The Experts below are selected from a list of 279 Experts worldwide ranked by ideXlab platform
R. E. M. Griffin - One of the best experts on this subject based on the ideXlab platform.
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Detection and measurement of total ozone from Stellar Spectra: Paper 2. Historic data from 1935?1942
Atmospheric Chemistry and Physics, 2006Co-Authors: R. E. M. GriffinAbstract:Atmospheric ozone columns are derived from historic Stellar Spectra observed between 1935 and 1942 at Mount Wilson Observatory, California. Comparisons with contemporary measurements in the Arosa database show a generally close correspondence, while a similar comparison with more sparse data from Table Mountain reveals a difference of ~15?20%, as has also been found by other researches of the latter data. The results of the analysis indicate that astronomy's archives command considerable potential for investigating the natural levels of ozone and its variability during the decades prior to anthropogenic interference.
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Detection and measurement of total ozone from Stellar Spectra: Paper 2. Historic data from 1935?1942
Atmospheric Chemistry and Physics Discussions, 2005Co-Authors: R. E. M. GriffinAbstract:Atmospheric ozone columns are derived from historic Stellar Spectra observed between 1935 and 1942 at Mount Wilson Observatory, California. Comparisons with contemporary measurements in the Arosa database show a generally close correspondence. The results of the analysis indicate that astronomy's archives command considerable potential for investigating the natural levels of ozone and its variability during the decades prior to anthropogenic interference.
A Mampaso - One of the best experts on this subject based on the ideXlab platform.
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automatic Spectral classification of Stellar Spectra with low signal to noise ratio using artificial neural networks
Astronomy and Astrophysics, 2012Co-Authors: Silvana G Navarro, R L M Corradi, A MampasoAbstract:Context. As part of a project aimed at deriving extinction-distances for thirty-five planetary nebulae, Spectra of a few thousand stars were analyzed to determine their Spectral type and luminosity class. Aims. We present here the automatic Spectral classification process used to classify Stellar Spectra. This system can be used to classify any other Stellar Spectra with similar or higher signal-to-noise ratios. Methods. Spectral classification was performed using a system of artificial neural networks that were trained with a set of line-strength indices selected among the Spectral lines most sensitive to temperature and the best luminosity tracers. The training and validation processes of the neural networks are discussed and the results of additional validation probes, designed to ensure the accuracy of the Spectral classification, are presented. Results. Our system permits the classification of Stellar Spectra of signal-to-noise ratio (S /N) significantly lower than it is generally considered to be needed. For S /N ≥ 20, a precision generally better than two Spectral subtypes is obtained. At S /N < 20, classification is still possible but has a lower precision. Its potential to identify peculiar sources, such as emission-line stars, is also recognized.
Agnès Lèbre - One of the best experts on this subject based on the ideXlab platform.
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POLLUX : a database of synthetic Stellar Spectra
Astronomy and Astrophysics, 2010Co-Authors: Ana Palacios, M. Gebran, Eric Josselin, Fabrice Martins, Bertrand Plez, M. Belmas, Agnès LèbreAbstract:Synthetic Spectra are needed to determine fundamental Stellar and wind parameters of all types of stars. They are also used for the construction of theoretical Spectral libraries helpful for Stellar population synthesis. Therefore, a database of theoretical Spectra is required to allow rapid and quantitative comparisons to spectroscopic data. We provide such a database offering an unprecedented coverage of the entire Hertzsprung-Russell diagram. We present the POLLUX database of synthetic Stellar Spectra. For objects with Teff 25 000 K). Their Spectra are computed with CMF_FLUX. Both high resolution (R>150 000) optical Spectra in the range 3 000 to 12 000 A and Spectral energy distributions extending from the UV to near--IR ranges are presented. These Spectra cover the HR diagram at solar metallicity. We propose a wide variety of synthetic Spectra for various types of stars in a format that is compliant with the Virtual Observatory standards. A user--friendly web interface allows an easy selection of Spectra and data retrieval. Upcoming developments will include an extension to a large range of metallicities and to the near--IR high resolution Spectra, as well as a better coverage of the HR diagram, with the inclusion of models for Wolf-Rayet stars and large datasets for cool stars. The POLLUX database is accessible at this http URL and through the Virtual Observatory.
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pollux a database of synthetic Stellar Spectra
Astronomy and Astrophysics, 2010Co-Authors: Ana Palacios, M. Gebran, Eric Josselin, Fabrice Martins, Bertrand Plez, M. Belmas, Agnès LèbreAbstract:Aims. Synthetic Spectra are needed to determine fundamental Stellar and wind parameters of all types of stars. They are also used for the construction of theoretical Spectral libraries helpful for Stellar population synthesis. Therefore, a database of theoretical Spectra is required to allow rapid and quantitative comparisons to spectroscopic data. We provide such a database offering an unprecedented coverage of the entire Hertzsprung-Russell diagram. Methods. We present the POLLUX database of synthetic Stellar Spectra. For objects with Teff ≤ 6000 K, MARCS atmosphere models are computed and the program TURBOSPECTRUM provides the synthetic Spectra. ATLAS12 models are computed for stars with 7000 K ≤ Teff ≤ 15 000 K. SYNSPEC gives the corresponding Spectra. Finally, the code CMFGEN provides atmosphere models for the hottest stars (Teff > 25 000 K). Their Spectra are computed with CMF_FLUX. Both high resolution (R > 150 000) optical Spectra in the range 3000 to 12 000 A and Spectral energy distributions extending from the UV to near-IR ranges are presented. These Spectra cover the HR diagram at solar metallicity. Results. We propose a wide variety of synthetic Spectra for various types of stars in a format that is compliant with the Virtual Observatory standards. A user-friendly web interface allows an easy selection of Spectra and data retrieval. Upcoming developments will include an extension to a large range of metallicities and to the near-IR high resolution Spectra, as well as a better coverage of the HR diagram, with the inclusion of models for Wolf-Rayet stars and large datasets for cool stars. The POLLUX database is accessible at http://pollux.graal.univ-montp2.fr/ and through the Virtual Observatory.
Stefanie Wachter - One of the best experts on this subject based on the ideXlab platform.
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THE SPITZER ATLAS OF Stellar Spectra (SASS)
The Astrophysical Journal Supplement Series, 2010Co-Authors: David R. Ardila, Inseok Song, Donald Hoard, Jeonghee Rho, Wojciech Makowiecki, Schuyler D. Van Dyk, Sergio Fajardo-acosta, John R. Stauffer, Stefanie WachterAbstract:We present the Spitzer Atlas of Stellar Spectra, which includes 159 Stellar Spectra (5-32 μm; R ~ 100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative Spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general Stellar Spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, such as blue stragglers and certain pulsating variables. All of the Spectra have been uniformly reduced, and all are available online. For dwarfs and giants, the Spectra of early-type objects are relatively featureless, characterized by the presence of hydrogen lines in A Spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest Spectral types. Most supergiant Spectra in the Atlas present evidence of circumStellar gas and/or dust. The sample includes five M supergiant Spectra, which show strong dust excesses and in some cases polycyclic aromatic hydrocarbon features. Sequences of WR stars present the well-known pattern of lines of He I and He II, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low Spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse Spectra, dominated by circumStellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of Spectral type for most luminosity classes.
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The Spitzer Atlas of Stellar Spectra
Proceedings of the International Astronomical Union, 2009Co-Authors: David R. Ardila, Inseok Song, Donald Hoard, Jeonghee Rho, Wojciech Makowiecki, Schuyler D. Van Dyk, John Stauffer, Stefanie Wachter, Sergio Fajardo-acostaAbstract:We present the Spitzer Atlas of Stellar Spectra (SASS), which includes 159 Stellar Spectra (5 to 32 mic; R~100) taken with the Infrared Spectrograph on the Spitzer Space Telescope. This Atlas gathers representative Spectra of a broad section of the Hertzsprung-Russell diagram, intended to serve as a general Stellar Spectral reference in the mid-infrared. It includes stars from all luminosity classes, as well as Wolf-Rayet (WR) objects. Furthermore, it includes some objects of intrinsic interest, like blue stragglers and certain pulsating variables. All the Spectra have been uniformly reduced, and all are available online. For dwarfs and giants, the Spectra of early-type objects are relatively featureless, dominated by Hydrogen lines around A Spectral types. Besides these, the most noticeable photospheric features correspond to water vapor and silicon monoxide in late-type objects and methane and ammonia features at the latest Spectral types. Most supergiant Spectra in the Atlas present evidence of circumStellar gas. The sample includes five M supergiant Spectra, which show strong dust excesses and in some cases PAH features. Sequences of WR stars present the well-known pattern of lines of HeI and HeII, as well as forbidden lines of ionized metals. The characteristic flat-top shape of the [Ne III] line is evident even at these low Spectral resolutions. Several Luminous Blue Variables and other transition stars are present in the Atlas and show very diverse Spectra, dominated by circumStellar gas and dust features. We show that the [8]-[24] Spitzer colors (IRAC and MIPS) are poor predictors of Spectral type for most luminosity classes.
Zachary Slepian - One of the best experts on this subject based on the ideXlab platform.
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Automatic Kalman-filter-based wavelet shrinkage denoising of 1D Stellar Spectra
Monthly Notices of the Royal Astronomical Society, 2019Co-Authors: Sankalp Gilda, Zachary SlepianAbstract:Author(s): Gilda, S; Slepian, Z | Abstract: © 2019 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society We propose a non-parametric method to denoise 1D Stellar Spectra based on wavelet shrinkage followed by adaptive Kalman thresholding. Wavelet shrinkage denoising involves applying the discrete wavelet transform (DWT) to the input signal, 'shrinking' certain frequency components in the transform domain, and then applying inverse DWT to the reduced components. The performance of this procedure is influenced by the choice of base wavelet, the number of decomposition levels, and the thresholding function. Typically, these parameters are chosen by 'trial and error', which can be strongly dependent on the properties of the data being denoised. We here introduce an adaptive Kalman-filter-based thresholding method that eliminates the need for choosing the number of decomposition levels. We use the 'Haar' wavelet basis, which we found to provide excellent filtering for 1D Stellar Spectra, at a low computational cost. We introduce various levels of Poisson noise into synthetic PHOENIX Spectra, and test the performance of several common denoising methods against our own. It proves superior in terms of noise suppression and peak shape preservation. We expect it may also be of use in automatically and accurately filtering low signal-to-noise galaxy and quasar Spectra obtained from surveys such as SDSS, Gaia, LSST, PESSTO, VANDELS, LEGA-C, and DESI.
