A new mass estimate method with hydrodynamical atmospheres for very massive WNh stars

Very massive stars with masses over 100 M⊙ are key objects in the Universe for our understanding of chemical and energetic feedback in the Universe, but their evolution and fate are almost entirely determined by their wind mass loss. Here, we aim to determine the mass of the most massive star known in the Local Group R136a1. To this end, we computed the first hydrodynamically consistent non-local thermodynamical equilibrium atmosphere models for R136a1 (WN5h), as well as the binary system R144 (WN5/6h+WN6/7h) in the Tarantula Nebula. Using the Potsdam Wolf–Rayet code, we were able to simultaneously empirically derive and theoretically predict their mass-loss rates and wind velocities. By fitting synthetic spectra derived from these models to multi-wavelength observations, we constrained the stellar and wind properties of R144 and R136a1. We first determined the clumping stratification required by our hydro-models to fit the spectra of R144, using the available dynamical mass estimates for the two components. We then utilised this clumping stratification in hydrodynamic models of R136a1 and estimated a mass of MHydro of 233 M⊙. Remarkably, the estimated mass is close to and fully consistent with chemical homogeneous mass relations. This present-day mass of 233 M⊙ provides a lower limit to the initial stellar mass, which could be far higher due to previous wind mass loss.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-04-25
DOI
https://doi.org/10.1051/0004-6361/202453447/pdf
Primary Topic
Stellar, planetary, and galactic studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A new mass estimate method with hydrodynamical atmospheres for very massive WNh stars

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

A new mass estimate method with hydrodynamical atmospheres for very massive WNh stars

article en

Abstract

Very massive stars with masses over 100 M⊙ are key objects in the Universe for our understanding of chemical and energetic feedback in the Universe, but their evolution and fate are almost entirely determined by their wind mass loss. Here, we aim to determine the mass of the most massive star known in the Local Group R136a1. To this end, we computed the first hydrodynamically consistent non-local thermodynamical equilibrium atmosphere models for R136a1 (WN5h), as well as the binary system R144 (WN5/6h+WN6/7h) in the Tarantula Nebula. Using the Potsdam Wolf–Rayet code, we were able to simultaneously empirically derive and theoretically predict their mass-loss rates and wind velocities. By fitting synthetic spectra derived from these models to multi-wavelength observations, we constrained the stellar and wind properties of R144 and R136a1. We first determined the clumping stratification required by our hydro-models to fit the spectra of R144, using the available dynamical mass estimates for the two components. We then utilised this clumping stratification in hydrodynamic models of R136a1 and estimated a mass of MHydro of 233 M⊙. Remarkably, the estimated mass is close to and fully consistent with chemical homogeneous mass relations. This present-day mass of 233 M⊙ provides a lower limit to the initial stellar mass, which could be far higher due to previous wind mass loss.

Springer Link (Chiba Institute of Technology)
Affordable and clean energy
Openalex Percentile: Top 71%
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.