相关论文: Spectral classification
The advent of large-scale spectroscopic surveys underscores the need to develop robust techniques for determining stellar properties ("labels", i.e., physical parameters and elemental abundances). However, traditional spectroscopic methods…
Due to the ever-expanding volume of observed spectroscopic data from surveys such as SDSS and LAMOST, it has become important to apply artificial intelligence (AI) techniques for analysing stellar spectra to solve spectral classification…
A set of points $S$ in $d$-dimensional Euclidean space $\mathbb{R}^d$ is called a 2-distance set if the set of pairwise distances between the points has cardinality two. The 2-distance set is called spherical if its points lie on the unit…
The method developed by Stock and Stock (1999) for stars of spectral types A to K to derive absolute magnitudes and intrinsic colors from the equivalent widths of absorption lines in stellar spectra is extended to B-type stars. Spectra of…
Quantitative spectroscopy is a powerful technique from which we can extract information about the physical properties and surface chemical composition of stars. In this chapter, I guide the reader through the main ideas required to get…
Low-mass stars and brown dwarfs -- spectral types (SpTs) M0 and later -- play a significant role in studying stellar and substellar processes and demographics, reaching down to planetary-mass objects. Currently, the classification of these…
Achieving high accuracy and precision in stellar parameter and chemical composition determinations is challenging in massive star spectroscopy. On one hand, the target selection for an unbiased sample build-up is complicated by several…
The fast classification of new variable stars is an important step in making them available for further research. Selection of science targets from large databases is much more efficient if they have been classified first. Defining the…
Spectral clustering has become a popular technique due to its high performance in many contexts. It comprises three main steps: create a similarity graph between N objects to cluster, compute the first k eigenvectors of its Laplacian matrix…
Michelson phase and Hanbury Brown-Twiss intensity stellar interferometry require expressions for the first- and second-order correlation functions, respectively, of the fields radiated by stars in terms of their diameters and measured…
Spectral clustering is a popular algorithm that clusters points using the eigenvalues and eigenvectors of Laplacian matrices derived from the data. For years, spectral clustering has been working mysteriously. This paper explains spectral…
Spectroscopy is one of the most important tools that an astronomer has for studying the universe. This chapter begins by discussing the basics, including the different types of optical spectrographs, with extension to the ultraviolet and…
We present a technique which employs artificial neural networks to produce physical parameters for stellar spectra. A neural network is trained on a set of synthetic optical stellar spectra to give physical parameters (e.g. T_eff, log g,…
Spectral methods have emerged as a simple yet surprisingly effective approach for extracting information from massive, noisy and incomplete data. In a nutshell, spectral methods refer to a collection of algorithms built upon the eigenvalues…
Spectral evolution models are a widely used tool for determining the stellar content of galaxies. I provide a review of the latest developments in stellar atmosphere and evolution models, with an emphasis on massive stars. In contrast to…
This short paper is to be published as part of the centennial celebrations of the American Astronomical Society. It presents some historical background on, and discusses the importance of, the 1953 paper by H.L. Johnson and W.W. Morgan, in…
The Main Sequence (MS) of star-forming galaxies plays a fundamental role in driving galaxy evolution and in our efforts to understand it. However, different studies find significant differences in the normalization, slope and shape of the…
M dwarfs are the most abundant stars in the Solar Neighborhood and they are prime targets for searching for rocky planets in habitable zones. Consequently, a detailed characterization of these stars is in demand. The spectral sub-type is…
A number of about 1500 spectroscopically classified CP2 stars in the southern sky (delta =-90 to -12 degrees) was extracted from the Michigan Catalogue (Vols. I - IV). This sample was compared with the classification from Bidelman & Mc…
This paper studies the performance of the spectral method in the estimation and uncertainty quantification of the unobserved preference scores of compared entities in a general and more realistic setup. Specifically, the comparison graph…