3D Hydrodynamic Simulations of Massive Main-sequence Stars. IV. Internal Gravity Wave Matter for Stochastic Low-frequency Variability

Abstract The power spectra of light curves from satellites like the Convection, Rotation and Planetary Transits space mission and the Transiting Exoplanet Survey Satellite of massive main-sequence stars show stochastic low-frequency (SLF) variability. To investigate the origin of this phenomenon, we conducted high-resolution 3D hydrodynamic PPMstar simulations of a nonrotating 25 M ⊙ zero-age main-sequence star, modeling 95% of the stellar structure with both a core and a thin outer envelope convection zone. The outer envelope convection zone was implemented through modification of the opacity model, shifting the Fe opacity bump inward and enhancing its amplitude for computational feasibility. The luminosity power spectrum from our primary simulation (M424) exhibits qualitative and quantitative characteristics similar to observed SLF variability, with a ≈2 dex difference between high- and low-frequency power. The spectrum displays distinct features attributable to internal gravity wave (IGW) eigenmodes. To isolate the contributions of different stellar regions, we performed numerical experiments with suppressed core convection, envelope convection, and envelope-only configurations. The comparative analysis demonstrates that outer envelope convection alone produces significantly less low-frequency power than the full-star configuration. In our simulations, the outer envelope convection zone excites at its inner boundary a rich IGW eigenmode spectrum in the layer just below. In an otherwise identical simulation where the core convection is not driven by heating, the SLF spectrum is remarkably similar, and the integrated power is reduced by only 10%, suggesting that the envelope convection is the dominant contributor to the SLF power spectrum. The IGW spectral characteristics depend on the complete stellar stratification, demonstrating that interior structure could influence observable surface variability.