Astronomy Archive

It was back in 2020 during the pandemic that the first call for the XShootU collaboration was sent. I had really little idea of what would follow, but I fount it definitely motivating to participate. Therefore I volunteer to help with the data reduction. After 2.5 years we are getting close to the first public release of this data. The current first (in a probable very long series of papers to follow) paper is on the project description. The second paper on data reduction will soon follow…

X-Shooting ULLYSES: massive stars at low metallicityI. Project Description

Jorick S. Vink, A. Mehner, P. A. Crowther, A. Fullerton, M. Garcia, F. Martins, N. Morrell, L.M.
Oskinova, N. St-Louis, A. ud-Doula, A.A.C. Sander, H. Sana, J.-C. Bouret, B. Kubátová, P. Marchant, L.P.
Martins, A. Wofford, J. Th. van Loon, O. Grace Telford, Y. Götberg, D.M. Bowman, C. Erba,
V.M. Kalari, M. Abdul-Masih, T. Alkousa, F. Backs, C.L. Barbosa, S.R. Berlanas, M. Bernini-Peron,
J.M. Bestenlehner, R. Blomme, J. Bodensteiner, S.A. Brands, C.J. Evans, A. David-Uraz, F.A.
Driessen, K. Dsilva, S. Geen, V.M.A.Gómez-González, L. Grassitelli, W.-R. Hamann, C. Hawcroft, A.
Herrero, E.R. Higgins, D. John Hillier, R. Ignace, A.G. Istrate, L. Kaper, N.D. Kee, C. Kehrig, Z.
Keszthelyi, J. Klencki, A. de Koter, R. Kuiper, E. Laplace, C.J.K. Larkin, R. R. Lefever, C.
Leitherer, D.J. Lennon, L. Mahy, J. Maíz Apellániz, G. Maravelias, W. Marcolino, A. F. McLeod,
S.E. de Mink, F. Najarro, M. S. Oey, T.N. Parsons, D. Pauli, M.G. Pedersen, R.K. Prinja, V.
Ramachandran, M.C. Ramírez-Tannus, G.N. Sabhahit, A. Schootemeijer, S. Reyero Serantes, T. Shenar,
G.S. Stringfellow, N. Sudnik, F. Tramper, and L. Wang

Observations of individual massive stars, super-luminous supernovae, gamma-ray bursts, and gravitational-wave events involving spectacular black-hole mergers, indicate that the low-metallicity Universe is fundamentally different from our own Galaxy. Many transient phenomena will remain enigmatic until we achieve a firm understanding of the physics and evolution of massive stars at low metallicity (Z). The Hubble Space Telescope has devoted 500 orbits to observe ∼250 massive stars at low Z in the ultraviolet (UV) with the COS and STIS spectrographs under the ULLYSES program. The complementary “X-Shooting ULLYSES” (XShootU) project provides enhanced legacy value with high-quality optical and near-infrared spectra obtained with the wide-wavelength coverage X-shooter spectrograph at ESO’s Very Large Telescope. We present an overview of the XShootU project, showing that combining ULLYSES UV and XShootU optical spectra is critical for the uniform determination of stellar parameters such as effective temperature, surface gravity, luminosity, and abundances, as well as wind properties such as mass-loss rates in function of Z. As uncertainties in stellar and wind parameters percolate into many adjacent areas of Astrophysics, the data and modelling of the XShootU project is expected to be a game-changer for our physical understanding of massive stars at low Z. To be able to confidently interpret James Webb Space Telescope (JWST) spectra of the first stellar generations, the individual spectra of low Z stars need to be understood, which is exactly where XShootU can deliver.

Fig. 6. Reduced X-shooter spectra for a range of spectral types of single-star supergiants (top) and dwarfs (bottom – not shown). For illustration purposes the flux of each spectrum was divided by its mean value and an arbitrary offset was added. The grey regions correspond to the UVB-VIS common wavelength coverage (∼ 5500 Å), a gap due to bad pixel masking (∼ 6360 Å), and telluric absorption. Minor manual treatment to remove strong cosmic rays was performed.

arXiv: 2305.06376

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)

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.

Fig. 15. Derived MLR-L relation from this work (left) and comparison of the same relation between this and previous works (right). In the left panel, the very dusty targets (τ > 1.0) are marked with red colors. In the right panel, lines of the same color are variations of the same relation. 2304.01835

Here comes the announcement of the third (already!) iteration of our Summer School for Astrostatistics in Crete!

This is an in-person meeting, as it focus on the practical use of statistics and machine learning in academic research. We will supply all the necessary guidelines through Astronomical problems.

Check the website for further information. Registration closes on March 24!

Getting observing time – as PI finally!

Posted February 17, 2023 By grigoris

Getting observing time needs both a good proposal and some … luck! Although I have been into many proposals (with some of them written by me actually) I did not have the excitement to get it as PI. The time has finally come now!!

At the current observing period of ESO (P111, running 1 April 2023 – 30 September 2023) we managed to get ~18 hours to use FORS2 to observe a set of three dwarf galaxies (IC 1613, Pegasus DIG, and Phoenix Dwarf), part of the ASSESS galaxy sample. The difference, with respect to our previous successful proposals both at ESO and GTC, is that we will use the predictions of the machine-learning classifier we developed for this project.

Now I have to work on the Phase-2 material, which consists of the preimaging OBs first, and then the mask designing (based on the images).

A proceedings paper from IAUS 366 that took place virtually back in October 2021 (for which I had another poster contribution) was finally published at the end of 2022. It summarizes a collective work led by Michaela on B[e] Supergiants and Yellow Hypergiants, two massive star phases where we observe episodic mass loss.

Environments of evolved massive stars: evidence for episodic mass ejections

M. Kraus, L. S. Cidale, M. L. Arias, A. F. Torres, I. Kolka, G. Maravelias, D. H. Nickeler, W. Glatzel and T. Liimets

The post-main sequence evolutionary path of massive stars comprises various transition phases, in which the stars shed large amounts of material into their environments. Our studies focus on two of them: B[e] supergiants and yellow hypergiants, for which we investigate the structure and dynamics within their environments. We find that each B[e] supergiant is surrounded by a unique set of rings or arc-like structures. These structures are either stable over time or they display high variability, including expansion and dilution. In contrast, yellow hypergiants are embedded in multiple shells of gas and dust. These objects are famous for their outburst activity. Moreover, the dynamics in their extended atmospheres imply an enhanced pulsation activity prior to outburst. The physical mechanism(s) leading to episodic mass ejections in these two types of stars is still uncertain. We propose that strange-mode instabilities, excited in the inflated envelopes of these objects, play a significant role.

Figure 1. Real parts (= pulsation periods, left panel) and the imaginary parts (right panel) of
the eigenfrequencies, which are normalized to the global free-fall time. Positive imaginary parts
correspond to damped modes, and negative ones to unstable modes. The computations have
been performed for T eff = 7000 K and log L/L  = 5.7, matching the observed values of ρ Cas.

IAUS 366, 2022 (NASA/ADS link)

Setting up virtual environments for Python

Posted October 6, 2022 By grigoris

The biggest issue when dealing with multiple projects is how to keep track of the various Python and other packages’ versions you are using in each project. It is not uncommon to update something and get something else broken…

The solution is virtual environments. And for these there are few options such as virtualenv and conda (among others). So far I have postponed (and not with good results) the use of environments. But finally, I took the necessary time to investigate pros and cons and make a decision. I found the following guides from WhiteBox exceptional well written and useful:

along with this great meme …

Darth Vader about conda envs (as presented in WhiteBox)

Javier Gorosabel award on pro-am collaborations

Posted October 4, 2022 By grigoris

In the latest meeting of the Spanish Astronomical Society (5-9 September, Tenerife, Spain) it was announced that our work with Emmanuel (Manos) Kardasis on Venus’ Cloud Discontinuity (published at the beginning of 2022, in the journal Atmosphere) was the winner for the 2nd iteration of the Javier Gorosabel Award on pro-am collaborations.

I am actually excited about this. But not because I am part of the award… I am excited because this award recognizes the effort put by some amateurs in order to produce not only scientifically useful images/data but document their effort, share it with both the amateur and professional communities and contribute to the advance of our knowledge by analyzing and publishing their results. I am honored that I could help Manos to achieve that. I strongly believe that it is a worthy recognition of his more than two decades of contribution in Astronomy and the community in general.

Of course, kudos to Javier – without his expertise and guidance this work wouldn’t have materialized.

The two main driving forces behind the work: Javier Peralta (left) and Manos Kardasis (right) holding the Javier Gorosabel award.

Properties of luminous red supergiant stars in the Magellanic Clouds

S. de Wit, A.Z. Bonanos, F. Tramper, M. Yang, G. Maravelias, K. Boutsia, N. Britavskiy, and E. Zapartas

There is evidence that some red supergiants (RSGs) experience short lived phases of extreme mass loss, producing copious amounts of dust. These episodic outburst phases help to strip the hydrogen envelope of evolved massive stars, drastically affecting their evolution. However, to date, the observational data of episodic mass loss is limited. This paper aims to derive surface properties of a spectroscopic sample of fourteen dusty sources in the Magellanic Clouds using the Baade telescope. These properties may be used for future spectral energy distribution fitting studies to measure the mass loss rates from present circumstellar dust expelled from the star through outbursts. We apply MARCS models to obtain the effective temperature (Teff) and extinction (AV) from the optical TiO bands. We use a χ2 routine to determine the best fit model to the obtained spectra. We compute the Teff using empirical photometric relations and compare this to our modelled Teff. We have identified a new yellow supergiant and spectroscopically confirmed eight new RSGs and one bright giant in the Magellanic Clouds. Additionally, we observed a supergiant B[e] star and found that the spectral type has changed compared to previous classifications, confirming that the spectral type is variable over decades. For the RSGs, we obtained the surface and global properties, as well as the extinction AV. Our method has picked up eight new, luminous RSGs. Despite selecting dusty RSGs, we find values for AV that are not as high as expected given the circumstellar extinction of these evolved stars. The most remarkable object from the sample, LMC3, is an extremely massive and luminous evolved massive star and may be grouped amongst the largest and most luminous RSGs known in the Large Magellanic Cloud (log(L∗/L⊙)∼5.5 and R=1400 R⊙).

Fig. 9: Top: HRD indicating the locations of our LMC targets with inverted red triangles. The Teff for all data points was derived through the TiO method. Smaller light grey squares and stars are objects from Levesque et al. (2006) and Davies et al. (2013), respectively. For the two outliers we have extended the uncertainty assuming a shift of 0.3 mag in the K−band (dotted vertical error bar) instead of only the propagated uncertainty, to visualize the effect of intrinsic variability. The colour map represents the central 12C mass fraction, while the nodes on the track again indicate a step of 104 years

arXiv: 2209.11239

This is actually a preview of what will follow after the first paper of the machine-learning classifier. We put it into action to get predictions for a number of galaxies and we start exploring the results. Of more interest is the fractions of the populations with metallicity, although a more detailed study is needed to take care of all caveats.

Using machine learning to investigate the populations of dusty evolved stars in various metallicities

Grigoris Maravelias, Alceste Z. Bonanos, Frank Tramper, Stephan de Wit, Ming Yang, Paolo Bonfini, Emmanuel Zapartas, Konstantinos Antoniadis, Evangelia Christodoulou, Gonzalo Muñoz-Sanchez

Mass loss is a key property to understand stellar evolution and in particular for low-metallicity environments. Our knowledge has improved dramatically over the last decades both for single and binary evolutionary models. However, episodic mass loss although definitely present observationally, is not included in the models, while its role is currently undetermined. A major hindrance is the lack of large enough samples of classified stars. We attempted to address this by applying an ensemble machine-learning approach using color indices (from IR/Spitzer and optical/Pan-STARRS photometry) as features and combining the probabilities from three different algorithms. We trained on M31 and M33 sources with known spectral classification, which we grouped into Blue/Yellow/Red/B[e] Supergiants, Luminous Blue Variables, classical Wolf-Rayet and background galaxies/AGNs. We then applied the classifier to about one million Spitzer point sources from 25 nearby galaxies, spanning a range of metallicites (1/15 to ∼3 Z⊙). Equipped with spectral classifications we investigated the occurrence of these populations with metallicity.

The fractions, of the predicted class members over the total sample size for each galaxy, with metallicity.

arXiv: 2209.06303

JWST is alive and … so do we!

Posted July 12, 2022 By grigoris

JWST delivered its first images (publicly) today! That was the best news to get as an astronomer for two reasons. The one is of course the scientific reasons, as it is one of the most important telescopes sent to space and perhaps the most challenging mission to launch and deploy at that distance (L1). There should have been already tens (or hundreds ??) of articles with respect to this part.

However, there is another important reason. Everything went finally smooth and we have a working telescope. That means that Astronomy will not dismay! Imagine if all this effort and funding of 10 billion dollars would fail… I cannot and I do not want to! Thankfully this did not happen and hopefully this will motivate more funding towards Astronomy that should be reflected to jobs also….

So let’s enjoy and cheer about this new era in Astronomy!

Webb’s First Deep Field, the image of galaxy cluster SMACS 0723 (Credit: NASA)