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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Photometric detection of internal gravity waves in upper main-sequence stars. IV. Comparable stochastic low-frequency variability in SMC, LMC, and Galactic massive stars

Authors: Bowman, Dominic;

Photometric detection of internal gravity waves in upper main-sequence stars. IV. Comparable stochastic low-frequency variability in SMC, LMC, and Galactic massive stars

Abstract

Supporting data for peer-reviewed publication entitled: 'Photometric detection of internal gravity waves in upper main-sequence stars. IV. Comparable stochastic low-frequency variability in SMC, LMC, and Galactic massive stars', published in A&A. For the purpose of open access, the authors have applied a CC BY licence to the author accepted manuscript version and made it publicly available: https://arxiv.org/abs/2410.12726 Evolutionary models and stability window calculations courtesy of Jermyn et al. 2022 (DOI: 10.3847/1538-4357/ac4e89) are publicly available via: https://github.com/adamjermyn/conv_trends TESS full-frame image data are publicly available from the Mikulski Archive for Space Telescopes (MAST) at the Space Telescope Science Institute (STScI): https://archive.stsci.edu/missions-and-data/tess TESS light curves (provided in this repository) were extracted using the publicly available tglc (Han & Brandt 2023; DOI: 10.3847/1538-3881/acaaa7) software package: https://github.com/TeHanHunter/TESS_Gaia_Light_Curve SLF variability parameters (provided in this repository; cf. Tables 1 and 2 of the paper) were obtained using GP regression with the publicly available celerite2 (Foreman-Mackey et al. 2017; DOI: 10.3847/1538-3881/aa9332) software package: https://celerite2.readthedocs.io/en/latest/ and confidence intervals were obtained using the publicly available pymc3 (Salvatier et al. 2016; https://doi.org/10.7717/peerj-cs.55) software package: https://github.com/pymc-devs/pymc This research was supported in part by the National Science Foundation (NSF) under Grant Number NSF PHY-1748958; the Research Foundation Flanders (FWO) with grant agreement numbers 1286521N, 11F7120N, and V411621N; UK Research and Innovation (UKRI) in the form of a Frontier Research grant under the UK government's ERC Horizon Europe funding guarantee (SYMPHONY; grant number: EP/Y031059/1); a Royal Society University Research Fellowship (URF; grant number: URF\R1\231631); and the KU Leuven Research Council (grant number C16/18/005: PARADISE).

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Keywords

Asteroseismology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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Average