The research of this group led by Michaela Kraus can be characterised by its dominant focus on studies of massive hot stars. More specifically, the long-term almost exclusive focus on Be and shell stars in binary systems was successfully extended to studies of hot massive stars at their different evolutionary stages, which now represent the main research topics of the group.
The research includes studies of luminous, hot massive B‑ and O‑type stars, and massive stars in transition phases, i.e., Wolf-Rayet (WR) stars, Luminous Blue Variables (LBVs), Blue Supergiants (BSGs), B[e] supergiants (B[e]SGs), Yellow Hypergiants (YHGs), and Red Supergiants (RSGs). The studied objects can be either single or in binary or multiple systems. Furthermore, the group is involved in observational and theoretical investigations of the chemistry and dynamics of the circumstellar material of evolved massive stars.
The research of massive stars is complemented by studies of low-mass stars in late evolutionary stages, namely white dwarfs, subdwarfs, cataclysmic variables, and recently also RR Lyrae stars. Theoretical studies in modelling stellar atmospheres with a natural focus on hot massive stars are also a part of the group's research. These studies include full NLTE (i.e. without the assumption of the local thermodynamic equilibrium) model atmospheres as well as NLTE models of stellar winds.
The group is also involved in astroinformatics research in order to develop new methods and tools to deal with the exponentially increasing amount of data in astronomy.
The research topics of the group are:
Stellar atmospheres, stellar winds, and their modelling
Stellar atmospheres, stellar winds, and their modelling
Theoretical studies in this research field are mainly targeted to development of sophisticated codes for stellar atmospheres and wind modelling and investigations of physical mechanisms which govern different processes in stars and their surroundings. One of the main goals of the theoretical study of the research led by Jiří Kubát is to provide improved mass-loss rates of massive hot stars using their own developed sophisticated stellar atmosphere (ATA code) and wind codes including 3‑D phenomena (such as non-sphericity and wind inhomogeneities, i.e., wind clumping).
Furthermore, research activities are focused on development of codes which are able to calculate emergent spectra in different wavebands and which can be directly compared with observations. Based on such comparison reliable values of stellar and wind parameters can be derived, in particular the mass-loss rates of massive stars in different evolutionary phases and different metallicity. The proper value of mass-loss rate is one of the main ingredients for stellar evolution modelling.
In addition to developing their own codes, the group members are also experienced in using similar stellar atmospheres and wind codes (e.g., TLUSTY, SYNSPEC, PoWR, and CMFGEN) as well as the stellar evolution codes (e.g., MESA) for quantitative stellar spectroscopy and analysing different types of stars.
New mass-loss rates of B supergiants from global wind models, Krtička J.; Kubát J.; Krtičková I.; 2020, Astron. Astrophys, submitted
Low-metallicity massive single stars with rotation. II Predicting spectra and spectral classes of TWUIN stars, Kubátová, B.; Szícsi, D.; Sander, A.A.C.; Kubát, J.; Tramper, F.; Krtička, J.; Kehrig, C.; Hamann, W.-R.; Hainich, R.; Shenar, T.; Astron. Astrophys., 2019, 623, A8
Global hot star wind models for stars from Magellanic Clouds, Krtička J.; Kubát J., 2018, Astron. Astrophys. 612, A20
Comoving frame models of hot star winds II. Reduction of O star wind mass-loss rates in global models, Krtička J.; Kubát J., 2017, Astron. Astrophys. 606, A31
Stellar wind models of subluminous hot stars ,Krtička, J.; Kubát, J.; Krtičková, I., 2016, Astron. Astrophys. 593, A101
X-ray irradiation of the winds in binaries with massive components, Krtička, J.; Kubát, J.; Krtičková, I., 2015, Astron. Astrophys. 579, A111
Macroclumping as solution of the discrepancy between H α and P v mass loss diagnostics for O-type stars, Šurlan, B.; Hamann, W.-R.; Aret, A.; Kubát, J.; Oskinova, L. M.; Torres, A. F.; 2013, Astron. Astrophys, 559, A130
Three-dimensional radiative transfer in clumped hot star winds. I. Influence of clumping on the resonance line formation, Šurlan, B.; Hamann, W.-R.; Kubát, J.; Oskinova, L. M.; Felmeier, A.; 2012, Astron. Astrophys, 541, A37
Spherically symmetric NLTE model atmospheres of hot hydrogen-helium first stars", Kubát J.; 2012, Astrophys. J. Suppl. Ser., 203, 20
NLTE models of line-driven stellar winds I. Method of calculation and first results for O stars, Krtička J.; Kubát J.; 2004, Astron. Astrophys. 417, 1003-1016
Massive stars in short-lived transition phases
One more expertise of the group is the research of massive stars in short-lived transition phases. These phases are divided into several stellar classes: WR stars, LBVs, BSGs, B[e]SGs, YHGs, and RSGs. During all these phases, the stars display signs for highly dynamic atmospheres and envelopes, and expel large amount of material, often in a series of eruptions. The ejected material accumulates in either circumstellar disks, shells, unipolar, bipolar or multi-polar nebulae.
The research of massive stars in transition phases led by Michaela Kraus is focused on developing suitable methods to derive mass-loss values of these types of stars and to investigate the chemical evolution, structure and dynamics of the ejected material. The knowledge of the amount of mass a star loses within each phase of its life is of utmost importance for reliable predictions of the evolution and final fate of massive stars.
Moreover, members of the group investigate physical mechanism(s) that can lead to enhanced mass-loss and trigger eruptions, as well as they analyse the chemical composition, the 3‑D structure and dynamics of ejecta to uncover the mass-loss history of massive stars in transition.
The group combines results from theoretical models with information derived from observations. Optical, infrared and radio data are collected from 2‑ to 12‑m telescopes, utilizing facilities at GEMINI North and South, ESO's Very Large Telescopes, APEX Telescope, Nordic Optical Telescope, Gran Telescopio de Canarias, Southern African Large Telescope, 2.2‑m MPI Telescope, 2.15‑m CASLEO Telescope, and the Perek 2‑m telescope. These data are supplemented with images from space missions such as the Spitzer Space Telescope, the Wide-field Infrared Survey Explorer, as well as with photometric data and light curves from various ground-based surveys (e.g., AAVSO, ASAS).
A Census of B[e] Supergiants, Kraus, M.; 2019, Galaxies, 7, 83
A new outburst of the yellow hypergiant star ρ Cas, Kraus, M.; Kolka, I.; Aret, A.; Nickeler, D. H.; Maravelias, G.; Eenmäe, T.; Lobel, A.; Klochkova, V. G.; 2019, MNRAS, 483, 3792-3809
On the evolutionary state of massive stars in transition phases in M33, Kourniotis, M., Kraus, M., Arias, M. L., Cidale, L., Torres, A. F.; 2018, MNRAS, 480, 3706-3717
New insights into the outflows from R Aquarii, Liimets, T.; Corradi, R. L. M.; Jones, D.; Verro, K.; Santander-García, M.; Kolka, I.; Sidonio, M.; Kankare, E.; Kankare, J.; Pursimo, T.; Wilson, P. A.; 2018, A&A, 612, A118
Wind and nebula of the M 33 variable GR 290 (WR/LBV), Maryeva, O.; Koenigsberger, G.; Egorov, O.; Rossi, C.; Polcaro, V. F.; Calabresi, M.; Viotti, R. F.; 2018, A&A, 617, A51
Resolving the circumstellar environment of the Galactic B[e] supergiant star MWC137 from large to small scales, Kraus, M., Liimets, T., Cappa, C. E., Cidale, L. S., Nickeler, D. H., Duronea, N. U., Arias, M. L., Gunawan, D. S., Oksala, M. E., Borges Fernandes, M., Maravelias, G., Curé, M., Santander-García, M.; 2017, AJ, 154, 186
On the nature of high reddening of Cygnus OB2 #12 hypergiant, Maryeva, O. V.; Chentsov, E. L.; Goranskij, V. P.; Dyachenko, V. V.; Karpov, S. V.; Malogolovets, E. V.; Rastegaev, D. A.; 2016, MNRAS, 458, 491-507
Interplay between pulsations and mass loss in the blue supergiant 55 Cygnus = HD 198478, Kraus, M., Haucke, M., Cidale, L. S., Venero, R. O. J., Nickeler, D. H., Németh, P., Niemczura, E., Tomić, S., Aret, A., Kubát, J., Kubátová, B., Oksala, M. E., Curé, M., Kamiński, K., Dimitrov, W., Fagas, M., & Polińska, M.; 2015, A&A, 581, A75
Discovery of the first B[e] supergiants in M 31, Kraus, M., Cidale, L. S., Arias, M. L., Oksala, M. E., & Borges Fernandes, M.; 2014, ApJ, 780, L10
Probing the ejecta of evolved massive stars in transition. A VLT/SINFONI K-band survey, Oksala, M. E., Kraus, M., Cidale, L. S., Muratore, M. F., & Borges Fernandes, M.; 2013, A&A, 558, A17
A Three-dimensional View of the Remnant of Nova Persei 1901 (GK Per), Liimets, T.; Corradi, R. L. M.; Santander-García, M.; Villaver, E.; Rodríguez-Gil, P.; Verro, K.; Kolka, I.; 2012, ApJ, 761, 34
Hot subdwarfs form a substantial fraction of low mass stars that experience an intermediate core helium-burning evolutionary phase before they become white dwarfs. They are at a major intersection on the evolutionary crossroad from the giant branch to the white dwarf sequence, at the hot end of the horizontal branch. These compact stars overwhelm white dwarfs in magnitude limited samples and dominate the Galactic disk populations of underluminous blue stars. Unlike white dwarfs, hot subdwarfs have more complex structures and peculiarities that require more sophisticated models, such as NLTE spectral synthesis.
The research in this area is focused on the spectroscopic investigations of hot subdwarfs using TLUSTY NLTE model atmospheres with a goal to process all available spectra and derive atmospheric parameters free of large systematics. The procedure must also include the analysis of composite binary spectra, due to the large binary fraction of hot subdwarfs. Extensions to process atmospheric chemical stratification and radiative interactions in close and compact binaries are underway. The former is important to derive an accurate luminosity function and mass distribution of hot subdwarfs, while the latter is necessary to be able to provide reliable stellar surface boundary conditions for seismic models.
The member of the group Peter Neméth started a web-service to make stellar spectral analysis and atmospheric parameter inference for hot evolved stars available to a larger community. The service is a web interface to the classical NLTE model atmosphere code TLUSTY. Even though all procedures are public and well documented, such calculations are complex tasks from theory through informatics, which require tailored expertise. With the framework provided by Astroserver this procedure can be used on a user platform to produce publication-grade results with relatively little user personal efforts. The interface is also intended to help observers to quickly process spectra, as well as students to take their first step in quantitative stellar spectroscopy and learn spectroscopy with the TLUSTY code.
Hot Subdwarf Stars Identified in Gaia DR2 with Spectra of LAMOST DR6 and DR7. II.Kinematics, Luo, Y.; Németh, P.; Li, Q.; 2020, AJ, 898, 64
Hot Subdwarf Stars Identified in Gaia DR2 with Spectra of LAMOST DR6 and DR7. I. Single-lined Spectra, Lei, Z.; Zhao, J.; Németh, P.; Zhao, G.; 2020, AJ, 889, 117
XTGRID Live: Online Spectral Analyses with TLUSTY Models, Nemeth, P.; 2019, ASP Conference Series, 519, 117
Composite hot subdwarf binaries - I. The spectroscopically confirmed sdB sample, Vos, J.; Németh, P.; Vučković, M.; Østensen, R.; Parsons, S.; 2018, MNRS, 473, 693
An unusual white dwarf star may be a surviving remnant of a subluminous Type Ia supernova, Vennes, S.; Nemeth, P.; Kawka, A.; Thorstensen, J. R.; Khalack, V.; Ferrario, L.; Alper, E. H.; 2017, Science, 357, 680
A selection of hot subluminous stars in the GALEX survey - II. Subdwarf atmospheric parameters, Németh, P.; Kawka, A.; Vennes, S.; 2012, MNRS, 427, 2180
Large data archives – Astroinformatics
The part of the group is involved in large data archives research and Astroinformatics, i.e., applications of machine learning and big data analysis in astronomy, including the Virtual Observatory (VO). This research is led by Petr Škoda, Viktor Votruba (until end of 2018), and several students from the Faculty of Information Technology of the Czech Technical University in Prague, the Faculty of Science of the Masaryk University, Brno and the Technical University in Ostrava.
The members of the group are actively involved in the preparation of new standards of the VO, mainly those focused on optical spectroscopy, and the development of new VO tools. This is organised at the national level as the Czech Virtual Observatory (CZVO) in close collaboration with the International Virtual Observatory Alliance (IVOA). The main achievements of CZVO activities are the VO-compatible archive of stellar spectra obtained with the Perek 2-m and LAMOST spectrographs and the web service VO-KOREL facilitating the Fourier disentangling of spectra in VO with the widely acknowledged procedure KOREL.
The achievements in this research area are:
Development of methods for finding Be stars using machine learning in millions of light curves, which were also incorporated in the pipeline of Gaia variability pipeline in the framework of Gaia CU7
Discovery of new emission line stars in big spectral surveys SDSS and LAMOST using deep learning and domain adaptation.
Development of cloud-based infrastructure for machine learning of astronomical spectra.
Development and implementation of standards of the IVOA, development of VO-compatible applications, setup of VO-compatible archives (Perek 2‑m telescope spectra CCD700 based on SSAP protocol), remotely controlled DK154 (Danish 1,54‑m telescope at ESO) photometry telescope archive based on SIAP, SCS, and newly developed time-series protocol.
One of the main achievements are a definition of a new IVOA standard for time series based on spare data cubes, which was presented at several IVOA Interoperability workshops and published as IVOA note, and a modification of a widely used SPLAT‑VO code for work with this standard.
Active deep learning method for the discovery of objects of interest in large spectroscopic surveys, Škoda, P.; Podsztavek, O.; Tvrdík, P.; 2020, Astron. Astrophys, 643, A122
Knowledge Discovery in Big Data from Astronomy and Earth Observation, Škoda, P.; Adam, F.; 2020, Knowledge Discovery in Big Data from Astronomy and Earth Observation, 1st Edition. Edited by Skoda P. and Fathalrahman A., Elsevier, ISBN: 9780128191545
Identification of Artifacts and Interesting Celestial Objects in the LAMOST Spectral Survey , Škoda, P.; Shakurova, K.; Koza, J.; Palička, A.; 2019, ASPCS, 521, 402
Gaia Data Release 2. Summary of the variability processing and analysis results , Holl, B.; Koubsky, P.; Votruba, V.; and 60 more co-authors; 2018, Astron. Astrophys, 618, A30
Identification of Interesting Objects in Large Spectral Surveys Using Highly Parallelized Machine Learning , Škoda, P.; Palička, A.; Koza, J.; Shakurova, K.; 2017, IAUS, 325, 180
Massively Parallel Machine Learning in the Virtual Observatory as a Key Technology in the Era of Multi-Million Spectral Surveys , Škoda, P.; 2017, ASI Conference Series, Edited by P. Coelho, L. Martins & E. Griffin, 14, 73-82
Time Series Cube Data Model, Nadvornik, J.; Škoda, P.; Morris, D.; Tvrdik, P.; 2017, IVOA Note 2017-12-15
The Distributed Cloud Based Engine for Knowledge Discovery in Massive Archives of Astronomical Spectra, Škoda, P.; Koza, J.; Palička, A.; Lopatovský, L.; Peterka, T.; 2017, ASPCS, 512, 689
Big Data Movement: A Challenge in Data Processing, Pokorný, J.; Škoda, P.; Zelinka, I.; Bednárek, D,; Zavoral, F., Kruliš, M.; Šaloun, P.; 2015, Springer Studies in Big Data, 9, 29
Spectroscopic analysis in the virtual observatory environment with SPLAT-VO , Škoda, P.; Draper, P. W.; Neves, M. C.; Andrešič, D.; Jenness, T.; 2014, Astronomy and Computing, 7, 108-120