arXiv subjects

Wen Hou

Publications and source records attributed to Wen Hou.

26 records · Page 2Linked to original sources

arXiv2018

Carbon stars identified from LAMOST DR4 using Machine Learning

In this work, we present a catalog of 2651 carbon stars from the fourth Data Release (DR4) of the Large Sky Area Multi-Object Fiber Spectroscopy Telescope (LAMOST). Using an efficient machine-learning algorithm, we find out these stars from more than seven million spectra. As a by-product, 17 carbon-enhanced metal-poor (CEMP) turnoff star candidates are also reported in this paper, and they are preliminarily identified by their atmospheric parameters. Except for 176 stars that could not be given spectral types, we classify the other 2475 carbon stars into five subtypes including 864 C-H, 226 C-R, 400 C-J, 266 C-N, and 719 barium stars based on a series of spectral features. Furthermore, we divide the C-J stars into three subtypes of CJ( H), C-J(R), C-J(N), and about 90% of them are cool N-type stars as expected from previous literature. Beside spectroscopic classification, we also match these carbon stars to multiple broadband photometries. Using ultraviolet photometry data, we find that 25 carbon stars have FUV detections and they are likely to be in binary systems with compact white dwarf companions.

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arXiv2017

Spectral classification and composites of galaxies in LAMOST DR4

We study the classification and composite spectra of galaxy in the fourth data release (DR4) of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). We select 40,182 spectra of galaxies from LAMOST DR4, which have photometric in- formation but no spectroscopic observations in the Sloan Digital Sky Survey(SDSS). These newly observed spectra are re-calibrated and classified into six classes, i.e. pas- sive, Hα-weak, star-forming, composite, LINER and Seyfert using the line intensity (H\b{eta}, [OIII]λ5007, Hα and [NII]λ6585). We also study the correlation between spectral classes and morphological types through three parameters: concentration index, (u - r) color, and D4000n index. We calculate composite spectra of high signal-to-noise ra- tio(S/N) for six spectral classes, and using these composites we pick out some features that can differentiate the classes effectively, including H\b{eta}, Fe5015, HγA, HK, and Mg2 band etc. In addition, we compare our composite spectra with the SDSS ones and analyse their difference. A galaxy catalogue of 40,182 newly observed spectra (36,601 targets) and the composite spectra of the six classes are available online.

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arXiv2016

LAMOST Spectrograph Response Curves: Stability and Application to flux calibration

The task of flux calibration for LAMOST (Large sky Area Multi-Object Spectroscopic Telescope) spectra is difficult due to many factors. For example, the lack of standard stars, flat fielding for large field of view, and variation of reddening between different stars especially at low galactic latitudes etc. Poor selection, bad spectral quality, or extinction uncertainty of standard stars not only might induce errors to the calculated spectral response curve (SRC), but also might lead to failures in producing final 1D spectra. In this paper, we inspected spectra with Galactic latitude |b|>=60 degree and reliable stellar parameters, determined through the LAMOST Stellar Parameter Pipeline (LASP), to study the stability of the spectrograph. To guarantee the selected stars had been observed by each fiber, we selected 37,931 high quality exposures of 29,000 stars from LAMOST DR2, and more than 7 exposures for each fiber. We calculated the SRCs for each fiber for each exposure, and calculated the statistics of SRCs for spectrographs with both the fiber variations and time variations. The result shows that the average response curve of each spectrograph (henceforth ASPSRC) is relatively stable with statistical errors <= 10%. From the comparison between each ASPSRC and the SRCs for the same spectrograph obtained by 2D pipeline, we find that the ASPSRCs are good enough to use for the calibration. The ASPSRCs have been applied to spectra which were abandoned by LAMOST 2D pipeline due to the lack of standard stars, increasing the number of LAMOST spectra by 52,181 in DR2. Comparing those same targets with SDSS, the relative flux differences between SDSS spectra and that of LAMOST spectra with the ASPSRC method are less than 10%, which underlines that the ASPSRC method is feasible for LAMOST flux calibration.

astro-ph.IM↗

arXiv2016

A catalogue of early-type emission-line stars and Hα line profiles from LAMOST DR2

We present a catalogue including 11,204 spectra for 10,436 early-type emission-line stars from LAMOST DR2, among which 9,752 early-type emission-line spectra are newly discovered. For these early-type emission-line stars, we discuss the morphological and physical properties from their low-resolution spectra. In this spectral sample, the H$α$ emission profiles display a wide variety of shapes. Based on the H$α$ line profiles, these spectra are categorized into five distinct classes: single-peak emission, single-peak emission in absorption, double-peak emission, double-peak emission in absorption, and P-Cygni profiles. To better understand what causes the H$α$ line profiles, we divide these objects into four types from the view of physical classification, which include classical Be stars, Herbig Ae/Be stars, close binaries and spectra contaminated by HII regions. The majority of Herbig Ae/Be stars and classical Be stars are identified and separated using the (H-K, K-W1) color-color diagram. We also discuss thirty one binary systems as listed in SIMBAD on-line catalogue and identify 3,600 spectra contaminated by HII regions after cross matching with positions in the Dubout-Crillon catalogue. A statistical analysis of line profiles versus classifications is then conducted in order to understand the distribution of H$α$ profiles for each type in our sample. Finally, we also provide a table of 172 spectra with FeII emission lines and roughly calculate stellar wind velocities for seven spectra with P-Cygni profiles.

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arXiv2016

An Efficient Method for Rare Spectra Retrieval in Astronomical Databases

One of important aims of astronomical data mining is to systematically search for specific rare objects in a massive spectral dataset, given a small fraction of identified samples with the same type. Most existing methods are mainly based on binary classification, which usually suffer from uncompleteness when the known samples are too few. While, rank-based methods would provide good solutions for such case. After investigating several algorithms, a method combining bipartite ranking model with bootstrap aggregating techniques was developed in this paper. The method was applied in searching for carbon stars in the spectral data of Sloan Digital Sky Survey (SDSS) DR10, and compared with several other popular methods used in data mining. Experimental results validate that the proposed method is not only the most effective but also less time consuming among these competitors automatically searching for rare spectra in a large but unlabelled dataset.128

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arXiv2015

A Sample of E+A Galaxy Candidates in LAMOST Data Released 2

A sample of 70 E+A galaxies are selected from 37, 206 galaxies in the second data release (DR2) of Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) according to the criteria for E+A galaxies defined by Goto, and each of these objects is further visually identified. In this sample, most objects are low redshift E+A galaxies with z < 0.25, and locate in the high latitude sky area with magnitude among 14 to 18 mag in g, r and i bands. A stellar population analysis for the whole sample indicates that the E+A galaxies are characterized by both young and old stellar populations (SPs), and the metal-rich SPs have relatively higher contributions than the metal-poor ones. Additionally, a morphological classification for these objects is performed based on the images taken from the Sloan Digital Sky Survey (SDSS).

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arXiv2015

A Large Sample of Am Candidates from LAMOST Data Release 1

We present a sample of metallic-line star (Am) candidates from the Large sky Area Multi-Object fiber Spectroscopic Telescope Data Release one (LAMOST DR1). According to the characteristic of under-abundance of calcium and overabundance of iron element of Am stars, we propose an empirical separation curve derived from line indices of Ca II K-line and iron lines we choose for low resolution spectra. 3537 Am candidates are ultimately selected from more than 30,000 stars which are classified as A-type or early-F stars by both LAMOST pipeline and visual inspection. Then we make some analysis on this sample and finally provide a list of these Am candidates with 10 relevant parameters. Comparing with other catalogues, Am candidates selected from LAMOST DR1 are much fainter on the whole. Obviously, our list is an important complementary to already known bright Am catalogues, and it offers valuable material for the research on this type of chemically peculiar stars.

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arXiv2014

A Search for Spectral Galaxy Pairs of Overlapping Galaxies based on Fuzzy Recognition

The Spectral Galaxy Pairs (SGPs) are defined as the composite galaxy spectra which contain two independent redshift systems. These spectra are useful for studying dust properties of the foreground galaxies. In this paper, a total of 165 spectra of SGPs are mined out from Sloan Digital Sky Survey (SDSS) Data Release 9 (DR9) using the concept of membership degree from the fuzzy set theory particularly defined to be suitable for fuzzily identifying emission lines. The spectra and images of this sample are classified according to the membership degree and their image features, respectively. Many of these 2nd redshift systems are too small or too dim to select from the SDSS images alone, making the sample a potentially unique source of information on dust effects in low-luminosity or low-surface-brightness galaxies that are underrepresented in morphological pair samples. The dust extinction of the objects with high membership degree is also estimated by Balmer decrement. Additionally, analyses for a series of spectroscopic observations of one SGP from 165 systems indicate that a newly star-forming region of our Milky Way might occur.

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