Zeta-Payne: A Fully Automated Spectrum Analysis Algorithm for the Milky Way Mapper Program of the SDSS-V Survey

Straumit, Ilya; Tkachenko, A.; Gebruers, Sarah; Audenaert, J.; Xiang, Maosheng; Zari, E.; Aerts, C.; Johnson, Jennifer A.; Kollmeier, Juna A.; Rix, Hans─Walter; Beaton, Rachael L.; Saders, Jennifer L. van; Teske, Johanna; Roman-Lopes, Alexandre; Ting, Yuan-Sen; Román-Zúñiga, C.

doi:10.3847/1538-3881/ac5f49

Cited by 14 publications

(15 citation statements)

References 62 publications

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“…We used the zeta-Payne (Straumit et al 2022) spectrum analysis algorithm to analyse the averaged spectra of the 98 Galactic single stars or SB1 systems. The zeta-Payne is a machine learning framework that trains a neural network on a grid of synthetic spectra to obtain a spectrum interpolator.…”

Section: Spectrum Analysis With the Zeta-paynementioning

confidence: 99%

“…In this paper, we analyse the spectra of 166 B-type stars that exhibit photometric variability in their TESS light curves, with the purpose of future combined asteroseismic and spectroscopic modelling. For the sake of efficiency and consistency of the obtained results across the entire stellar sample, we employ the zeta-Payne (Straumit et al 2022) machine learning-based spectrum analysis algorithm. The method is a generalisation of the originally proposed The Payne algorithm (Ting et al 2019) towards the inclusion of a model with an a priori unknown residual instrumental response function into the parameter vector.…”

Section: Introductionmentioning

confidence: 99%

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Discovery of an optical cocoon tail behind the runaway HD 185806

Spetsieri

Boumis

Chiotellis

et al. 2022

Monthly Notices of the Royal Astronomical Society

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Studies on the circumstellar structures around evolved stars provide vital information on the evolution of the parent star and the properties of the local interstellar medium. In this work, we present the discovery and characterization of an optical cocoon tail behind the star HD 185806. The cocoon apex emission is puzzling, as it is detected in the infrared but shows no signal in the optical wavelength. The Hα and [O iii] fluxes of the nebular structure vary from 2.7 to 8.5×10−12 erg s−1 cm−2 and from 0.9 to 7.0×10−13 erg s−1 cm−2, respectively. Through high-resolution spectroscopy, we derive the spectral type of the star, construct the position-velocity diagrams of the cocoon tail for the Hα, [O iii] and [N ii] emission lines, and determine its velocity in the range of −100 to 40 km s−1. Furthermore, we use SED fitting and MESA evolutionary models adopting a distance of 900 pc, and classify HD 185806 as a 1.3 M⊙ star, in the transition phase between the RGB and early AGB stages. Finally, we study the morpho-kinematic structure of the cocoon tail using the astronomical software SHAPE. An ellipsoidal structure, with an inclination of ∼19○ with respect to the plane of sky is found to better reproduce the observed cocoon tail of HD 185806.

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Section: Spectrum Analysis With the Zeta-paynementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Discovery of an optical cocoon tail behind the runaway HD 185806

Spetsieri

Boumis

Chiotellis

et al. 2022

Monthly Notices of the Royal Astronomical Society

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show abstract

“…It is therefore easier to compute. Straumit et al (2022) pointed out that for high-resolution spectra, the neural network performs worse in regions of the parameter space with low values of v sin i and temperatures in the late-A to F-type regime. This is due to the many narrow spectral lines that have to be resolved by the neural network in this regime.…”

Section: Spectrum Analysis With Zeta-paynementioning

confidence: 99%

“…We used the constant resolution value of FEROS because the LSF computed from the ThAr frames that were taken during the observing run changes from night to night. The neural network was trained in the same way as described in Straumit et al (2022); more information can be found in that paper. For every star in the sample, surface parameters and the RV were derived by fitting model spectra to the observed spectrum using the neural network interpolator, performing a Doppler shift, and minimising the χ 2 merit function.…”

Section: Parametermentioning

confidence: 99%

“…In order to minimise subjectivity, we followed Straumit et al (2022) and normalised the spectra automatically during the fitting procedure in zeta-Payne, such that the optimal response function was determined simultaneously with the best-fitting surface parameters. We assumed that the response function could be represented by a Chebyshev polynomial for which we optimised its coefficients (as described in Straumit et al 2022). The number of coefficients is a free parameter that had to be fixed before starting the fitting procedure.…”

Section: Parametermentioning

confidence: 99%

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Analysis of high-resolution FEROS spectroscopy for a sample of variable B-type stars assembled from TESS photometry,

Gebruers

Tkachenko

Bowman

et al. 2022

A&A

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Context. Spectroscopic data are necessary to break degeneracies in the asteroseismic modelling of the interior structure in high-and intermediate-mass stars. With the TESS mission, the number of bright intermediate-mass B-type stars with long photometric light curves that are suitable for detailed asteroseismic studies has increased substantially compared to the pre-TESS era. Aims. We derive precise photospheric stellar parameters for a sample of 166 B-type stars with TESS light curves through a homogeneous spectroscopic analysis. The variability types of these sample stars are also classified based on all currently available TESS sectors, and they are ultimately prioritised according to their astrophysical potential. Methods. We obtained high-resolution spectra for all 166 targets with the FEROS spectrograph in the context of a large program. The spectra were reduced with the CERES pipeline, which we adapted to improve the quality of the reduced spectra. These spectra were subsequently analysed with zeta-Payne, a machine-learning-based spectrum analysis algorithm, to infer precise stellar labels for all stars in the sample. Furthermore, the least-squares deconvolution (LSD) method was employed to investigate spectral line profile variability (LPV) and isolate binary systems from presumably single stars. Results. The LSD profile analysis identified 26 spectroscopic double-lined binaries; the remainder of the sample are 42 supergiants in the Large Magellanic Cloud galaxy and 98 Galactic stars, both with and without apparent LPV. For the Galactic single stars and singlelined spectroscopic binaries, we determine their five main surface parameters: effective temperature (T eff ), surface gravity (log g), global metallicity ([M/H]), projected rotational velocity (v sin i), and microturbulent velocity (ξ) with average formal precisions of 70 K, 0.03 dex, 0.07 dex, 8 km s −1 , and 0.7 km s −1 , respectively. The average internal uncertainties we find for FEROS spectra with our spectrum analysis method are 430 K (T eff ), 0.12 dex (log g), 0.13 dex ([M/H]), 12 km s −1 (v sin i), and 2 km s −1 (ξ). Conclusions. We find spectroscopic evidence that 8 of the 98 galactic single or SB1 variables are fast-rotating gravity-mode pulsators occurring in between the slowly pulsating B (SPB) stars and δ Scuti instability strips. The g-mode frequencies of these pulsators are shifted to relatively high frequency values due to their rotation, and their apparently too low T eff relative to the SPB instability region can in most cases be explained by the gravity darkening effect. We also discover 13 new HgMn stars in the Galactic sample of which only one is found in a spectroscopic binary, resulting in a biased and therefore unreliable low binary rate of only 8%.

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The ESO UVES/FEROS Large Programs of TESS OB pulsators

Serebriakova¹,

Tkachenko²,

Gebruers³

et al. 2023

A&A

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Context. Modern stellar structure and evolution theory suffers from a lack of observational calibration for the interior physics of intermediate- and high-mass stars. This leads to discrepancies between theoretical predictions and observed phenomena that are mostly related to angular momentum and element transport. Analyses of large samples of massive stars connecting state-of-the-art spectroscopy to asteroseismology may provide clues as to how to improve our understanding of their interior structure. Aims. We aim to deliver a sample of O- and B-type stars at metallicity regimes of the Milky Way and the Large Magellanic Cloud (LMC) galaxies with accurate atmospheric parameters from high-resolution spectroscopy, along with a detailed investigation of line-profile broadening, both for the benefit of future asteroseismic studies. Methods. After describing the general aims of our two Large Programs, we develop a dedicated methodology to fit spectral lines and deduce accurate global stellar parameters from high-resolution multi-epoch UVES and FEROS spectroscopy. We use the best available atmosphere models for three regimes covered by our global sample, given its breadth in terms of mass, effective temperature, and evolutionary stage. Results. Aside from accurate atmospheric parameters and locations in the Hertzsprung-Russell diagram, we deliver detailed analyses of macroturbulent line broadening, including estimations of the radial and tangential components. We find that these two components are difficult to disentangle from spectra with signal-to-noise ratios of below 250. Conclusions. Future asteroseismic modelling of the deep interior physics of the most promising stars in our sample will provide much needed information regarding OB stars, including those of low metallicity in the LMC.

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Zeta-Payne: A Fully Automated Spectrum Analysis Algorithm for the Milky Way Mapper Program of the SDSS-V Survey

Cited by 14 publications

References 62 publications

Discovery of an optical cocoon tail behind the runaway HD 185806

Discovery of an optical cocoon tail behind the runaway HD 185806

Analysis of high-resolution FEROS spectroscopy for a sample of variable B-type stars assembled from TESS photometry,

The ESO UVES/FEROS Large Programs of TESS OB pulsators

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