Search

Stellar spectral template libraries play an important role in the automated analysis of stellar spectra. Synthetic template libraries cover a very large parameter space but suffer from poor matching with observed spectra. In this study, we propose a synthetic-to-observed spectral translation (SOST) method based on generative adversarial networks. The SOST method is able to calibrate synthetic spectra by converting them to the corresponding observed spectra. We applied this method to Kurucz synthetic spectra and observed spectra data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST). After that, we constructed a stellar spectral library with uniform and broad parameter distributions using the SOST-corrected Kurucz synthetic spectra. Our stellar spectral template library contains 2431 spectra spanning a parameter space of 3500–8000 K for effective temperature (Teff), 0.0–5.0 dex for surface gravity (log g), and −2.0–0.5 dex for metallicity ([Fe/H]). The spectra in the library have a resolution of R ∼ 1800 and cover the wavelength range 3900–8700 Å. In order to verify the accuracy of this template library, we used the template library and the template-matching algorithm to derive the parameters of the PASTEL database. Compared to measurements using the original synthetic template library, the accuracies of the three parameters, Teff, log g, and [Fe/H], are improved, from 140 K, 0.31 dex, and 0.21 dex to 121 K, 0.26 dex, and 0.13 dex, respectively. In addition, we re-parameterised more than six million stellar spectra released by LAMOST DR8. [ABSTRACT FROM AUTHOR]

Context. A successful identification of an interstellar compound requires that its spectrum has first been assigned in the laboratory. New and sensitive radiotelescopes, such as ALMA, will make it possible to detect interstellar molecules in much smaller concentrations than before. Cyanoallene (CH2=C=CH-CN) has recently been observed in the dense molecular cloud TMC-1 by means of its rotational spectrum. Its methyl congener, 4-methylcyanoallene (CH3CH=C=CH-CN), may also be present in the interstellar medium (ISM). This chiral compound exists in two forms, which are mirror images. Chirality is an essential feature of life. So far, no chiral compounds have been detected in the ISM. Aims. The synthesis and assignment of the rotational spectrum of CH3CH=C=CH-CN, will facilitate the potential detection of this compound in the ISM. Methods. The spectrum of 4-methylcyanoallene has been recorded between 13 and 116 GHz using the microwave spectrometer at the University of Oslo. The spectroscopic study has been augmented with high-level quantum chemical calculations at the B3LYP/ccpVTZ and CCSD/cc-pVTZ levels of theory. Results. The rotational spectra of CH3CH=C=CH-CN in the ground vibrational state and in the first vibrationally excited state are reported for the first time and accurate spectroscopic constants have been obtained from a large number of transitions. [ABSTRACT FROM AUTHOR]

Context. Accurate determination of the redshifts of galaxies comes from the identification of key lines in their spectra. Large sky surveys, and the sheer volume of data they produce, have made it necessary to tackle this identification problem in an automated and reliable fashion. Current methods attempt to do this with careful modelling of the spectral lines and the continua, or by employing a flux/magnitude or a signal-to-noise cut to the dataset in order to obtain reliable redshift estimates for the majority of galaxies in the sample. Aims. In this paper, we present the Darth Fader algorithm (denoised and automatic redshifts thresholded with a false detection rate), which is a new wavelet-based method for estimating redshifts of galaxy spectra. Automated, simple, and largely empirical, we highlight how the Darth Fader algorithm performs in the very low signal-to-noise regime, and demonstrate its effectiveness at removing catastrophic failures from the catalogue of redshift estimates. Methods. We present a new, nonparametric method for estimating and removing the continuum in noisy data that requires no a priori information about the galaxy properties. This method employs wavelet filtering based on a tuneable false detection rate (FDR) threshold, which effectively removes the noise in the spectrum, and extracts features at different scales. After removal of the continuum, the galaxy spectra are then cross-correlated with the eigentemplates, and a standard χ2-minimisation used to determine the redshift of the spectrum. FDR filtering is applied to the spectra a second time to determine the number of spectral features in each galaxy spectrum, and those with fewer than six total features are removed from the catalogue as we are unlikely to obtain a reliable and correct estimate of the redshift of such spectra. Results. Applying our wavelet-based cleaning algorithm on a simulated testing set, we can successfully build a clean catalogue including extremely low signal-to-noise data (S/N = 2.0), for which we are able to obtain a 5.1% catastrophic failure rate in the redshift estimates (compared with 34.5% prior to cleaning). We also show that for a catalogue with uniformly mixed signal-to-noise ratios between 1.0 and 20.0, with realistic pixel-dependent noise, it is possible to obtain redshifts with a catastrophic failure rate of 3.3% after cleaning (as compared to 22.7% before cleaning). Whilst we do not test this algorithm exhaustively on real data, we present a proof of concept of the applicability of this method to real data, showing that the wavelet filtering techniques perform well when applied to some typical spectra from the Sloan Digital Sky Survey archive. Conclusions. The Darth Fader algorithm provides a robust method for extracting spectral features from very noisy spectra: spectra for which a reliable redshift cannot be measured are automatically identified and removed from the input data set. The resulting clean catalogue, although restricted in number, gives an extremely low rate of catastrophic failures, even when the spectra have a very low S/N. For very large sky surveys, this technique may offer a significant boost in the number of faint galaxies with accurately determined redshifts. [ABSTRACT FROM AUTHOR]

Context. The large amount of spectra obtained during the epoch of extensive spectroscopic surveys of Galactic stars needs the development of automatic procedures to derive their atmospheric parameters and individual element abundances. Aims. Starting from the widely-used code MOOG by C. Sneden, we have developed a new procedure to determine atmospheric parameters and abundances in a fully automatic way. The code FAMA (Fast Automatic MOOG Analysis) is presented describing its approach to derive atmospheric stellar parameters and element abundances. The code, freely distributed, is written in Perl and can be used on di erent platforms. Methods. The aim of FAMA is to render the computation of the atmospheric parameters and abundances of a large number of stars using measurements of equivalent widths (EWs) as automatic and as independent of any subjective approach as possible. It is based on the simultaneous search for three equilibria: excitation equilibrium, ionization balance, and the relationship between log n(Fe i) and the reduced EWs. FAMA also evaluates the statistical errors on individual element abundances and errors due to the uncertainties in the stellar parameters. The convergence criteria are not fixed "a priori" but are based on the quality of the spectra. Results. In this paper we present tests performed on the solar spectrum EWs that assess the method's dependency on the initial parameters and we analyze a sample of stars observed in Galactic open and globular clusters. [ABSTRACT FROM AUTHOR]