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| 2. |
- Puspitarini, L., et al.
(författare)
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The Gaia-ESO Survey: Extracting diffuse interstellar bands from cool star spectra DIB-based interstellar medium line-of-sight structures at the kpc scale
- 2015
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Ingår i: Astronomy & Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 573
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Tidskriftsartikel (refereegranskat)abstract
- Aims. We study how diffuse interstellar bands (DIBs) measured toward distance-distributed target stars can be used to locate dense interstellar (IS) clouds in the Galaxy and probe a line-of-sight (LOS) kinematical structure, a potentially useful tool when gaseous absorption lines are saturated or not available in the spectral range. Cool target stars are numerous enough for this purpose. Methods. We devised automated DIB-fitting methods appropriate for cool star spectra and multiple IS components. The data were fitted with a combination of a synthetic stellar spectrum, a synthetic telluric transmission, and empirical DIB profiles. The initial number of DIB components and their radial velocity were guided by HI 21 cm emission spectra, or, when available in the spectral range, IS neutral sodium absorption lines. For NaI, radial velocities of NaI lines and DIBs were maintained linked during a global simultaneous fit. In parallel, stellar distances and extinctions were estimated self-consistently by means of a 2D Bayesian method from spectroscopically-derived stellar parameters and photometric data. Results. We have analyzed Gaia-ESO Survey (GES) spectra of 225 stars that probe between similar to 2 and 10 kpc long LOS in five different regions of the Milky Way. The targets are the two CoRoT fields, two open clusters (NGC 4815 and gamma Vel), and the Galactic bulge. Two OGLE fields toward the bulge observed before the GES are also included (205 target stars). Depending on the observed spectral intervals, we extracted one or more of the following DIBs: lambda lambda 6283.8, 6613.6, and 8620.4. For each field, we compared the DIB strengths with the Bayesian distances and extinctions, and the DIB Doppler velocities with the HI emission spectra. Conclusions. For all fields, the DIB strength and the target extinction are well correlated. For targets that are widely distributed in distance, marked steps in DIBs and extinction radial distance profiles match each other and broadly correspond to the expected locations of spiral arms. For all fields, the DIB velocity structure agrees with HI emission spectra, and all detected DIBs correspond to strong NaI lines. This illustrates how DIBs can be used to locate the Galactic interstellar gas and to study its kinematics at the kpc scale, as illustrated by Local and Perseus Arm DIBs that differ by greater than or similar to 30 km s(-1), in agreement with HI emission spectra. On the other hand, if most targets are located beyond the main absorber, DIBs can trace the differential reddening within the field.
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- Cescutti, G., et al.
(författare)
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MINCE I. Presentation of the project and of the first year sample
- 2022
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 668
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Tidskriftsartikel (refereegranskat)abstract
- Context. In recent years, Galactic archaeology has become a particularly vibrant field of astronomy, with its main focus set on the oldest stars of our Galaxy. In most cases, these stars have been identified as the most metal-poor. However, the struggle to find these ancient fossils has produced an important bias in the observations - in particular, the intermediate metal-poor stars (-2.5 < [Fe/H] < -1.5) have been frequently overlooked. The missing information has consequences for the precise study of the chemical enrichment of our Galaxy, in particular for what concerns neutron capture elements and it will be only partially covered by future multi object spectroscopic surveys such as WEAVE and 4MOST.Aims. Measuring at Intermediate Metallicity Neutron Capture Elements (MINCE) is gathering the first high-quality spectra (high signal-to-noise ratio, S/N, and high resolution) for several hundreds of bright and metal-poor stars, mainly located in our Galactic halo.Methods. We compiled our selection mainly on the basis of Gaia data and determined the stellar atmospheres of our sample and the chemical abundances of each star.Results. In this paper, we present the first sample of 59 spectra of 46 stars. We measured the radial velocities and computed the Galactic orbits for all stars. We found that 8 stars belong to the thin disc, 15 to disrupted satellites, and the remaining cannot be associated to the mentioned structures, and we call them halo stars. For 33 of these stars, we provide abundances for the elements up to zinc. We also show the chemical evolution results for eleven chemical elements, based on recent models.Conclusions. Our observational strategy of using multiple telescopes and spectrographs to acquire high S/N and high-resolution spectra for intermediate-metallicity stars has proven to be very efficient, since the present sample was acquired over only about one year of observations. Finally, our target selection strategy, after an initial adjustment, proved satisfactory for our purposes.
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- Einig, Lucas, et al.
(författare)
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Deep learning denoising by dimension reduction: Application to the ORION-B line cubes
- 2023
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Ingår i: Astronomy and Astrophysics. - 0004-6361 .- 1432-0746. ; 677
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Tidskriftsartikel (refereegranskat)abstract
- Context. The availability of large bandwidth receivers for millimeter radio telescopes allows for the acquisition of position-position-frequency data cubes over a wide field of view and a broad frequency coverage. These cubes contain a lot of information on the physical, chemical, and kinematical properties of the emitting gas. However, their large size coupled with an inhomogenous signal-to-noise ratio (S/N) are major challenges for consistent analysis and interpretation. Aims. We searched for a denoising method of the low S/N regions of the studied data cubes that would allow the low S/N emission to be recovered without distorting the signals with a high S/N. Methods. We performed an in-depth data analysis of the 13CO and C17O (1-0) data cubes obtained as part of the ORION-B large program performed at the IRAM 30 m telescope. We analyzed the statistical properties of the noise and the evolution of the correlation of the signal in a given frequency channel with that of the adjacent channels. This has allowed us to propose significant improvements of typical autoassociative neural networks, often used to denoise hyperspectral Earth remote sensing data. Applying this method to the 13CO (1-0) cube, we were able to compare the denoised data with those derived with the multiple Gaussian fitting algorithm ROHSA, considered as the state-of-the-art procedure for data line cubes. Results. The nature of astronomical spectral data cubes is distinct from that of the hyperspectral data usually studied in the Earth remote sensing literature because the observed intensities become statistically independent beyond a short channel separation. This lack of redundancy in data has led us to adapt the method, notably by taking into account the sparsity of the signal along the spectral axis. The application of the proposed algorithm leads to an increase in the S/N in voxels with a weak signal, while preserving the spectral shape of the data in high S/N voxels. Conclusions. The proposed algorithm that combines a detailed analysis of the noise statistics with an innovative autoencoder architecture is a promising path to denoise radio-astronomy line data cubes. In the future, exploring whether a better use of the spatial correlations of the noise may further improve the denoising performances seems to be a promising avenue. In addition, dealing with the multiplicative noise associated with the calibration uncertainty at high S/N would also be beneficial for such large data cubes.
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