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Evolved Massive Stars at Low-metallicity V. Mass-Loss Rate of Red Supergiant Stars in the Small Magellanic Cloud

Ming Yang (杨明), Alceste Z. Bonanos, Biwei Jiang (姜碧沩), Emmanouil Zapartas, Jian Gao (高健), Yi Ren(任逸), Man I Lam (林敏仪), Tianding Wang (王天丁), Grigoris Maravelias, Panagiotis Gavras, Shu Wang (王舒), Xiaodian Chen (陈孝钿), Frank Tramper, Stephan de Wit, Bingqiu Chen (陈丙秋), Jing Wen (文静), Jiaming Liu (刘佳明), Hao Tian (田浩), Konstantinos Antoniadis, and Changqing Luo (罗常青)

ABSTRACT
The mass-loss rate (MLR) is one of the most important parameters in astrophysics, since it impacts many areas of astronomy, such as, the ionizing radiation, wind feedback, star-formation rates, initial mass functions, stellar remnants, supernovae, and so on. However, the most important modes of mass-loss are also the most uncertain, as we are still far from clear about the dominant physical mechanisms of the mass-loss. Here we assemble the most complete and clean red supergiant (RSG) sample (2,121 targets) so far in the Small Magellanic Cloud (SMC) with 53 different bands of data to study the MLR of RSGs. In order to match the observed spectral energy distributions (SEDs), a theoretical grid of 17,820 Oxygen-rich models (“normal” and “dusty” grids are half-and-half) is created by the radiatively-driven wind model of the DUSTY code, covering a wide range of dust parameters. We select the best model for each target by calculating the minimal modified chi-square and visual inspection. The resulting MLRs from DUSTY are converted to real MLRs based on the scaling relation, for which a total MLR of 6.16 × 10⁻³ M yr^-1 is measured (corresponding to a dust-production rate of ∼ 6 × 10⁻⁶ M yr^-1), with a typical MLR of ∼ 10⁻⁶ M yr^-1 for the general population of the RSGs. The complexity of mass-loss estimation based on the SED is fully discussed for the first time, indicating large uncertainties based on the photometric data (potentially up to one order of magnitude or more). The Hertzsprung-Russell and luminosity versus median absolute deviation diagrams of the sample indicate the positive relation between luminosity and MLR. Meanwhile, the luminosity versus MLR diagrams show a “knee-like” shape with enhanced mass-loss occurring above log10(L/L) ≈ 4.6, which may be due to the degeneracy of luminosity, pulsation, low surface gravity, convection, and other factors. We derive our MLR relation by using a third-order polynomial to fit the sample and compare our result with previous empirical MLR prescriptions. Given that our MLR prescription is based on a much larger sample than previous determinations, it provides a more accurate relation at the cool and luminous region of the H-R diagram at low-metallicity compared to previous studies. Finally, 9 targets in our sample were detected in the UV, which could be an indicator of OB-type companions of binary RSGs.

arXiv.org: 2304.01835

Three poster contributions during EAS 2021 with the following … statistics: all of them on massive stars,  two within the framework of the ASSESS project, and two on machine-learning applications.

1. Applying machine-learning methods to build a photometric classifier for massive stars in nearby galaxies

Grigoris Maravelias, Alceste Bonanos, Frank Tramper, Stephan de Wit, Ming Yang, Paolo Bonfini

Mass loss is a key parameter in the evolution of massive stars. Despite the recent progress in the theoretical understanding of how stars lose mass, discrepancies between theory and observations still hold. Even worse, episodic mass loss in evolved massive stars is not included in the models while the importance of its role in the evolution os massive stars is currently undetermined. A major hindrance to determining the role of episodic mass loss is the lack of large samples of classified stars. Given the recent availability of extensive photometric catalogs from various surveys spanning a range of metallicity environments, we aim to remedy the situation by applying machine learning techniques to these catalogs.We compiled a large catalog of known massive stars in M31 and M33, using IR (Spitzer) and optical (Pan-STARRS) photometry, as well as Gaia astrometric information. We grouped them in 7 classes (Blue, Red, Yellow, B[e] supergiants, Luminous Blue Variables, Wolf-Rayet, and outliers, e.g. QSO’s and background galaxies). Using this catalog as a training set, we built an ensemble classifier utilizing color indices as features. The probabilities from three machine-learning algorithms (Support Vector Classification, Random Forests, Neural Networks) are combined to obtain the final classifications. The overall performance of the classifier is ~87%. Highly populated (Red/Blue/Yellow Supergiants) and well-defined classes (B[e] Supergiants) have a high recovery rate between ~98-74%. On the contrary, Wolf-Rayet sources are detected at ~20% while Luminous Blue Variables are almost non-existent. The is mainly due to the small sample sizes of these classes, although M31 and M33 have spectral classifications for several massive stars (about 2500). In addition, the mixing of spectral types, as there are no strict boundaries in the features space (color indexes) between those classes, complicates the classification. In an independent application of the classifier to other galaxies (IC 1613, WLM, Sextans A) we obtained an overall accuracy of ~71% despite the missing values on their features (which we replace with averaged values from the training sample). This approach results only in a few percent difference, with the remaining discrepancy attributed to the different metallicity environments of their host galaxies. The classifier’s prediction capability is only limited by the available number of sources per class, reflecting the rarity of these objects and the possible physical links between these massive star phases. Our methodology is also efficient in correctly classifying sources with missing data and at lower metallicities, making it an excellent tool for spotting interesting objects and prioritizing targets for observations. Future spectroscopic observations will offer a test-bed of its actual performance along with opportunities for improvement.

For more see this k-poster (submitted for SS32: Machine Learning and Visualisation in Data Intensive Era ).

2. A new automated tool for the spectral classification of OB stars

E. Kyritsis, G. Maravelias, A. Zezas, P. Bonfini, K. Kovlakas, P. Reig

As more and more large spectroscopic surveys become available, an automated approach in spectral classification becomes necessary. Due to the importance of the massive stars it is of paramount importance to identify the phenomenological parameters of these stars (e.g., the spectral type ) which can be used as proxies to their physical parameters (e.g mass, temperature).
In this work, we use the Random Forest (RF) algorithm to develop a tool for automated spectral classification of the OB-type stars into their sub-types. We use the regular RF algorithm, the Probabilistic RF (PRF) which is an extension of RF that incorporates uncertainties, and we introduce the KDE – RF method which is a combination of the Kernel-Density Estimation and the RF algorithm. We train the algorithms on the Equivalent Width (EW) of characteristic absorption lines measured in the spectra from large Galactic (LAMOST, GOSSS) and extragalactic surveys (2dF, VFTS) with available spectral-type classification. By following an adaptive binning approach we group the labels of these data on 11 sub-types within the range O3-B9. We examined which of the characteristic spectral lines (features) are more important to use based on a number of feature selection methods and we searched for the optimal hyper-parameters of the classifiers, to achieve the best performance.
From the feature screening process, we find 13 spectral lines as the optimal number of features. We find that the overall accuracy score is ~ 76 % with similar results across all approaches, with our KDE – RF being slightly lower at ~ 73 %. In addition, we show that our optimized RF model can reach an overall accuracy score of ~ 85 % in the ideal case of robust measurement of the weakest characteristic spectral lines. We apply our model in other observational data sets providing examples of potential application of our classifier on real science cases. We find that it performs well for both single massive stars and for the companion massive stars in Be X-ray Binaries, especially for data with S/N in the range 50-300. Furthermore, we present an alternative model for lower quality data S/N < 25 based on a reduced feature-set classification scheme, including only the strongest spectral lines.
The similarity in the performances of our models indicates the robustness and the reliability of the RF algorithm when used for spectral classification of early-type stars. This is strengthened also by the fact that we are working with real-world data and not with simulations. In addition, the approach presented in this work is very fast and applicable to products from different surveys in terms of quality (e.g different resolutions) and of different formats (e.g., absolute or normalized flux).

For more see this k-poster (submitted for S16: Massive stars: birth, rotation, and chemical evolution).

3. Evolved massive stars in the Magellanic Clouds

Ming Yang, Alceste Bonanos, Biwei Jiang, Jian Gao, Panagiotis Gavras, Grigoris Maravelias, Man I Lam, Shu Wang, Xiaodian Chen, Yi Ren, Frank Tramper, Zoi Spetsieri

We present two clean, magnitude-limited (IRAC1 or WISE1≤15.0 mag) multiwavelength source catalogs for the Large and Small Magellanic Cloud (LMC and SMC). The catalogs were built by crossmatching (1”) and deblending (3”) between the source list of Spitzer Enhanced Imaging Products (SEIP) and Gaia Data Release 2 (DR2), with strict constraints on the Gaia astrometric solution in order to remove the foreground contamination. It is estimated that about 99.5% of the targets in our catalog are most likely genuine members of the LMC and SMC. The LMC catalog contains 197,004 targets in 52 different bands, while SMC catalog including contains 45,466 targets in 50 different bands, ranging from the ultraviolet to the far-infrared. Additional information about radial velocities and spectral and photometric classifications were collected from the literature. For the LMC, we compare our sample with the sample from Gaia Collaboration et al. (2018), indicating that the bright end of our sample is mostly comprised of blue helium-burning stars (BHeBs) and red HeBs with inevitable contamination of main sequence stars at the blue end. For the SMC, by using the evolutionary tracks and synthetic photometry from MESA Isochrones & Stellar Tracks and the theoretical J-Ks color cuts, we identified and ranked 1,405 red supergiant (RSG), 217 yellow supergiant (YSG), and 1,369 blue supergiant (BSG) candidates in the SMC in five different color-magnitude diagrams (CMDs), where attention should also be paid to the incompleteness of our sample. For the LMC, due to the problems with models, we applied modified magnitude and color cuts based on previous studies, and identified and ranked 2,974 RSG, 508 YSG, and 4,786 BSG candidates in the LMC in six CMDs. The comparison between the CMDs from the two catalogs of the LMC SMC indicates that the most distinct difference appears at the bright red end of the optical and near-infrared CMDs, where the cool evolved stars (e.g., RSGs, asymptotic giant branch stars, and red giant stars) are located, which is likely due to the effect of metallicity and star formation history. A further quantitative comparison of colors of massive star candidates in equal absolute magnitude bins suggests that there is essentially no difference for the BSG candidates, but a large discrepancy for the RSG candidates since LMC targets are redder than the SMC ones, which may be due to the combined effect of metallicity on both spectral type and mass-loss rate as well as the age effect. The effective temperatures (Teff) of massive star populations are also derived from reddening-free color of (J-Ks). The Teff ranges are 3500≤Teff≤5000 K for an RSG population, 5000≤Teff≤8000 K for a YSG population, and Teff≥8000 K for a BSG population, with larger uncertainties toward the hotter stars.

For more see this k-poster (submitted for S16: Massive stars: birth, rotation, and chemical evolution).

Evolved Massive Stars at Low-metallicity II. Red Supergiant Stars in the Small Magellanic Cloud

Ming Yang, Alceste Z. Bonanos, Bi-Wei Jiang, Jian Gao, Panagiotis Gavras, Grigoris Maravelias, Shu Wang, Xiao-Dian Chen, Frank Tramper, Yi Ren, Zoi T. Spetsieri, Meng-Yao Xue

We present the most comprehensive RSG sample for the SMC up to now, including 1,239 RSG candidates. The initial sample is derived based on a source catalog for the SMC with conservative ranking. Additional spectroscopic RSGs are retrieved from the literature, as well as RSG candidates selected from the inspection of CMDs. We estimate that there are in total ∼ 1,800 or more RSGs in the SMC. We purify the sample by studying the infrared CMDs and the variability of the objects, though there is still an ambiguity between AGBs and RSGs. There are much less RSGs candidates (∼4%) showing PAH emission features compared to the Milky Way and LMC (∼15%). The MIR variability of RSG sample increases with luminosity. We separate the RSG sample into two subsamples (“risky” and “safe”) and identify one M5e AGB star in the “risky” subsample. Most of the targets with large variability are also the bright ones with large MLR. Some targets show excessive dust emission, which may be related to previous episodic mass loss events. We also roughly estimate the total gas and dust budget produced by entire RSG population as ∼1.9(+2.4/−1.1)×10⁻⁶ M⊙/yr in the most conservative case. Based on the MIST models, we derive a linear relation between Teff and observed J−KS color with reddening correction for the RSG sample. By using a constant bolometric correction and this relation, the Geneva evolutionary model is compared with our RSG sample, showing a good agreement and a lower initial mass limit of ∼7 M⊙ for the RSG population. Finally, we compare the RSG sample in the SMC and the LMC. Despite the incompleteness of LMC sample in the faint end, the result indicates that the LMC sample always shows redder color (except for the IRAC1−IRAC2 and WISE1−WISE2 colors due to CO absorption) and larger variability than the SMC sample.

arXiv.org: 2005.10108

Evolved Massive Stars at Low-metallicity I. A Source Catalog for the Small Magellanic Cloud

Ming Yang, Alceste Z. Bonanos, Bi-Wei Jiang, Jian Gao, Panagiotis Gavras, Grigoris Maravelias, Yi Ren, Shu Wang, Meng-Yao Xue, Frank Tramper, Zoi T. Spetsieri, Ektoras Pouliasis

We present a clean, magnitude-limited (IRAC1 or WISE1 ≤ 15.0 mag) multiwavelength source catalog for the SMC with 45,466 targets in total, with the purpose of building an anchor for future studies, especially for the massive star populations at low-metallicity. The catalog contains data in 50 different bands including 21 optical and 29 infrared bands, ranging from the ultraviolet to the far-infrared. Additionally, radial velocities and spectral classifications were collected from the literature, as well as infrared and optical variability statistics were retrieved from different projects. The catalog was essentially built upon a 1′′ crossmatching and a 3′′ deblending between the SEIP source list and Gaia DR2 photometric data. Further constraints on the proper motions and parallaxes from Gaia DR2 allowed us to remove the foreground contamination. We estimated that about 99.5\% of the targets in our catalog were most likely genuine members of the SMC. By using the evolutionary tracks and synthetic photometry from MIST and the theoretical J−KS color cuts, we identified 1,405 RSG, 217 YSG and 1,369 BSG candidates in the SMC in five different CMDs, where attention should also be paid to the incompleteness of our sample. We ranked the candidates based on the intersection of different CMDs. A comparison between the models and observational data shows that the lower limit of initial mass for the RSGs population may be as low as 7 or even 6 M⊙ and the RSG is well separated from the AGB population even at faint magnitude, making RSGs a unique population connecting the evolved massive and intermediate stars, since stars with initial mass around 6 to 8 M⊙ are thought to go through a second dredge-up to become AGBs. We encourage the interested reader to further exploit the potential of our catalog

arXiv.org: 1907.06717

Building upon our previous ATel #12224 we managed to obtain an optical spectrum of the counterpart. The full text follows:

ATel #12237; G. Maravelias (NOA), V. Antoniou (TTU/SAO), K. Boutsia (LCO), A. Zezas (UoC/SAO), A. Z. Bonanos (NOA), F. Haberl (MPE), D. Hatzidimitriou (UoA/NOA)

on 21 Nov 2018; 23:36 UT /

In ATel #12224 we reported the Hα emission, derived from a wide-field photometric survey of the Small Magellanic Cloud (Maravelias et al. 2017, IAUS 329, 373; Maravelias et al. 2019, in prep.), of the proposed optical counterpart source [M2002] 20671 to the X-ray transient XTE J0052-723 pulsar (SXP 4.78; Swift J005139.2-721704; ATel #12209). In addition to this clear detection, the work of Bonanos et al. (2010, AJ, 140, 416) showed that the IR colors of this source ([2dFS]0811; J=15.54 mag, J-[3.6]=0.56 mag) are indicative of a “photometric” Be star, defined as sources with an intrinsic color of JIRSF-[3.6]>0.5 mag.

However, to confirm the nature of the counterpart optical spectroscopy is needed. We obtained optical spectra using the LDSS-3 spectrograph on the 6.5m Clay/Magellan telescope (Las Campanas Observatory). The observations were performed on Nov. 20, 2018, acquiring two exposures of 600s each with a 1″ slit using the VPH-All grism (resulting in a 2630 — 10859 Å wavelength range, at a nominal dispersion of 1.9 Å/pix). The spectrum shows a clear single-peaked Hα line in emission, with a corresponding equivalent width of -10.65±0.14 Å. This is the first optical spectroscopic confirmation of the presence of Hα in emission. We note that Hβ appears in emission as well.

The spectral classification was based on the blue part of the spectrum and the classification scheme used in Maravelias et al. (2014, MNRAS, 438, 2005). The presence of the OII+CIII 4640-4650 blend and the strong HeI 4471 line point to an early-type star (spectral type up to B2), which is consistent with the absence of the MgII 4481 line and the weak SiII 4552 triplet line. The HeII 4200 and 4686 lines, which are indicative of B0.5 and earlier-spectral types, are absent, thus pointing to later types.

Combining these criteria we constrain the optical classification to a B1-2e source (with an error of 0.5 subtype). This is consistent with the early-type B star classification proposed in ATel #12229, as well as the previous classification of B0-B3 by Evans et al. (2004, MNRAS, 351, 601; source ID [2dFS]0811).

Thus, we provide the first optical spectrum with Hα emission of the optical counterpart of XTE J0052-723, further confirming its Be/X-ray binary nature.

The ATel #12224 was released on 17 Nov 2018 (19:01 UT) regarding the identification of the proposed optical counterpart to the source XTE J0052-723 (SXP 4.78; Swift J005139.2-721704) as an Hα emitting OB star. The full text follows.

ATel #12224; G. Maravelias (NOA), V. Antoniou (TTU/SAO), A. Zezas (UoC/SAO), A. Strantzalis (UoA), D. Hatzidimitriou (UoA), F. Haberl (MPE)

on 17 Nov 2018; 19:01 UT /

ATel #12209 reported the detection of a new X-ray transient in the Small Magellanic Cloud (SMC), Swift J005139.2-721704, exhibiting outbursting activity. The system has been classified as a new SMC high-mass X-ray binary based on its identification with the B-type star [M2002]20671. NICER followed up this source immediately (ATel #12219), reporting an absorption-corrected luminosity of LX ~7×1037erg s-1 (0.5-8 keV; 60 kpc). Temporal analysis of NICER and Fermi/GBM observations (ATel #12222) identified Swift J005139.2-721704 with the known X-ray pulsar XTE J0052-723 (SXP 4.78). Evans et al. (2004, MNRAS, 353, 601) obtained a refined B0-3(III) spectral type for [M2002]20671 (= [2dFS]0811) based on optical spectroscopy, but they do not report Hα emission.

Here, we report the identification of the SMC star [M2002]20671, and thus XTE J0052-723, with an Hα emitting source, which confirms XTE J0052-723 as a Be/X-ray binary (Be-XRB) pulsar in the SMC. This source is identified in Hα and R-band observations covering the SMC almost completely (Maravelias et al. 2017, IAUS 329, 373) using the Wide Field Imager on the 2.2m MPG/ESO telescope at La Silla (16/17 November 2011) and the MOSAIC-II camera on the 4m Blanco telescope at Cerro Tololo (15/16 December 2011).

The Hα emitting source is found at RA=00:51:38.78 and DEC=-72:17:04.7 (better than 0.2″ relative astrometry with respect to the 2MASS catalog). It is located 2.2″ away from the Swift position (ATel #12209), with Hα and R-band magnitudes equal to 15.476±0.006 and 15.613±0.008, respectively. The resulting Hα-R color is -0.137±0.010 mag with an SNR~13 above the continuum and an Hα excess significance of ~6σ above the Hα-R baseline value. The only nearby source with significant Hα-R excess is much fainter (Hα and R ~22 mag), has a lower SNR (~4) and is located at a larger distance from the X-ray source (~6″).

Observations with the IMACS f/2 camera on the 6.5m Magellan Telescope (4 October 2004) give B=15.652±0.009 mag and I=15.524±0.017 mag (Strantzalis et al. 2018, IAUS 344, 453; Strantzalis et al. 2019, in prep.), compatible with an OB star.

All the identifications described above secure the nature of Swift J005139.2-721704 = XTE J0052-723 = SXP 4.78 as Be-XRB pulsar in the SMC.

The distribution and ages of star clusters in the Small Magellanic Cloud: Constraints on the interaction history of the Magellanic Clouds

T. Bitsakis, R. A. Gonzalez-Lopezlira, P. Bonfini, G. Bruzual, G. Maravelias, D. Zaritsky, S. Charlot, V. H. Ramirez-Siordia

We present a new study of the spatial distribution and ages of the star clusters in the Small Magellanic Cloud (SMC). To detect and estimate the ages of the star clusters we rely on the new fully-automated method developed by Bitsakis et al. (2017). Our code detects 1319 star clusters in the central 18 deg2 of the SMC we surveyed (1108 of which have never been reported before). The age distribution of those clusters suggests enhanced cluster formation around 240 Myr ago. It also implies significant differences in the cluster distribution of the bar with respect to the rest of the galaxy, with the younger clusters being predominantly located in the bar. Having used the same set-up, and data from the same surveys as for our previous study of the LMC, we are able to robustly compare the cluster properties between the two galaxies. Our results suggest that the bulk of the clusters in both galaxies were formed approximately 300 Myr ago, probably during a direct collision between the two galaxies. On the other hand, the locations of the young (≤50 Myr) clusters in both Magellanic Clouds, found where their bars join the HI arms, suggest that cluster formation in those regions is a result of internal dynamical processes. Finally, we discuss the potential causes of the apparent outside-in quenching of cluster formation that we observe in the SMC. Our findings are consistent with an evolutionary scheme where the interactions between the Magellanic Clouds constitute the major mechanism driving their overall evolution.

2018 ApJ, 853, 104 / NASA/ADS / arXiv: 1712.04974

This is a follow-up paper from the initial work on the Large Magellanic Cloud.

Optical spectra of 5 new Be/X-ray Binaries in the Small Magellanic Cloud and the link of the supergiant B[e] star LHA 115-S 18 with an X-ray source

Grigoris Maravelias, Andreas Zezas, Vallia Antoniou, Despoina Hatzidimitriou

The Small Magellanic Cloud (SMC) is well known to harbor a large number of High-Mass X-ray Binaries (HMXBs). The identification of their optical counterparts provides information on the nature of the donor stars and can help to constrain the parameters of these systems and their evolution. We obtained optical spectra for a number of HMXBs identified in previous Chandra and XMM-Newton surveys of the SMC using the AAOmega/2dF fiber-fed spectrograph at the Anglo-Australian Telescope. We find 5 new Be/X-ray binaries (BeXRBs; including a tentative one), by identifying the spectral type of their optical counterparts, and we confirm the spectral classification of an additional 15 known BeXRBs. We compared the spectral types, orbital periods, and eccentricities of the BeXRB populations in the SMC and the Milky Way and we find marginal evidence for difference between the spectral type distributions, but no statistically significant differences for the orbital periods and the eccentricities. Moreover, our search revealed that the well known supergiant B[e] star LHA 115-S 18 (or AzV 154) is associated with the weak X-ray source CXOU J005409.57-724143.5. We provide evidence that the supergiant star LHA 115-S 18 is the optical counterpart of the X-ray source, and we discuss different possibilities of the origin of its low X-ray luminosity (Lx ~ 4 x 10^33 erg/s).

arXiv:1312.0593