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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

Lookup NU author(s): Dr Dominic BowmanORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

Context. Massive main-sequence stars have convective cores and radiative envelopes, but can also have sub-surface convection zones caused by partial ionisation zones. However, the convective properties of such regions strongly depend on opacity and therefore a star’s metallicity. Non-rotating 1D evolution models of main-sequence stars between 7 ≤ M ≤ 40 M and the metallicity of the Small Magellanic Cloud (SMC) galaxy suggest tenuous (if any) sub-surface convection zones when using the Rayleigh number as a criterion for convection owing to their substantially lower metallicity compared to Galactic massive stars.Aims. We test whether massive stars of different metallicities both inside and outside of asteroseismically calibrated stability windows for sub-surface convection exhibit different properties in stochastic low-frequency (SLF) variability. Thus, we aim to constrain the metallicity dependence of the physical mechanism responsible for SLF variability commonly found in light curves of massive stars.Methods. We extracted customised light curves from the ongoing NASA Transiting Exoplanet Survey Satellite (TESS) mission for a sample of massive stars using an effective point spread function (ePSF) method, and compared their morphologies in terms of characteristic frequency, νchar, and amplitude using a Gaussian process (GP) regression methodology.Results. We demonstrate that the properties of SLF variability observed in time series photometry of massive stars are generally consistent across the metallicity range from the Milky Way down to the SMC galaxy, for stars both inside and outside of the sub-surface stability windows based on the Rayleigh number as a criterion for convection.Conclusions. We conclude that non-rotating 1D stellar structure models of sub-surface convection cannot alone be used to explain the mechanism giving rise to SLF variability in light curves of massive stars. Additionally, the similar properties of SLF variability across a wide range of metallicity values, which follow the same trends in mass and age in the Hertzsprung–Russell (HR) diagram at both high and low metallicity, support a transition in the dominant mechanism causing SLF variability from younger to more evolved stars. Specifically, core-excited internal gravity waves (IGWs) are favoured for younger stars lacking sub-surface convection zones, especially at low metallicity, and sub-surface convection zones are favoured for more evolved massive stars.


Publication metadata

Author(s): Bowman DM, Van Daele P, Michielsen M, Van Reeth T

Publication type: Article

Publication status: Published

Journal: Astronomy & Astrophysics

Year: 2024

Volume: 692

Pages: 10

Print publication date: 02/12/2024

Online publication date: 02/12/2024

Acceptance date: 21/10/2024

Date deposited: 11/02/2025

ISSN (print): 1432-0746

ISSN (electronic): 0004-6361

Publisher: EDP Sciences

URL: https://doi.org/10.1051/0004-6361/202451419

DOI: 10.1051/0004-6361/202451419

Data Access Statement: This research has made use of the following software packages: tglc (Han & Brandt 2023) for light curve extraction (https://github.com/TeHanHunter/TESS_Gaia_ Light_Curve), celerite2 (Foreman-Mackey et al. 2017) for GP regression fit- ting (https://celerite2.readthedocs.io/en/latest/) and pymc3 (Sal- vatier et al. 2016) for confidence interval estimation (https://github.com/ pymc-devs/pymc), as well as matplotlib (Hunter 2007), seaborn (Waskom 2021), and numpy (Oliphant 2006; van der Walt et al. 2011; Harris et al. 2020).Data products that support the results in this paper are publicly available via the Zenodo repository: https://zenodo.org/records/14018449.


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Funding

Funder referenceFunder name
EP/Y031059/1
KU Leuven Research Council (C16/18/005: PARADISE)
National Science Foundation (NSF) under Grant Number NSF PHY-1748958
Research Foundation Flanders (FWO)
Royal Society University Research Fellowship (URF; grant number: URF\R1\231631)
UK Research and Innovation (UKRI)

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