# Probing Thin Winds in Massive OB Stars of the SMC with JWST/NIRSPEC Br α Spectroscopy

Miriam Garcia, Alexander W Fullerton, Francisco Najarro, Joachim Puls, Daniel J Lennon, Jean-Claude Bouret, Christopher J Evans, Margaret Hanson, Artemio Herrero, D. John Hillier, et al.

► To cite this version:

Miriam Garcia, Alexander W Fullerton, Francisco Najarro, Joachim Puls, Daniel J Lennon, et al. Probing Thin Winds in Massive OB Stars of the SMC with JWST/NIRSPEC Br α Spectroscopy. The Astrophysical Journal Letters, 2025, 990 (1), pp.L23. 10.3847/2041-8213/adfa0f. hal-05393542

HAL Id: hal-05393542

https://hal.science/hal-05393542v1

Submitted on 2 Dec 2025

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
OPEN ACCESS

<figure><img src="image_2.png" /></figure>

CrossMark

# Probing Thin Winds in Massive OB Stars of the SMC with JWST/NIRSPEC Brα Spectroscopy

Miriam Garcia¹ ID, Alexander W. Fullerton² ID, Francisco Najarro¹ ID, Joachim Puls³ ID, Daniel J. Lennon⁴,⁵ ID,
Jean-Claude Bouret⁶ ID, Christopher J. Evans⁷ ID, Margaret Hanson⁸ ID, Artemio Herrero⁴,⁵ ID, D. John Hillier⁹ ID,
Alexandre Legault¹,¹⁰ ID, María del Mar Rubio-Díez¹ ID, Sergio Simón-Díaz⁴,⁵ ID, Jon O. Sundqvist¹¹ ID, and Frank Tramper¹ ID

¹Centro de Astrobiología, CSIC-INTA, Crtra. de Torrejón a Ajalvir km 4, 28850 Torrejón de Ardoz (Madrid), Spain; mgg@cab.inta-csic.es

²Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA

³LMU München, Universitätsternwarte, Scheinerstrasse 1, 81679 München, Germany

⁴Instituto de Astrofísica de Canarias, Avenida Vía Láctea s.n., 38205 La Laguna, Tenerife, Spain

⁵Dpto. Astrofísica, Universidad de La Laguna, 38205 La Laguna, Tenerife, Spain

⁶Aix Marseille Univ, CNRS, CNES, LAM, Marseille, France

⁷European Space Agency (ESA), ESA Office, Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA

⁸Department of Physics, University of Cincinnati, P.O. Box 210011, Cincinnati, OH 45221-0011, USA

⁹Department of Physics and Astronomy & Pittsburgh Particle Physics, Astrophysics and Cosmology Center (PITT PACC), University of Pittsburgh, 3941 O’Hara Street, Pittsburgh, PA 15260, USA

¹⁰Departamento de Física Teórica, Universidad Autónoma de Madrid (UAM), Campus de Cantoblanco, 28049, Madrid, Spain

¹¹KU Leuven, Instituut voor Sterrenkunde, Celestijnenlaan 200D, 3001 Leuven, Belgium

Received 2025 July 1; revised 2025 August 8; accepted 2025 August 8; published 2025 August 29

## Abstract

Mass loss is a key physical process in the evolution of massive stars, the impact of which propagates into galactic evolution, population synthesis models, the interpretation of high-redshift galaxies, and explosive events such as supernovae. However, there are currently substantial uncertainties in the low-metallicity, low-luminosity thin wind regime where classical diagnostics (Hα and ultraviolet, UV, P Cygni profiles) yield wind momenta that are 1 to 2 orders of magnitude below prescriptions implemented by default in most evolutionary models. Here, we present spectra of the mass-loss diagnostic line Brα in 15 OB-type stars in the Small Magellanic Cloud obtained using the Near Infrared Spectrograph on the James Webb Space Telescope. The line profile morphology, recovered by virtue of the outstanding signal-to-noise ratio of the data and the avoidance of regions with nebular emission, is consistent with predictions based on previous mass-loss rate estimates from optical and UV spectroscopy. Moreover, an initial spectroscopic analysis of sources covering the thin wind regime confirms the low mass-loss rates, indicates a change of slope in the wind-momentum–luminosity relation in this regime with respect to high-luminosity objects, and strengthens the abovementioned discrepancies with commonly used wind-momentum prescriptions.

*Unified Astronomy Thesaurus concepts: Stellar physics (1621); Stellar winds (1636); OB stars (1141); Small Magellanic Cloud (1468); Infrared spectroscopy (2285); James Webb Space Telescope (2291)*

## 1. Introduction

Mass loss is a key agent in the life cycle of massive stars (P. S. Conti 1975; A. Maeder 1981) that is widely implemented in stellar evolution codes with simplifying recipes (N. Langer et al. 1988; J. Petrovic et al. 2005; P. Eggenberger et al. 2008; B. Paxton et al. 2013). However, uncertainties in the dependence of mass-loss rate (M̄) on metallicity (Z), luminosity (log L*/*L*<sub>☉</sub>), and effective temperature (T<sub>eff</sub>), even for stars on the main sequence, have significant implications for their subsequent evolutionary pathways and end products (e.g., J. Josiek et al. 2024). These M̄ recipes rely on theoretical predictions but are anchored to observations in the Milky Way and the Large and Small Magellanic Cloud (SMC). While results for mass-loss rates and their Z-dependence for high-luminosity O-type stars (e.g., J. Puls et al. 1996; M. R. Mokiem et al. 2007) were found to be in reasonable agreement with theoretical predictions (R. P. Kudritzki et al. 1987), significant discrepancies seemed to exist for lower-luminosity O-type stars within the Milky Way (F. Martins et al. 2004; W. L. F. Marcolino et al. 2009) and SMC

(J. C. Bouret et al. 2003; V. Ramachandran et al. 2019; M. J. Rickard et al. 2022), with estimates of wind momenta up to 2 orders of magnitude below commonly employed predictions (see below). This discrepancy in the thin wind regime represents a significant observational challenge that, if confirmed by other methods, would have a far-reaching impact on astrophysics in general, particularly in the context of feedback from a population of massive stars, given that later-type, less-luminous O-stars are significantly more numerous than higher-mass, earlier-type stars.

The SMC, due to its low metallicity (Z ~ 0.2 *Z*<sub>☉</sub>), is of special interest as the thin wind regime becomes apparent at earlier spectral types than in the Milky Way, being present even for O7 stars on the main sequence with log(L*/L*) ≲ 5.4 (e.g., W. L. F. Marcolino et al. 2022; M. J. Rickard et al. 2022; F. Backs et al. 2024). This is illustrated in Figure 1 where we plot the wind-momentum–luminosity relation (WLR) for the SMC, adopting literature results that are based on optical (Hα), or combined optical–ultraviolet (UV) analyses. At log L*/L* < 5.2–5.4, only upper M̄ limits can be provided in many cases, most of which are well below the widely used J. S. Vink et al. (2001) relation. One implication of this discrepancy is that the mass-loss rates of low-luminosity, low-Z massive stars could be overestimated by as much as factors of 50–100 when using the prescriptions by J. S. Vink et al. (2001),

<figure><img src="image_3.png" /></figure>

Original content from this work may be used under the terms of the [Creative Commons Attribution 4.0 licence](https://creativecommons.org/licenses/by/4.0/). Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
<figure><img src="image_4.png" /><figcaption>**Figure 1.** Wind-momentum–luminosity relation at SMC metallicity expressed in cgs units. Gray points mark empirical results, with $\dot{M}$ obtained from $H\alpha$ or combined optical–UV analyses (P. Massey et al. 2004, 2005, 2009; S. R. Heap et al. 2006; M. R. Mokiem et al. 2006, 2007; J. C. Bouret et al. 2013). When these works considered clumping, we computed the equivalent smooth-wind mass-loss rate ($\dot{M}_{\text{smooth}} = \dot{M}/\sqrt{f_{\text{vol}}}$, with $f_{\text{vol}}$ being the clumping volume filling factor; see, e.g., J. Puls et al. 2008, Sect. 6.3) prior to calculating the wind-momentum rate. $H\alpha$ only provides upper limits for mass-loss rates at $\log L_*/L_\odot \lesssim 5.2–5.4$ (downward triangles). We note the change of slope between the high-luminosity objects and the less-luminous ones at this $L_*$. The gray lines represent the theoretical WLR derived by J. S. Vink et al. (2001; solid) and scaled to the SMC metallicity and more modern relations at SMC metallicity by J. Krtička & J. Kubát (2018; dashed-dotted) and R. Björklund et al. (2021; dashed). The shaded region below the yellow line marks the parameter space where $Br\alpha$ is predicted to exhibit narrow emission. Blue and green symbols denote project targets expected to show broad and narrow $Br\alpha$ emission, respectively, while the red sources lie in the expected thin wind regime (see Table 1 for the stellar parameters used in this plot). For some project sources, only upper limits of $\dot{M}$ could be constrained by previous works (red downward arrows). Objects with underlined designations have been analyzed in Section 5.</figcaption></figure>

which are implemented as default in most models of massive star evolution. More modern prescriptions by J. Krtička & J. Kubát (2018) and R. Björklund et al. (2021) partly reconcile the $\dot{M}$ differences, although they do not reproduce the change of slope of the observational WLR at the luminosities when thin winds set in.

Nonetheless, major caveats also affect optical/UV analyses that result in a large scatter of the observed $\dot{M}-L_{\text{bol}}$ relation at the low-luminosity end (see e.g., Figure 13 of R. Björklund et al. 2021). On the one hand, $H\alpha$ provides only upper limits to $\dot{M}$ due to its profile being almost purely photospheric in nature, while UV resonance lines exhibit very weak, or entirely absent, P-Cygni features (N. R. Walborn et al. 2000; C. J. Evans et al. 2004) that also depend strongly on both X-ray emission from wind-embedded shocks and wind inhomogeneities (D. J. Hillier et al. 2003; A. W. Fullerton et al. 2006; L. M. Oskinova et al. 2007; J. Puls et al. 2008 and references therein; R. K. Prinja & D. L. Massa 2010; J. O. Sundqvist et al. 2014).

The Brackett $\alpha$ ($Br\alpha$) line at 4.0512 µm, corresponding to the $n=5–4$ transition of atomic hydrogen, offers an alternative and independent method of deriving mass-loss rates. For dense winds, $Br\alpha$ behaves similarly to $H\alpha$, i.e., it displays broad emission that increases in strength with increasing $\dot{M}$. However, for the weaker winds of low-luminosity stars, this inherently strong transition exhibits extreme non-LTE effects, particularly in the transition zone between the photosphere and wind. This results in a strong depopulation of level $n=4$ compared to level $n=5$ and thus an extremely large source function (F. Najarro et al. 2011, Appendix B). As a consequence, $Br\alpha$ exhibits a narrow emission spike near the

line center, while the line wings are still in absorption. F. Najarro et al. (2011) showed that the line intensity of the central spike of narrow $Br\alpha$ profiles increases as the mass-loss rate decreases, thus providing reliable diagnostics for extremely low $\dot{M}$ beyond the sensitivity range of $H\alpha$ (see Figure 11 of F. Najarro et al. 2011), and that it is relatively insensitive to wind inhomogeneities. While this is an extremely powerful diagnostic, the thermal background of the Earth’s atmosphere prevents its application from ground-based telescopes for all but a handful of targets in the Milky Way (K. A. Murdoch et al. 1994; F. Najarro et al. 2011).

The superb sensitivity of the James Webb Space Telescope (JWST) in the thermal infrared uniquely enables observation of $Br\alpha$ in massive stars in the SMC (see also A. Mang Román et al. 2025). In this Letter we present, for the first time, very high signal-to-noise ratio (S/N ~ 170–200) observations of 15 OB stars in the SMC taken with the JWST Near Infrared Spectrograph (NIRSpec). We discuss whether the $Br\alpha$ morphology agrees with theoretical predictions from CMFGEN (D. J. Hillier & D. L. Miller 1998) and FASTWIND (J. Puls et al. 2005; J. G. Rivero González et al. 2011) non-LTE, unified atmosphere-plus-wind models, and its consistency with the UV and optical diagnostics. Building upon the thorough tests on the $Br\alpha$ behavior we performed in F. Najarro et al. (2011), we carry out a preliminary analysis of a representative subsample of five sources. The Letter is structured as follows: the sample, observing configuration, and data reduction are described in Sections 2 and 3; the $Br\alpha$ atlas and analysis are presented in Sections 4 and 5. Finally, we provide our conclusions and future work in Section 6.
<table><caption>**Table 1**
Sample Stars Sorted by Spectral Type and Luminosity Class</caption><thead><tr><th>Target</th><th>Spectral Type</th><th>K<sub>s</sub> (mag.)</th><th>[4.5] (mag.)</th><th>vsini (km s<sup>-1</sup>)</th><th>T<sub>eff</sub> (K)</th><th>log g<sub>true</sub> (dex)</th><th>log L<sub>*</sub>/L<sub>☉</sub> (dex)</th><th>M&#x0307; (M<sub>☉</sub> yr<sup>-1</sup>)</th><th>v<sub>∞</sub> (km s<sup>-1</sup>)</th><th>Regime</th><th>References</th></tr></thead><tbody><tr><td>AzV 177</td><td>O4V (f)</td><td>15.32</td><td>15.24</td><td>220</td><td>44500</td><td>4.03</td><td>5.43</td><td>1.4E-07 5.0E-08<br>2.0E-07</td><td>2400</td><td>B</td><td>(4)</td></tr><tr><td>AzV 388</td><td>O4 V</td><td>14.80</td><td>14.80</td><td>150</td><td>43100</td><td>4.01</td><td>5.54</td><td>1.0E-07</td><td>2100</td><td>N</td><td>(4)</td></tr><tr><td>AzV 15</td><td>O6.5 III(f)</td><td>13.61</td><td>13.60</td><td>110</td><td>39750</td><td>3.70</td><td>5.91</td><td>6.8E-07 2.9E-07<br>4.5E-07</td><td>2250</td><td>B</td><td>(8)</td></tr><tr><td>AzV 446</td><td>O6.5 V</td><td>15.42</td><td>15.37</td><td>30</td><td>39700</td><td>4.00</td><td>5.25</td><td>4.0E-09 3.0E-09<br>3.0E-09</td><td>1400</td><td>T</td><td>(4)</td></tr><tr><td>AzV 207</td><td>O7 V((f))z</td><td>14.92</td><td>15.05</td><td>110</td><td>38000</td><td>3.82</td><td>5.29</td><td>2.2E-08</td><td>1775</td><td>T</td><td>(8)</td></tr><tr><td>AzV 95</td><td>O7.5 V(f)</td><td>14.25</td><td>14.20</td><td>75</td><td>38250</td><td>3.64</td><td>5.58</td><td>7.6E-08</td><td>1850</td><td>N</td><td>(8)</td></tr><tr><td>AzV 461</td><td>O8 V</td><td>15.41</td><td>15.56</td><td>200</td><td>37100</td><td>4.05</td><td>5.00</td><td>1.0E-09 1.3E-09<br>1.3E-09</td><td>1540</td><td>T</td><td>(4)</td></tr><tr><td>AzV 440</td><td>O8 V</td><td>15.27</td><td>15.30</td><td>100</td><td>37000</td><td>4.01</td><td>5.28</td><td>&le;3.0E-07</td><td>1300</td><td>T</td><td>(2)</td></tr><tr><td>AzV 468</td><td>O8.5 V</td><td>15.92</td><td>15.95</td><td>50</td><td>34700</td><td>4.00</td><td>4.76</td><td>&le;7.0E-10</td><td>1540</td><td>T</td><td>(4)</td></tr><tr><td>AzV 223</td><td>O9.5 II</td><td>14.30</td><td>14.25</td><td>140</td><td>31600</td><td>3.45</td><td>5.37</td><td>2.0E-07</td><td>1680</td><td>B</td><td>(5)</td></tr><tr><td>AzV 378</td><td>O9.5 III</td><td>14.48</td><td>14.53</td><td>110</td><td>31500</td><td>3.27</td><td>5.34</td><td>&le;1.0E-07</td><td>2000</td><td>T</td><td>(1, 2)</td></tr><tr><td>NGC 346-ELS-090</td><td>O9.5 V</td><td>16.48</td><td>16.43</td><td>188</td><td>34900</td><td>4.28</td><td>4.56</td><td>&le;9.8E-08</td><td>2978</td><td>T</td><td>(3)</td></tr><tr><td>AzV 170</td><td>O9.7 III</td><td>14.67</td><td>14.71</td><td>70</td><td>30500</td><td>3.41</td><td>5.14</td><td>1.5E-09 2.5E-09<br>2.5E-09</td><td>1200</td><td>T</td><td>(6)</td></tr><tr><td>AzV 396</td><td>B0 III</td><td>15.04</td><td>14.92</td><td>120</td><td>30000</td><td>3.52</td><td>5.17</td><td>&le;1.0E-07</td><td>2000</td><td>T</td><td>(1, 2)</td></tr><tr><td>NGC 346-MPG012</td><td>B0 IV</td><td>15.35</td><td>14.79</td><td>60</td><td>31000</td><td>3.65</td><td>4.93</td><td>5.0E-10</td><td>1250</td><td>T</td><td>(4)</td></tr></tbody></table>

**Note.** K<sub>s</sub> and Spitzer 4.5 µm magnitudes from A. Z. Bonanos et al. (2010). Stellar (v sin i, T<sub>eff</sub>, centrifugally corrected log g<sub>true</sub>, log L<sub>*</sub>/L<sub>☉</sub>) and wind (M&#x0307;, v<sub>∞</sub>) parameters were adopted from the references provided in column “References.” These used Hα and/or UV resonance lines as the main mass-loss diagnostics, as follows, and considered clumping unless otherwise noted: (1) P. Massey et al. (2004), Hα (unclumped); (2) P. Massey et al. (2005), Hα (unclumped); (3) M. R. Mokiem et al. (2006), Hα (unclumped); (4) J. C. Bouret et al. (2013), UV; (5) P. Massey et al. (2013), Hα; (6) J. C. Bouret et al. (2021), UV; (7) F. Martins et al. (2024), UV; (8) F. Backs et al. (2024), UV+Hα. Column “Regime” specifies the expected wind regime and Brα morphology: B—broad, N—narrow, and T—thin wind (see Section 2). A subsample of five objects was analyzed in Section 5 with CMFGEN and FASTWIND, yielding the mass-loss rates provided in the second and third entry of column “M&#x0307;,” respectively.

## 2. Sample Selection

Our primary project goal is to obtain reliable M&#x0307; measurements of thin wind stars by exploiting the unique physical behavior of Brα, which is independent from the limitations and uncertainties of Hα and UV diagnostics. To this end, the target sample was designed to probe the mass-loss rates and WLR of O- and early B-type stars, with emphasis on the low-luminosity, thin wind regime (see Table 1 and Figure 1).

The bulk of the sample consists of 10 stars with log L<sub>*</sub>/L<sub>☉</sub> &le; 5.4 (labeled “T”), for which Hα is unable to yield mass-loss rates and where FASTWIND and CMFGEN models predict narrow Brα emission on top of photospheric absorption wings. In order to enable cross calibration against the new Brα measurements, the sample also includes stars with wind-sensitive Hα profiles. We considered a number of such objects for which the models predict Brα hydrogen emission to be narrow (“N,” with photospheric absorption, e.g., AzV 95) or broad (“B,” with both core and wing emission, e.g., AzV 15). Because some of them are close to the narrow-to-broad-transition mass-loss rates, and rotational broadening additionally affects the Brα profile (see Section 4), five objects were included with various v sin i values. These five targets ensure a proper understanding of the physics of Brα and its transition from the narrow to the broad regime.

All targets are well-observed O-type stars in the main body of the SMC, with reliable photospheric parameters (T<sub>eff</sub>, log g, log L<sub>*</sub>/L<sub>☉</sub>) derived from optical or optical and UV data (see Table 1). Besides luminosity and mass-loss rates, the sample

was designed to assess the role of effective temperature and gravity. Binaries were avoided, at least in so far as this information was available. A final, critical constraint was that nebulosity should be avoided, which is especially important to prevent nebular contamination of narrow Brα profile components.

## 3. Observations and Data Reduction

Table 2 summarizes the JWST/NIRSpec data obtained under the auspices of JWST Cycle 2 program GO-03225 (PI: Garcia). All observations were made in Fixed Slit mode through the S200A2 aperture with the high-resolution G395H grating and the F290LP long-pass filter. This configuration provides wavelength coverage between 2.87 and 5.27 µm with a small gap between 3.81 and 3.91 µm due to the separation of the two detectors. Besides Brα, our observations include additional diagnostic lines such as Pfγ 3.75, Hβ 4.65, He II 3.09, He I 4.29, and He II 4.76 µm. On-orbit measurements indicate that the resolving power of this mode is ~3600 (Y. Isobe et al. 2023), which is considerably better than prelaunch predictions of ~2700 (P. Jakobsen et al. 2022). This resolving power corresponds to velocity resolution of ~85 km s<sup>-1</sup> at the wavelength of Brα.

Each observational sequence consisted of a wide-aperture target acquisition (WATA)<sup>12</sup> to place the source accurately in

<footnote n="12">12 https://jwst-docs.stsci.edu/jwst-near-infrared-spectrograph/nirspec-operations/nirspec-target-acquisition#gsc.tab=0</footnote>
<figure><img src="image_5.png" /><figcaption>**Figure 2.** Left: NIRSpec spectrum of NGC 346-ELS-090, embedded in intense H II emission, after reduction with and without background subtraction. Right: same, now showing a target within negligible nebulosity.</figcaption></figure>

<table><caption>**Table 2**
Journal of Observations</caption><thead><tr><th>Target</th><th>Spectral Type</th><th>Visit ID</th><th>Readpatt</th><th>N<sub>ints</sub></th><th>N<sub>groups</sub></th><th>UT (Start)</th><th>Exptime (s)</th><th>S/N</th></tr></thead><tbody><tr><td>AzV 177</td><td>O4 V(f(f))</td><td>03225012001</td><td>NRSIRS2</td><td>2</td><td>16</td><td>2024-06-25T21:11:26</td><td>11671</td><td>184</td></tr><tr><td>AzV 388</td><td>O4 V</td><td>03225013001</td><td>NRSIRS2RAPID</td><td>1</td><td>90</td><td>2024-08-03T14:25:11</td><td>6565</td><td>181</td></tr><tr><td>AzV 15</td><td>O6.5 III(f)</td><td>03225015001</td><td>NRSIRS2RAPID</td><td>1</td><td>30</td><td>2024-06-25T17:43:52</td><td>2188</td><td>170</td></tr><tr><td>AzV 446</td><td>O6.5 V</td><td>03225008001</td><td>NRSIRS2</td><td>2</td><td>18</td><td>2024-08-03T06:17:55</td><td>13130</td><td>184</td></tr><tr><td>AzV 207</td><td>O7 V(f(f))z</td><td>03225009001</td><td>NRSIRS2</td><td>1</td><td>20</td><td>2024-07-31T19:42:33</td><td>7294</td><td>175</td></tr><tr><td>AzV 95</td><td>O7.5 V(f(f))</td><td>03225014001</td><td>NRSIRS2</td><td>1</td><td>12</td><td>2024-08-23T02:39:05</td><td>4377</td><td>166</td></tr><tr><td>AzV 461</td><td>O8 V</td><td>03225004001</td><td>NRSIRS2</td><td>2</td><td>18</td><td>2024-07-04T20:15:12</td><td>13130</td><td>185</td></tr><tr><td>AzV 440</td><td>O8 V</td><td>03225007001</td><td>NRSIRS2</td><td>2</td><td>16</td><td>2024-08-03T02:23:44</td><td>11671</td><td>186</td></tr><tr><td>AzV 468</td><td>O8.5 V</td><td>03225002001</td><td>NRSIRS2</td><td>3</td><td>20</td><td>2024-07-04T13:28:23</td><td>21883</td><td>189</td></tr><tr><td>AzV 223</td><td>O9.5 II</td><td>03225011001</td><td>NRSIRS2RAPID</td><td>1</td><td>60</td><td>2024-08-03T12:37:56</td><td>4377</td><td>188</td></tr><tr><td>AzV 378</td><td>O9.5 III</td><td>03225010001</td><td>NRSIRS2RAPID</td><td>1</td><td>70</td><td>2024-08-03T10:36:02</td><td>5106</td><td>186</td></tr><tr><td>NGC 346-ELS-090</td><td>O9.5 V</td><td>03225001001</td><td>NRSIRS2</td><td>6</td><td>20</td><td>2024-08-02T10:16:31</td><td>43767</td><td>213</td></tr><tr><td>AzV 170</td><td>O9.7 III</td><td>03225005001</td><td>NRSIRS2RAPID</td><td>1</td><td>80</td><td>2024-06-25T18:55:36</td><td>5836</td><td>180</td></tr><tr><td>AzV 396</td><td>B0 III</td><td>03225006001</td><td>NRSIRS2</td><td>2</td><td>13</td><td>2024-08-02T23:10:13</td><td>9483</td><td>188</td></tr><tr><td>NGC 346-MPG-012</td><td>B0 IV</td><td>03225003001</td><td>NRSIRS2</td><td>2</td><td>16</td><td>2024-07-31T15:53:50</td><td>11671</td><td>181</td></tr></tbody></table>

**Note.** See the main text for the column description.

the S200A2 aperture, which was followed by spectroscopic exposures at five primary dither positions offset along the spatial dimension of the aperture. The NIRSpec detectors were read with either the NRSIRS2RAPID or NRSIRS2 pattern to mitigate the effects of “1/f noise.” NRSIRS2RAPID was generally preferred for integrations consisting of fewer than 90 groups. Table 2 records the number of integrations (N<sub>ints</sub>) and groups per integration (N<sub>groups</sub>) that were tuned to achieve S/N ≥ 150 without saturating, as required to define the continuum flux to a precision of 1%. The total exposure time devoted to each target (Exptime), and the median S/N per pixel measured between 4.2 and 4.4 µm are listed in the final two columns of Table 2.

The observations were processed with version 1.18.0 of the JWST calibration pipeline, which uses the reference files specified in Calibration Reference Data System context jwst_1364.pmap. Processing through the initial CALWEBB-DETECTOR1 stage relied on default values of parameters to produce a count-rate image for each exposure in the dither pattern for a given target and included additional mitigation for 1/f noise in the clean_flicker step. These images were subsequently flat-fielded, rectified, and resampled in the

CALWEBB\_SPEC2 stage of the pipeline. A combined background image was created and subtracted before the individual images were combined and a single spectrum extracted during processing in CALWEBB\_SPEC3 stage. Default values were generally chosen for all these processing stages, which used “exptime” weighting in both the resample_spec and outlier_detection steps. However, the extraction aperture was manually recentered on the trace in the resampled and rectified “s2d” image in the CALWEBB\_SPEC3 processing.

Our background subtraction strategy proved to be a critical step in recovering the shape of the stellar Brα profile. Figure 2 illustrates the influence of nebular contamination on Brα for a target on the outskirts of the giant H II region N66 (NGC 346-ELS-090; left panel) and for a more isolated target (AzV 170; right panel). In both cases the strategy of constructing a mean background image from the five spatially dithered images provided adequate mitigation of astrophysical contamination. This procedure, together with the consideration of the nebular environment during target selection, allowed the difficulties posed by background contamination described by A. Mang Román et al. (2025) to be avoided.
<figure><img src="image_6.png" /><figcaption>**Figure 3.** Brα spectra of slowly rotating sample stars, arranged by spectral type and luminosity class. The spectra are shown in the same vertical scale, offset by a constant for clarity. “B,” “N,” and “T” specify the *expected* regime. Vertical lines mark H I (red), He I (blue), and He II (orange) transitions. Stark absorption wings underlying the Brα emission are absent in AzV 15 and then evolve toward strong absorption in the later types.</figcaption></figure>

## 4. Brα Morphology of SMC O-type Stars

Figure 3 displays the NIRSpec Brα observations of the sample stars with relatively low projected rotational speed $v \sin i$, arranged by spectral type and luminosity class. Because rotational velocity broadens the Brα emission, the observations of fast rotating, $v \sin i \ge 150 \text{ km s}^{-1}$ stars are shown separately in Figure 4.

Figure 3 shows the trend of the line morphology with spectral type, though somewhat distorted by rotation and macroturbulence. AzV 15 exhibits pure, broad Brα emission. For the rest of the stars, Brα shows core emission on top of broad Stark absorption wings that increase in strength toward later spectral subtypes.

For the hotter types, the overlapping He II 4.0495 µm emission leads to broader emission (e.g., AzV 95 and AzV 207) and to a shift to shorter wavelengths of the peak of the

<figure><img src="image_7.png" /><figcaption>**Figure 4.** Same as Figure 3, now for the sample stars with $v \sin i \ge 150 \text{ km s}^{-1}$. The high rotational velocities broaden the Brα profiles and cause the *apparent* disagreement between observations and the prediction. The late spectral types show the broad absorption wings seen in Figure 3, although somehow washed out by the fast rotation.</figcaption></figure>

Brα line complex (e.g., AzV 15) as well as to an overall asymmetry in both broad and pure narrow emission profiles. For the later types, the asymmetry in the absorption component is caused by the He I 4.048 µm 5f-4f triplet and singlet transitions (note also the strong He I $n=5-4$ hydrogenic transitions at 4.037 and 4.040 µm in these subtypes). Thus, whereas the blue side of the Brα line complex is typically contaminated by He II (close to line center) and/or He I (in the absorption wings), its red side is dominated by the hydrogen transition alone, leading to the asymmetric line shape.

The observed morphology matches the model predictions of narrow/broad Brα profiles, as listed in Table 1, except for AzV 223. Broad Brα emission was expected for this star, but it exhibits the narrow emission and broad photospheric absorption typical for late types. This object displays emission filling in the Hα absorption core so that an actual $\dot{M}$ value could be derived under the assumption that the emission originated in the wind (see Table 1). However, the observed Brα line strongly hints at lower $\dot{M}$ than expected from Hα.

## 5. $\dot{M}$ Constraints from Quantitative Spectroscopy

We performed an initial analysis for a subsample of five stars with previously determined UV mass-loss rates, spanning different temperatures, luminosities, and wind regimes, by means of the non-LTE, unified model atmosphere code CMFGEN. Our panchromatic analysis by visual comparison against UV, optical, and JWST/NIRSpec data resulted in roughly the same stellar parameters as provided in the literature (see Table 1). To obtain an overall good fit we adapted the wind parameters, the transition velocity between photosphere and wind, the macroturbulence, and the clumping law (the latter to fit optical and UV wind lines), aiming at the first atmosphere models that reproduce the complete UV-to-IR spectrum including the critical $\dot{M}$ indicator Brα. An example fit is shown in the Appendix. Pathfinder models show that neither clumping nor X-ray emission from wind-embedded shocks affect Brα in the thin wind regime since it is formed in the transonic region, where inhomogeneities and shocks are weak or absent (see also Appendix). They further show that the impact of X-rays on Brα is negligible in stronger winds as well. More details will be provided in a forthcoming paper, but
<figure><img src="image_8.png" /><figcaption>**Figure 5.** Line fits to a subset of five sample stars, encompassing different wind regimes, with CMFGEN (blue) and FASTWIND (orange) models. The mass-loss rate values obtained by the analysis with CMFGEN are provided next to each star.</figcaption></figure>

we refer the reader to F. Najarro et al. (2011) for thorough tests on the impact of clumping and transition velocity.

As an independent check, we used FASTWIND (v10.6) models to calculate Brα profiles, for identical photospheric parameters, microturbulence, and clumping law as derived by CMFGEN, and varied only M and the shape of the velocity law (keeping FASTWIND’s default transition velocity at v<sub>trans</sub> = 0.1 v<sub>sound</sub>).

Figure 5 shows the best-fitting models for the five stars analyzed at the Brα region. After accounting for v sin i, microturbulence, and spectral resolution, all CMFGEN and most FASTWIND profiles reproduce the observed Brα emission and (if present) the asymmetric broad photospheric absorption quite well. Despite extremely thin winds, we managed to constrain mass-loss rates with both codes and obtained similar or identical values (see Table 1). The most outstanding difference, of a factor 4, is registered for AzV 177, but this fast rotator could experience spherical-symmetry departures. In fact, the shape of the Brα emission resembles several spectral features observed in the optical spectrum of the fast rotating O4 If ζ Puppis star (D. J. Hillier et al. 2012). Moreover, we currently estimate M uncertainties as roughly a factor 2, given the influence of the transition velocity and the microturbulence on the formation of Brα in thin wind stars (F. Najarro et al. 2011). Further tests and accurate error estimates will be performed in the forthcoming paper.

Most interestingly, however, our M values generally agree well with those from previous studies using UV lines (see Table 1). Thus it seems that at least for this subset of five objects, the uncertainties discussed in Section 1 do not play an

important role, and/or the underlying assumptions for UV analyses (X-rays, clumping) are reasonable. Moreover, our results confirm the low Ṁ derived for thin wind stars in the UV and the discrepancy with J. S. Vink et al. (2001)'s WLR by ~1–2 orders of magnitude.

## 6. Conclusions and Future Work

We present high-S/N JWST/NIRSpec observations of a sample of thin wind candidates in the SMC. In contrast to A. Mang Román et al. (2025), we find a clear correlation of Brα morphology with spectral types, likely emerging as a result of the higher S/N and minimal nebular contamination issues of our data set. Moreover, a comparison between the observed morphology and predictions from model atmosphere codes reveals good agreement.

For a subsample of five objects, we analyzed archival UV and optical spectra together with our new IR data to infer their mass-loss rate mainly from Brα. The resulting Ṁ values are quite similar to previous values obtained from the UV alone. Overarching conclusions from our analysis are (i) Brα is a useful Ṁ estimator also in the case of thin winds, (ii) narrow Brα can provide mass-loss rates in the range where other diagnostics are insensitive or not available (e.g., due to high extinction), and (iii) there is overlap with the regime where Hα is sensitive, thus enabling a critical consistency check between mass-loss rates derived from narrow Brα and Hα.

One of the major questions to be answered is whether thin winds are actually weak or only mimic such low Ṁ because of insufficient shock cooling and/or the presence of multiple components (e.g., D. P. Huenemoerder et al. 2012; J. C. Bouret et al. 2015; C. Lagae et al. 2021). In this context D. R. Law et al. (2024) used JWST/MIRI to observe highly ionized, forbidden mid-infrared emission lines that form in the outer wind of 10 Lac and obtained a mass-loss rate one order of magnitude above UV/optical results. While very promising, this method is subject to uncertainties related to clumping and multiple wind components, which likely have little impact on the Brα diagnostics that are based on the conditions in the transonic region. Nevertheless, additional data in this spectral domain would be informative.

Analysis of our complete data set, including the full list of lines formed in the transonic region and captured by our JWST/NIRSpec data (see Section 3), will provide unique insights on the true mass-loss rates of thin wind stars and potentially yield a robust, empirical WLR over the entire luminosity range. Furthermore, comparison with Milky Way analogs will enable a new determination of the metallicity dependence of radiation-driven mass loss, providing the boundary conditions for empirically supported mass-loss recipes in codes simulating the evolution of massive stars in the nearby and distant Universe.

Given the somewhat surprising result that all five analyzed stars display consistent Brα and UV mass-loss rates, and that the observational features for the other objects also point to very low mass-loss rates for log(L/L<sub>☉</sub>) ≤ 5.4, it is highly likely that the weak-wind problem is real: at low luminosities and low metallicities, the values expected from an extrapolation of the empirical high-luminosity WLR are too large, and modern models fail to reproduce the observed change of slope, requiring further effort for clarification. In this sense, the problem remains unsolved.
## Acknowledgments

This work is based on observations with the NASA/ESA/ CSA James Webb Space Telescope obtained at the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-03127. All data products can be accessed at MAST: doi:10.17909/xxf8-f637. Support for Program number 03225 is provided through a grant from the STScI under NASA contract NAS5-03127.

M.G., F.N., A.L., and F.T. gratefully acknowledge support by grant PID2022-137779OB-C41, and M.G. further acknowledges grant PID2022-140483NB-C22, funded by the Spanish Ministry of Science, Innovation and Universities/State Agency of Research MICIU/AEI/10.13039/501100011033 and by “ERDF A way of making Europe.” M.G. and F.N. also acknowledge grant MAD4SPACE, TEC-2024/TEC-182 from Comunidad de Madrid (Spain). D.J.L., A.H., and S.S.-D. are supported by the Spanish Government Ministerio de Ciencia e Innovación through grant PID2021-122397NB-C21. A.L. also acknowledges funding from grant PREP2022-000263. A.W.F. and D.J.H. acknowledge support from grants JWST-GO-03225.002-A and JWST-GO-03225.003-A, respectively. We

gratefully acknowledge the valuable comments and suggestions by our anonymous referee.

Facility: JWST (NIRSpec).

## Appendix

### Multiwavelength Fit

To illustrate the quality of the analysis described in Section 5, Figure 6 shows the best-fitting synthetic spectra to AzV 446 for important stellar and wind diagnostic lines observed in the UV (ULLYSES library, J. Roman-Duval et al. 2025), optical (XSHOOTU library, J. S. Vink et al. 2023), and L-band ranges (this work). The fit includes the *Ṁ*-sensitive diagnostic lines Pfγ, Brα, and Huβ. The best-fitting CMFGEN model has very similar parameters to those found by J. C. Bouret et al. (2013): slightly adjusted *T*<sub>eff</sub> = 40,750 K and log *g* = 4.2, the same clumping and velocity field values these authors derived, *f*<sub>vol</sub> = 0.1, *v*<sub>∞</sub> = 1400 km s<sup>-1</sup>, and X-ray luminosity *L*<sub>x</sub>/*L*<sub>*</sub> = 5E-07, *v*<sub>trans</sub> = 0.1 *v*<sub>sound</sub>, and *Ṁ* = 3.0E-09 *M*<sub>☉</sub> yr<sup>-1</sup>. Additional CMFGEN spectra for models with the same parameters, except for clumping and X-rays, which are switched off, are also shown in Figure 6 to show that related variations of Brα (and other L-band lines) are negligible.
<figure><img src="image_9.png" /></figure>

Wavelength

**Figure 6.** JWST observations of AzV 446 and archival optical and UV data (black), together with model fits that account for instrumental and rotational/macroturbulence broadening. The best-fitting CMFGEN model (red) reproduces $T_{\text{eff}}$ and log g diagnostic lines in the visible, as well as classical mass-loss rate indicators in the UV and optical ranges. The model spectra successfully reproduce the observed M-sensitive lines in the L-band (lowermost row). For comparison, the figure includes synthetic spectra for models without clumping (orange) and without X-rays (blue). Such differences in the simulations do not produce any effect on the displayed L-band lines.
ORCID iDs

Miriam Garcia https://orcid.org/0000-0003-0316-1208

Alexander W. Fullerton https://orcid.org/0000-0003-2429-7964

Francisco Najarro https://orcid.org/0000-0002-9124-0039

Joachim Puls https://orcid.org/0000-0002-0874-1669

Daniel J. Lennon https://orcid.org/0000-0003-3063-4867

Jean-Claude Bouret https://orcid.org/0000-0003-4946-2591

Christopher J. Evans https://orcid.org/0009-0005-7288-6407

Margaret Hanson https://orcid.org/0000-0003-1780-6150

Artemio Herrero https://orcid.org/0000-0001-8768-2179

D. John Hillier https://orcid.org/0000-0001-5094-8017

Alexandre Legault https://orcid.org/0000-0003-2372-9825

María del Mar Rubio-Díez https://orcid.org/0000-0003-4076-7313

Sergio Simón-Díaz https://orcid.org/0000-0003-1168-3524

Jon O. Sundqvist https://orcid.org/0000-0003-1729-1273

Frank Tramper https://orcid.org/0000-0001-8631-7700

References

Backs, F., Brands, S. A., de Koter, A., et al. 2024, A&A, 692, A88

Björklund, R., Sundqvist, J. O., Puls, J., & Najarro, F. 2021, A&A, 648, A36

Bonanos, A. Z., Lennon, D. J., Köhlinger, F., et al. 2010, AJ, 140, 416

Bouret, J. C., Lanz, T., Hillier, D. J., et al. 2003, ApJ, 595, 1182

Bouret, J. C., Lanz, T., Hillier, D. J., et al. 2015, MNRAS, 449, 1545

Bouret, J. C., Lanz, T., Martins, F., et al. 2013, A&A, 555, A1

Bouret, J. C., Martins, F., Hillier, D. J., et al. 2021, A&A, 647, A134

Conti, P. S. 1975, MSRSL, 9, 193

Eggenberger, P., Meynet, G., Maeder, A., et al. 2008, Ap&SS, 316, 43

Evans, C. J., Lennon, D. J., Walborn, N. R., Trundle, C., & Rix, S. A. 2004, PASP, 116, 909

Fullerton, A. W., Massa, D. L., & Prinja, R. K. 2006, ApJ, 637, 1025

Heap, S. R., Lanz, T., & Hubeny, I. 2006, ApJ, 638, 409

Hillier, D. J., Bouret, J.-C., Lanz, T., & Busche, J. R. 2012, MNRAS, 426, 1043

Hillier, D. J., Lanz, T., Heap, S. R., et al. 2003, ApJ, 588, 1039

Hillier, D. J., & Miller, D. L. 1998, ApJ, 496, 407

Huenemoerder, D. P., Oskinova, L. M., Ignace, R., et al. 2012, ApJL, 756, L34

Isobe, Y., Ouchi, M., Nakajima, K., et al. 2023, ApJ, 956, 139

Jakobsen, P., Ferruit, P., Alves de Oliveira, C., et al. 2022, A&A, 661, A80

Josiek, J., Ekström, S., & Sander, A. A. C. 2024, A&A, 688, A71

Krtička, J., & Kubát, J. 2018, A&A, 612, A20

Kudritzki, R. P., Pauldrach, A., & Puls, J. 1987, A&A, 173, 293

Lagae, C., Driessen, F. A., Hennicker, L., Kee, N. D., & Sundqvist, J. O. 2021, A&A, 648, A94

Langer, N., Kiriakidis, M., El Eid, M. F., Fricke, K. J., & Weiss, A. 1988, A&A, 192, 177

Law, D. R., Hawcroft, C., Smith, L. J., et al. 2024, ApJL, 976, L25

Maeder, A. 1981, A&A, 99, 97

Mang Román, A., Zeidler, P., Hamann, W.-R., et al. 2025, ApJL, 984, L49

Marcolino, W. L. F., Bouret, J. C., Martins, F., et al. 2009, A&A, 498, 837

Marcolino, W. L. F., Bouret, J. C., Rocha-Pinto, H. J., Bernini-Peron, M., & Vink, J. S. 2022, MNRAS, 511, 5104

Martins, F., Bouret, J. C., Hillier, D. J., et al. 2024, A&A, 689, A31

Martins, F., Schaerer, D., Hillier, D. J., & Heydari-Malayeri, M. 2004, A&A, 420, 1087

Massey, P., Bresolin, F., Kudritzki, R. P., Puls, J., & Pauldrach, A. W. A. 2004, ApJ, 608, 1001

Massey, P., Neugent, K. F., Hillier, D. J., & Puls, J. 2013, ApJ, 768, 6

Massey, P., Puls, J., Pauldrach, A. W. A., et al. 2005, ApJ, 627, 477

Massey, P., Zangari, A. M., Morrell, N. I., et al. 2009, ApJ, 692, 618

Mokiem, M. R., de Koter, A., Evans, C. J., et al. 2006, A&A, 456, 1131

Mokiem, M. R., de Koter, A., Vink, J. S., et al. 2007, A&A, 473, 603

Murdoch, K. A., Drew, J. E., & Anderson, L. S. 1994, A&A, 284, L27

Najarro, F., Hanson, M. M., & Puls, J. 2011, A&A, 535, A32

Oskinova, L. M., Hamann, W. R., & Feldmeier, A. 2007, A&A, 476, 1331

Paxton, B., Cantiello, M., Arras, P., et al. 2013, ApJS, 208, 4

Petrovic, J., Langer, N., Yoon, S. C., & Heger, A. 2005, A&A, 435, 247

Prinja, R. K., & Massa, D. L. 2010, A&A, 521, L55

Puls, J., Kudritzki, R. P., Herrero, A., et al. 1996, A&A, 305, 171

Puls, J., Urbaneja, M. A., Venero, R., et al. 2005, A&A, 435, 669

Puls, J., Vink, J. S., & Najarro, F. 2008, A&ARv, 16, 209

Ramachandran, V., Hamann, W. R., Oskinova, L. M., et al. 2019, A&A, 625, A104

Rickard, M. J., Hainich, R., Hamann, W. R., et al. 2022, A&A, 666, A189

Rivero González, J. G., Puls, J., & Najarro, F. 2011, A&A, 536, A58

Roman-Duval, J., Fischer, W. J., Fullerton, A. W., et al. 2025, ApJ, 985, 109

Sundqvist, J. O., Puls, J., & Owocki, S. P. 2014, A&A, 568, A59

Vink, J. S., de Koter, A., & Lamers, H. J. G. L. M. 2001, A&A, 369, 574

Vink, J. S., Mehner, A., Crowther, P. A., et al. 2023, A&A, 675, A154

Walborn, N. R., Lennon, D. J., Heap, S. R., et al. 2000, PASP, 112, 1243