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arXiv · 2610.33163

Wolf-Rayet Stars in M33: The Impact of Stellar Crowding on Spectral Classification and Mass-Loss Diagnostics

Abstract

The metallicity dependence of Wolf-Rayet (WR) mass-loss rates is a critical input for massive star evolutionary models, chemical yield predictions, and ionizing radiation budgets of young stellar populations. The Triangulum Galaxy (M33), with 213 spectroscopically confirmed WR stars spanning a $\sim$0.5 dex radial metallicity gradient, is the premier laboratory for this calibration. However, the ground-based fiber spectra on which the current census rests blend each target with neighboring OB stars, diluting diagnostic emission-line equivalent widths and biasing spectral classifications, inferred mass-loss rates, and surface hydrogen abundances. Using $0\farcs1$-resolution HST/PHATTER survey imaging, we quantify this contamination for 123 WR stars within the survey footprint, finding that $\sim$27% suffer moderate-to-severe dilution from unresolved neighbors with WR continuum flux contributions $F_{\rm WR} < 0.85$. We provide crowding classifications, $F_{\rm WR}$ fractions, and six-band photometry in the F275W, F336W, F475W, F814W, F110W, and F160W bands for each identified counterpart. We also present Keck/DEIMOS slit spectra of five WR stars, which are substantially less contaminated than the discovery MMT/Hectospec fiber spectra. A direct equivalent-width comparison of these targets confirms the predicted dilution. The slit spectra yield blue-edge velocities of He I absorption ($v_{\rm blue} \approx 700$--$1500$ km s$^{-1}$), comparable to WR stars at similar metallicity in the LMC. The $F_{\rm WR}$ correction factors, together with the slit-spectrum benchmarks, provide the inputs needed to place M33 on the $\dot{M}$--$Z$ relation as a calibration anchor between the LMC and the Galaxy.

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Rohit Raj, Puragra Guhathakurta, Robert E. Williams, Benjamin F. Williams, Julianne J. Dalcanton, Meredith J. Durbin. 2026-10-23. Wolf-Rayet Stars in M33: The Impact of Stellar Crowding on Spectral Classification and Mass-Loss Diagnostics. https://arxiv.org/abs/2610.33163

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