Photometric detection of internal gravity waves in upper main-sequence stars

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 Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2024-12-02
DOI
https://doi.org/10.1051/0004-6361/202451419/pdf
Primary Topic
Stellar, planetary, and galactic studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Photometric detection of internal gravity waves in upper main-sequence stars

Springer Link (Chiba Institute of Technology)
Stellar, planetary, and galactic studies
article

Photometric detection of internal gravity waves in upper main-sequence stars

article en

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.

Springer Link (Chiba Institute of Technology)
National Science Foundation, National Aeronautics and Space Administration, Space Telescope Science Institute, Government of the United Kingdom, UK Research and Innovation, Fonds Wetenschappelijk Onderzoek, KU Leuven, Vlaamse regering, HORIZON EUROPE Framework Programme, Kavli Institute for Theoretical Physics, University of California, Santa Barbara, Astrophysics Division
Openalex Percentile: Top 73%
Stellar, planetary, and galactic studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.