magnitude from the sparse…

We have constructed an all-sky catalog of optical AGNs with $z < 0.09$, based on optical spectroscopy, from the parent sample of galaxies in the 2MASS Redshift Survey (2MRS), a near-complete census of the nearby universe. Our catalog…

We describe the algorithm that selects the main sample of galaxies for spectroscopy in the Sloan Digital Sky Survey from the photometric data obtained by the imaging survey. Galaxy photometric properties are measured using the Petrosian…

We present a study of the connection between star-forming galaxies, AGN host galaxies, and normal early-type galaxies in the Sloan Digital Sky Survey (SDSS). Using the SDSS DR5 and DR4plus data, we select our early-type galaxy sample in the…

While it is clear that spiral galaxies can have different handedness, galaxies with clockwise patterns are assumed to be symmetric in all of their other characteristics to galaxies with counterclockwise patterns. Here we use data from SDSS…

Galaxy clusters can be detected as surface brightness enhancements in smoothed optical surveys. This method does not require individual galaxies to be identifiable, and enables clusters to be detected out to surprisingly high redshifts, as…

With the aim of investigating galaxies with two strong simultaneous starbursts, we have extracted a sample of galaxies with double-peaked emission lines in their global spectra from the SDSS spectral database. We then fitted the emission…

Various galaxy classification schemes have been developed so far to constrain the main physical processes regulating evolution of different galaxy types. In the era of a deluge of astrophysical information and recent progress in machine…

Algebraic Subspace Clustering (ASC) is a simple and elegant method based on polynomial fitting and differentiation for clustering noiseless data drawn from an arbitrary union of subspaces. In practice, however, ASC is limited to…

An empirical method of modeling the stellar spectrum of galaxies is proposed, based on two successive applications of Principal Component Analysis (PCA). PCA is first applied to the newly available stellar library STELIB, supplemented by…