Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userLAMOST Observations in 15 textit{K}2 Campaigns: I. Low resolution spectra from LAMOST DR6
236
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
The LAMOST-textit{K}2 (Ltextit{K}2) project, initiated in 2015, aims to collect low-resolution spectra of targets in the textit{K}2 campaigns, similar to LAMOST-textit{Kepler} project. By the end of 2018, a total of 126 Ltextit{K}2 plates had been observed by LAMOST. After cross-matching the catalog of the LAMOST data release 6 (DR6) with that of the textit{K}2 approved targets, we found 160,619 usable spectra of 84,012 objects, most of which had been observed more than once. The effective temperature, surface gravity, metallicity, and radial velocity from 129,974 spectra for 70,895 objects are derived through the LAMOST Stellar Parameter Pipeline (LASP). The internal uncertainties were estimated to be 81 K, 0.15 dex, 0.09 dex and 5 kms$^{-1}$, respectively, when derived from a spectrum with a signal-to-noise ratio in the $g$ band (SNR$_g$) of 10. These estimates are based on results for targets with multiple visits. The external accuracies were assessed by comparing the parameters of targets in common with the APOGEE and GAIA surveys, for which we generally found linear relationships. A final calibration is provided, combining external and internal uncertainties for giants and dwarfs, separately. We foresee that these spectroscopic data will be used widely in different research fields, especially in combination with textit{K}2 photometry.
rate research
Read More
We set out to determine stellar labels from low-resolution survey spectra of hot, OBA stars with effective temperature (Teff) higher than 7500K. This fills a gap in the scientific analysis of large spectroscopic stellar surveys such as LAMOST, which offers spectra for millions of stars at R=1800. We first explore the theoretical information content of such spectra for determining stellar labels, via the Cramer-Rao bound. We show that in the limit of perfect model spectra and observed spectra with S/N of 100, precise estimates are possible for a wide range of stellar labels: not only the effective temperature Teff, surface gravity logg, and projected rotation velocity vsini, but also the micro-turbulence velocity, Helium abundance and the elemental abundances [C/H], [N/H], [O/H], [Si/H], [S/H], and [Fe/H]. Our analysis illustrates that the temperature regime of around 9500K is challenging, as the dominant Balmer and Paschen line strength vary little with Teff. We implement the simultaneous fitting of these 11 stellar labels to LAMOST hot-star spectra using the Payne approach, drawing on Kuruczs ATLAS12/SYNTHE LTE spectra as the underlying models. We then obtain stellar parameter estimates for a sample of about 330,000 hot stars with LAMOST spectra, an increase by about two orders of magnitude in sample size. Among them, about 260,000 have good Gaia parallaxes (S/N>5), and more than 95 percent of them are luminous stars, mostly on the main sequence; the rest reflects lower luminosity evolved stars, such as hot subdwarfs and white dwarfs. We show that the fidelity of the abundance estimates is limited by the systematics of the underlying models, as they do not account for NLTE effects. Finally, we show the detailed distribution of vsini of stars with 8000-15,000K, illustrating that it extends to a sharp cut-off at the critical rotation velocity, across a wide range of temperatures.
The nearly continuous light curves with micromagnitude precision provided by the space mission Kepler are revolutionising our view of pulsating stars. They have revealed a vast sea of low-amplitude pulsation modes that were undetectable from Earth. The long time base of Kepler light curves allows an accurate determination of frequencies and amplitudes of pulsation modes needed for in-depth asteroseismic modeling. However, for an asteroseismic study to be successful, the first estimates of stellar parameters need to be known and they can not be derived from the Kepler photometry itself. The Kepler Input Catalog (KIC) provides values for the effective temperature, the surface gravity and the metallicity, but not always with a sufficient accuracy. Moreover, information on the chemical composition and rotation rate is lacking. We are collecting low-resolution spectra for objects in the Kepler field of view with the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST, Xinglong observatory, China). All of the requested fields have now been observed at least once. In this paper we describe those observations and provide a database of use to the whole astronomical community.
LAMOST DR5 released more than 200,000 low resolution spectra of early-type stars with S/N>50. Searching for metallic-line (Am) stars in such a large database and study of their statistical properties are presented in this paper. Six machine learning algorithms were experimented with using known Am spectra, and both the empirical criteria method(Hou et al. 2015) and the MKCLASS package(Gray et al. 2016) were also investigated. Comparing their performance, the random forest (RF) algorithm won, not only because RF has high successful rate but also it can derives and ranks features. Then the RF was applied to the early type stars of DR5, and 15,269 Am candidates were picked out. Manual identification was conducted based on the spectral features derived from the RF algorithm and verified by experts. After manual identification, 9,372 Am stars and 1,131 Ap candidates were compiled into a catalog. Statistical studies were conducted including temperature distribution, space distribution, and infrared photometry. The spectral types of Am stars are mainly between F0 and A4 with a peak around A7, which is similar to previous works. With the Gaia distances, we calculated the vertical height Z from the Galactic plane for each Am star. The distribution of Z suggests that the incidence rate of Am stars shows a descending gradient with increasing jZj. On the other hand, Am stars do not show a noteworthy pattern in the infrared band. As wavelength gets longer, the infrared excess of Am stars decreases, until little or no excess in W1 and W2 bands.
182 single-lined hot subdwarf stars are identified by using spectra from the sixth and seventh data release (DR6 and DR7) of the Large Sky Area Multi-Object Fibre Spectroscopic Telescope (LAMOST) survey. We classified all the hot subdwarf stars using a canonical classification scheme, and got 89 sdB, 37 sdOB, 26 sdO, 24 He-sdOB, 3 He-sdO and 3 He-sdB stars, respectively. Among these stars, 108 hot subdwarfs are newly discovered, while 74 stars were reported by previous catalogs. The atmospheric parameters of these stars were obtained by fitting the hydrogen (H) and helium (He) lines with non-local thermodynamic equilibrium (non-LTE) model atmospheres. The atmospheric parameters confirm the two He sequences and the two subgroups of He-sdOB stars in our samples, which were found by previous studies in the T eff -log(nHe/nH) diagram. Our results demonstrate different origins of field hot subdwarf stars and extreme horizontal branch (EHB) stars in globular clusters (GCs), and provide strict observational limits on the formation and evolution models of the different sub-types of these evolved objects. Based on the results, we evaluated the completeness of the Geier et al. (2019) catalog. We found the fraction of hot subdwarf stars is between 10% and 60%, depending on the brightness of the sample. A more accurate estimation for the hot subdwarf fraction can be obtained when similar results from composite spectra will become available.
LAMOST Data Release 5, covering $sim$17,000 $deg^2$ from $-10^{circ}$ to $80^{circ}$ in declination, contains 9 millions co-added low resolution spectra of celestial objects, each spectrum combined from repeat exposure of two to tens of times during Oct 2011 to Jun 2017. In this paper, We present the spectra of individual exposures for all the objects in LAMOST Data Release 5. For each spectrum, equivalent width of 60 lines from 11 different elements are calculated with a new method combining the actual line core and fitted line wings. For stars earlier than F type, the Balmer lines are fitted with both emission and absorption profiles once two components are detected. Radial velocity of each individual exposure is measured by minimizing ${chi}^2$ between the spectrum and its best template. Database for equivalent widths of spectral lines and radial velocities of individual spectra are available online. Radial velocity uncertainties with different stellar type and signal-to-noise ratio are quantified by comparing different exposure of the same objects. We notice that the radial velocity uncertainty depends on the time lag between observations. For stars observed in the same day and with signal-to-noise ratio higher than 20, the radial velocity uncertainty is below 5km/s, and increase to 10km/s for stars observed in different nights.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
