Vulvar edema diagnosis

Gilmore, Katherine Ramsey; Hussey, Jane

doi:10.1201/9781315113739-18

Cited by 12 publications

(12 citation statements)

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“…In this work, the sample of open clusters observed by the Gaia-ESO Survey (Gilmore et al 2012, Randich & Gilmore 2013) is used for a controlled test of chemical tagging. In the field of each Gaia-ESO open cluster, a large number of stars are selected for observation using the expected location of the cluster in the colour-magnitude diagram.…”

Section: Experiments Using the Gaia -Eso Open Clustersmentioning

confidence: 99%

Chemical tagging experiment with the Gaia-ESO open clusters

Smiljanić¹

2017

Proc. IAU

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Stars observed in the field of an open cluster are ideal for a controlled test of chemical tagging. Using chemical tagging, one should identify the cluster members, i.e., those stars of similar chemical composition, if their composition is indeed different from that of all the nonmember stars of the field. Moreover, the abundance-based membership can be checked against membership based on radial velocities and proper motions. Here, I report preliminary results of such an experiment using data from the Gaia-ESO Survey. Although the three membership criteria usually agree, a few interesting examples of discrepant membership classification have been found. In addition, the mean composition of each open cluster was compared to a sample of 1 600 Gaia-ESO field stars. Some cases of field stars with abundances matching those of the open clusters were identified. This experiment suggests that open clusters do not necessarily have unique abundance patterns that set them apart from all other clusters.

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Section: Experiments Using the Gaia -Eso Open Clustersmentioning

confidence: 99%

Chemical tagging experiment with the Gaia-ESO open clusters

Smiljanić¹

2017

Proc. IAU

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“…As large spectroscopic surveys, e.g., SDSS/SEGUE (Beers et al 2006), RAVE (Steinmetz et al 2006), SDSS/APOGEE (Majewski 2012), LAMOST (Deng et al 2012), Gaia-ESO (Gilmore et al 2012), and GALAH (Freeman 2012) proceed, deriving the stellar labels (or stellar parameters) is of extreme importance. In particular, such large surveys often observe stars covering a large range of spectral types.…”

Section: Introductionmentioning

confidence: 99%

Deriving the Stellar Labels of LAMOST Spectra with the Stellar LAbel Machine (SLAM)

Zhang

Liu

Deng

2020

ApJS

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The LAMOST survey has provided 9 million spectra in its Data Release 5 (DR5) at R ∼ 1800. Extracting precise stellar labels is crucial for such a large sample. In this paper, we report the implementation of the Stellar LAbel Machine (SLAM), which is a data-driven method based on Support Vector Regression (SVR), a robust non-linear regression technique. Thanks to the capability to model highly non-linear problems with SVR, SLAM generally can derive stellar labels over a wide range of spectral types. This gives it a unique capability compared to other popular data-driven methods. To illustrate this capability, we test the performance of SLAM on stars ranging from T eff ∼ 4000 to ∼ 8000 K trained on LAMOST spectra and stellar labels. At g-band signal-to-noise ratio (SNR g ) higher than 100, the random uncertainties of T eff , log g and [Fe/H] are 50 K, 0.09 dex, and 0.07 dex, respectively. We then set up another SLAM model trained by APOGEE and LAMOST common stars to demonstrate its capability of dealing with high dimensional problems. The spectra are from LAMOST DR5 and the stellar labels of the training set are from APOGEE DR15, including T eff , log g, [M/H], [α/M], [C/M], and [N/M]. The cross-validated scatters at SNR g ∼ 100 are 49 K, 0.10 dex, 0.037 dex, 0.026 dex, 0.058 dex, and 0.106 dex for these parameters, respectively. This performance is at the same level as other up-to-date data-driven models. As a byproduct, we also provide the latest catalog of ∼ 1 million LAMOST DR5 K giant stars with SLAM-predicted stellar labels in this work.

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“…Pepe et al 2004) supports the same impression. On the other hand this century has seen the first large scale stellar spectroscopic surveys, increasing the number of observed objects from 14,139 stars of the Geneva-Copenhagen survey (Nordström et al 2004), which observed one star at a time, to hundreds of thousands observed with modern multiple fibre spectrographs, as part of the RAVE (Steinmetz et al 2006;Kunder et al 2017), Gaia-ESO (Gilmore et al 2012), APOGEE (Holtzman et al 2015;Majewski et al 2016, LAMOST (Liu et al 2017, and GALAH (De Silva et al 2015;Martell et al 2017) surveys. These efforts have been focused on Galactic archaeology (Freeman & Bland-Hawthorn 2002), which aims to decipher the structure and formation of our Galaxy as one of the typical galaxies in the universe through detailed measurements of stellar kinematics and chemistry of their atmospheres.…”

Section: Introductionmentioning

confidence: 99%

The GALAH survey: accurate radial velocities and library of observed stellar template spectra

Zwitter

Kos

Chiavassa

et al. 2018

Monthly Notices of the Royal Astronomical Society

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GALAH is a large-scale magnitude-limited southern stellar spectroscopic survey. Its second data release (GALAH DR2) provides values of stellar parameters and abundances of 23 elements for 342,682 stars (Buder et al.). Here we add a description of the public release of radial velocities with a typical accuracy of 0.1 km s −1 for 336,215 of these stars, achievable due to the large wavelength coverage, high resolving power and good signal to noise ratio of the observed spectra, but also because convective motions in stellar atmosphere and gravitational redshift from the star to the observer are taken into account. In the process we derive medians of observed spectra which are nearly noiseless, as they are obtained from between 100 and 1116 observed spectra belonging to the same bin with a width of 50 K in temperature, 0.2 dex in gravity, and 0.1 dex in metallicity. Publicly released 1181 median spectra have a resolving power of 28,000 and trace the well-populated stellar types with metallicities between −0.6 and +0.3. Note that radial velocities from GALAH are an excellent match to the accuracy of velocity components along the sky plane derived by Gaia for the same stars. The level of accuracy achieved here is adequate for studies of dynamics within stellar clusters, associations and streams in the Galaxy. So it may be relevant for studies of the distribution of dark matter.

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Vulvar edema diagnosis

Cited by 12 publications

References 0 publications

Chemical tagging experiment with the Gaia-ESO open clusters

Chemical tagging experiment with the Gaia-ESO open clusters

Deriving the Stellar Labels of LAMOST Spectra with the Stellar LAbel Machine (SLAM)

The GALAH survey: accurate radial velocities and library of observed stellar template spectra

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