An Updated Formalism For Line-Driven Radiative Acceleration and Implications for Stellar Mass Loss

Abstract

Radiation contributes to the acceleration of large-scale flows in various astrophysical environments because of the strong opacity in spectral lines. Quantification of the associated force is crucial to understanding these line-driven flows, and a large number of lines (due to the full set of elements and ionization stages) must be taken into account. Here we provide new calculations of the dimensionless line strengths and associated opacity-dependent force multipliers for an updated list of approximately 4.5 million spectral lines compiled from the NIST, CHIANTI, CMFGEN, and TOPbase databases. To maintain generality of application to different environments, we assume local thermodynamic equilibrium, illumination by a Planck function, and the Sobolev approximation. We compute the line forces in a two-dimensional grid of temperatures (i.e., values between 5,200 and 70,000 K) and densities (varying over 11 orders of magnitude). Historically, the force multiplier function has been described by a power-law function of optical depth. We revisit this assumption by fitting alternative functions that include a saturation to a constant value (Gayley's $\bar{Q}$ parameter) in the optically-thin limit. This alternate form is a better fit than the power-law form, and we use it to calculate example mass-loss rates for massive main-sequence stars. Because the power-law force multiplier does not continue to arbitrarily small optical depths, we find a sharp decrease, or quenching, of line-driven winds for stars with effective temperatures less than about 15,000 K.

20 pages, 14 figures, 1 table

References in corpus (20)

• SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python
• Astropy: A Community Python Package for Astronomy
• The NumPy array: a structure for efficient numerical computation
• The chemical composition of the Sun
• The Astropy Project: Building an inclusive, open-science project and status of the v2.0 core package
• Intrinsic Colors, Temperatures, and Bolometric Corrections of Pre-Main Sequence Stars
• Mass loss from hot massive stars
• CHIANTI - an atomic database for emission lines - Paper XV: Version 9, improvements for the X-ray satellite lines
• Predictions for mass-loss rates and terminal wind velocities of massive O-type stars
• Line-driven Disk Winds in Active Galactic Nuclei: The Critical Importance of Ionization and Radiative Transfer
• Mass loss in main-sequence B stars
• A non-hydrodynamical model for acceleration of line-driven winds in Active Galactic Nuclei
• New predictions for radiation-driven, steady-state mass-loss and wind-momentum from hot, massive stars. I. Method and first results
• Line-driven ablation of circumstellar disks: I. Optically thin decretion disks of classical Oe/Be stars
• Time-dependent atomic diffusion in the atmospheres of CP stars. A big step forward: introducing numerical models including a stellar mass loss
• Self-consistent modelling of line-driven hot-star winds with Monte Carlo radiation hydrodynamics
• Self-consistent solutions for line-driven winds of hot massive stars. The m-CAK procedure
• Line-driven ablation of circumstellar discs: IV. The role of disc ablation in massive star formation and its contribution to the stellar upper mass limit
• Line-driven ablation of circumstellar discs: III. Accounting for and analyzing the effects of continuum optical depth
• Metal enrichment by radiation pressure in active galactic nucleus outflows -- theory and observations

Cited by in corpus (15)

• Radiation-Hydrodynamics with MPI-AMRVAC: Flux-Limited Diffusion
• Radiation-Driven Wind Hydrodynamics of Massive Stars: A Review
• Method and new tabulations for flux-weighted line-opacity and radiation line-force in supersonic media
• Dynamic and polarimetric VLBI imaging with a multiscalar approach
• Evolution of rotating massive stars with new hydrodynamic wind models
• New self-consistent wind parameters fitting optical spectra of O-type stars observed with HERMES spectrograph
• Swarm intelligence for full Stokes dynamic imaging reconstruction of interferometric data
• Deep learning inference with the Event Horizon Telescope III. Zingularity results from the 2017 observations and predictions for future array expansions
• Deep learning inference with the Event Horizon Telescope II. The Zingularity framework for Bayesian artificial neural networks
• Deep learning inference with the Event Horizon Telescope I. Calibration improvements and a comprehensive synthetic data library
• Prospects of using closure traces directly for imaging in Very Long Baseline Interferometry
• An on-the-fly line-driven-wind iterative mass-loss estimator (LIME) for hot, massive stars of arbitrary chemical compositions
• Accelerating the CLEAN algorithm of radio interferometry with convex optimization
• Conditions for accretion disc formation and observability of wind-accreting X-ray binaries
• Multiobjective optimization for scattering mitigation and scattering screen reconstruction in VLBI observations of the Galactic Center