Gal Matijevic
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Gal Matijevic has a total of 87 co-authors. Here are the top co-authors by number of shared publications:
Albert Bijaoui
4 shared publicationsAlejandra Recio-Blanco
4 shared publicationsAlessandro Siviero
4 shared publications- Amina Helmi
Kapteyn Astronomical Institute, University of Groningen
4 shared publications - Andrea Kunder
Saint Martin’s University, 5000 Abbey Way SE, Lacey, WA 98503, USA
4 shared publications - Andreas Just
Zentrum für Astronomie der Universität Heidelberg, Astronomisches Rechen-Institut
4 shared publications
Latest Publications
- 1 January 2021
- Published by American Astronomical Society in The Astrophysical Journal
- Vol. 907 (1) , 54
Classification of High-resolution Solar Hα Spectra Using t-distributed Stochastic Neighbor Embedding
The Hα spectral line is a well-studied absorption line revealing properties of the highly structured and dynamic solar chromosphere. Typical features with distinct spectral signatures in Hα include filaments and prominences, bright active-region plages, superpenumbrae around sunspots, surges, flares, Ellerman bombs, filigree, and mottles and rosettes, among others. This study is based on high-spectral resolution Hα spectra obtained with the Echelle spectrograph of the Vacuum Tower Telescope (VTT) located at Observatorio del Teide, Tenerife, Spain. The t-distributed stochastic neighbor embedding (t-SNE) is a machine-learning algorithm, which is used for nonlinear dimensionality reduction. In this application, it projects Hα spectra onto a two-dimensional map, where it becomes possible to classify the spectra according to results of cloud model (CM) inversions. The CM parameters optical depth, Doppler width, line-of-sight velocity, and source function describe properties of the cloud material. Initial results of t-SNE indicate its strong discriminatory power to separate quiet-Sun and plage profiles from those that are suitable for CM inversions. In addition, a detailed study of various t-SNE parameters is conducted, the impact of seeing conditions on the classification is assessed, results for various types of input data are compared, and the identified clusters are linked to chromospheric features. Although t-SNE proves to be efficient in clustering high-dimensional data, human inference is required at each step to interpret the results. This exploratory study provides a framework and ideas on how to tailor a classification scheme toward specific spectral data and science questions.
- 1 January 2021
- Published by American Astronomical Society in The Astrophysical Journal
- Vol. 907 (1) , 54
Classification of High-resolution Solar Hα Spectra Using t-distributed Stochastic Neighbor Embedding
The Hα spectral line is a well-studied absorption line revealing properties of the highly structured and dynamic solar chromosphere. Typical features with distinct spectral signatures in Hα include filaments and prominences, bright active-region plages, superpenumbrae around sunspots, surges, flares, Ellerman bombs, filigree, and mottles and rosettes, among others. This study is based on high-spectral resolution Hα spectra obtained with the Echelle spectrograph of the Vacuum Tower Telescope (VTT) located at Observatorio del Teide, Tenerife, Spain. The t-distributed stochastic neighbor embedding (t-SNE) is a machine-learning algorithm, which is used for nonlinear dimensionality reduction. In this application, it projects Hα spectra onto a two-dimensional map, where it becomes possible to classify the spectra according to results of cloud model (CM) inversions. The CM parameters optical depth, Doppler width, line-of-sight velocity, and source function describe properties of the cloud material. Initial results of t-SNE indicate its strong discriminatory power to separate quiet-Sun and plage profiles from those that are suitable for CM inversions. In addition, a detailed study of various t-SNE parameters is conducted, the impact of seeing conditions on the classification is assessed, results for various types of input data are compared, and the identified clusters are linked to chromospheric features. Although t-SNE proves to be efficient in clustering high-dimensional data, human inference is required at each step to interpret the results. This exploratory study provides a framework and ideas on how to tailor a classification scheme toward specific spectral data and science questions.
- 27 July 2020
- Published by American Astronomical Society in The Astronomical Journal
- Vol. 160 (2) , 82
The Sixth Data Release of the Radial Velocity Experiment (RAVE). I. Survey Description, Spectra, and Radial Velocities
The Radial Velocity Experiment (Rave) is a magnitude-limited (9 < I < 12) spectroscopic survey of Galactic stars randomly selected in Earth’s southern hemisphere. The Rave medium-resolution spectra (R ∼ 7500) cover the Ca-triplet region (8410–8795 Å). The sixth and final data release (DR6) is based on 518,387 observations of 451,783 unique stars. Rave observations were taken between 2003 April 12 and 2013 April 4. Here we present the genesis, setup, and data reduction of Rave as well as wavelength-calibrated and flux-normalized spectra and error spectra for all observations in Rave DR6. Furthermore, we present derived spectral classification and radial velocities for the Rave targets, complemented by cross-matches with Gaia DR2 and other relevant catalogs. A comparison between internal error estimates, variances derived from stars with more than one observing epoch, and a comparison with radial velocities of Gaia DR2 reveals consistently that 68% of the objects have a velocity accuracy better than 1.4 km s–1, while 95% of the objects have radial velocities better than 4.0 km s–1. Stellar atmospheric parameters, abundances and distances are presented in a subsequent publication. The data can be accessed via the Rave website (http://rave-survey.org) or the Vizier database.
- 27 July 2020
- Published by American Astronomical Society in The Astronomical Journal
- Vol. 160 (2) , 82
The Sixth Data Release of the Radial Velocity Experiment (RAVE). I. Survey Description, Spectra, and Radial Velocities
The Radial Velocity Experiment (Rave) is a magnitude-limited (9 < I < 12) spectroscopic survey of Galactic stars randomly selected in Earth’s southern hemisphere. The Rave medium-resolution spectra (R ∼ 7500) cover the Ca-triplet region (8410–8795 Å). The sixth and final data release (DR6) is based on 518,387 observations of 451,783 unique stars. Rave observations were taken between 2003 April 12 and 2013 April 4. Here we present the genesis, setup, and data reduction of Rave as well as wavelength-calibrated and flux-normalized spectra and error spectra for all observations in Rave DR6. Furthermore, we present derived spectral classification and radial velocities for the Rave targets, complemented by cross-matches with Gaia DR2 and other relevant catalogs. A comparison between internal error estimates, variances derived from stars with more than one observing epoch, and a comparison with radial velocities of Gaia DR2 reveals consistently that 68% of the objects have a velocity accuracy better than 1.4 km s–1, while 95% of the objects have radial velocities better than 4.0 km s–1. Stellar atmospheric parameters, abundances and distances are presented in a subsequent publication. The data can be accessed via the Rave website (http://rave-survey.org) or the Vizier database.
- 27 July 2020
- Published by American Astronomical Society in The Astronomical Journal
- Vol. 160 (2) , 83
The Sixth Data Release of the Radial Velocity Experiment (Rave). II. Stellar Atmospheric Parameters, Chemical Abundances, and Distances
We present part 2 of the sixth and final Data Release (DR6) of the Radial Velocity Experiment (Rave), a magnitude-limited ( ) spectroscopic survey of Galactic stars randomly selected in Earth’s southern hemisphere. The Rave medium-resolution spectra (R ∼ 7500) cover the Ca triplet region (8410–8795 Å) and span the complete time frame from the start of Rave observations on 2003 April 12 to their completion on 2013 April 4. In the second of two publications, we present the data products derived from 518,387 observations of 451,783 unique stars using a suite of advanced reduction pipelines focusing on stellar atmospheric parameters, in particular purely spectroscopically derived stellar atmospheric parameters ( , , and the overall metallicity), enhanced stellar atmospheric parameters inferred via a Bayesian pipeline using Gaia DR2 astrometric priors, and asteroseismically calibrated stellar atmospheric parameters for giant stars based on asteroseismic observations for 699 K2 stars. In addition, we provide abundances of the elements Fe, Al, and Ni, as well as an overall [α/Fe] ratio obtained using a new pipeline based on the GAUGUIN optimization method that is able to deal with variable signal-to-noise ratios. The Rave DR6 catalogs are cross-matched with relevant astrometric and photometric catalogs, and are complemented by orbital parameters and effective temperatures based on the infrared flux method. The data can be accessed via the Rave website (http://rave-survey.org) or the Vizier database.
- 27 July 2020
- Published by American Astronomical Society in The Astronomical Journal
- Vol. 160 (2) , 83
The Sixth Data Release of the Radial Velocity Experiment (Rave). II. Stellar Atmospheric Parameters, Chemical Abundances, and Distances
We present part 2 of the sixth and final Data Release (DR6) of the Radial Velocity Experiment (Rave), a magnitude-limited ( ) spectroscopic survey of Galactic stars randomly selected in Earth’s southern hemisphere. The Rave medium-resolution spectra (R ∼ 7500) cover the Ca triplet region (8410–8795 Å) and span the complete time frame from the start of Rave observations on 2003 April 12 to their completion on 2013 April 4. In the second of two publications, we present the data products derived from 518,387 observations of 451,783 unique stars using a suite of advanced reduction pipelines focusing on stellar atmospheric parameters, in particular purely spectroscopically derived stellar atmospheric parameters ( , , and the overall metallicity), enhanced stellar atmospheric parameters inferred via a Bayesian pipeline using Gaia DR2 astrometric priors, and asteroseismically calibrated stellar atmospheric parameters for giant stars based on asteroseismic observations for 699 K2 stars. In addition, we provide abundances of the elements Fe, Al, and Ni, as well as an overall [α/Fe] ratio obtained using a new pipeline based on the GAUGUIN optimization method that is able to deal with variable signal-to-noise ratios. The Rave DR6 catalogs are cross-matched with relevant astrometric and photometric catalogs, and are complemented by orbital parameters and effective temperatures based on the infrared flux method. The data can be accessed via the Rave website (http://rave-survey.org) or the Vizier database.
- Open Access
The Sixth Data Release of the Radial Velocity Experiment (RAVE) -- II: Stellar Atmospheric Parameters, Chemical Abundances and Distances
We present part 2 of the 6th and final Data Release (DR6 or FDR) of the Radial Velocity Experiment (RAVE), a magnitude-limited (9<I<12) spectroscopic survey of Galactic stars randomly selected in the southern hemisphere. The RAVE medium-resolution spectra (R~7500) cover the Ca-triplet region (8410-8795A) and span the complete time frame from the start of RAVE observations on 12 April 2003 to their completion on 4 April 2013. In the second of two publications, we present the data products derived from 518,387 observations of 451,783 unique stars using a suite of advanced reduction pipelines focussing on stellar atmospheric parameters, in particular purely spectroscopically derived stellar atmospheric parameters (Teff, logg, and the overall metallicity), enhanced stellar parameters inferred via a Bayesian pipeline using Gaia DR2 astrometric priors, and asteroseismically calibrated stellar parameters for giant stars based on asteroseismic observations for 699 K2 stars. In addition, we provide abundances of the elements Fe, Al, and Ni, as well as an overall [alpha/Fe] ratio obtained using a new pipeline based on the GAUGUIN optimization method that is able to deal with variable signal-to-noise ratios. The RAVE DR6 catalogs are cross matched with relevant astrometric and photometric catalogs, and are complemented by orbital parameters and effective temperatures based on the infrared flux method. The data can be accessed via the RAVE Web site (http://rave-survey.org) or the Vizier database.
Open AccessThe Sixth Data Release of the Radial Velocity Experiment (RAVE) -- II: Stellar Atmospheric Parameters, Chemical Abundances and Distances
We present part 2 of the 6th and final Data Release (DR6 or FDR) of the Radial Velocity Experiment (RAVE), a magnitude-limited (9<I<12) spectroscopic survey of Galactic stars randomly selected in the southern hemisphere. The RAVE medium-resolution spectra (R~7500) cover the Ca-triplet region (8410-8795A) and span the complete time frame from the start of RAVE observations on 12 April 2003 to their completion on 4 April 2013. In the second of two publications, we present the data products derived from 518,387 observations of 451,783 unique stars using a suite of advanced reduction pipelines focussing on stellar atmospheric parameters, in particular purely spectroscopically derived stellar atmospheric parameters (Teff, logg, and the overall metallicity), enhanced stellar parameters inferred via a Bayesian pipeline using Gaia DR2 astrometric priors, and asteroseismically calibrated stellar parameters for giant stars based on asteroseismic observations for 699 K2 stars. In addition, we provide abundances of the elements Fe, Al, and Ni, as well as an overall [alpha/Fe] ratio obtained using a new pipeline based on the GAUGUIN optimization method that is able to deal with variable signal-to-noise ratios. The RAVE DR6 catalogs are cross matched with relevant astrometric and photometric catalogs, and are complemented by orbital parameters and effective temperatures based on the infrared flux method. The data can be accessed via the RAVE Web site (http://rave-survey.org) or the Vizier database.
- Open Access
The Sixth Data Release of the Radial Velocity Experiment (RAVE) -- I: Survey Description, Spectra and Radial Velocities
We present part 1 of the 6th and final Data Release (DR6 or FDR) of the Radial Velocity Experiment (RAVE), a magnitude-limited (9<I<12) spectroscopic survey of Galactic stars randomly selected in the southern hemisphere. The RAVE medium-resolution spectra (R~7500) cover the Ca-triplet region (8410-8795A) and span the complete time frame from the start of RAVE observations on 12 April 2003 to their completion on 4 April 2013. Wavelength-calibrated and flux-normalized spectra for 518,387 observations of 451,783 unique stars are presented. The final data release presented in this publication consists of spectra, error spectra, spectral classification, derived radial velocities, and cross matches with other relevant catalogs. The data can be accessed via the RAVE Web site (http://rave-survey.org) or the Vizier database.
Open AccessThe Sixth Data Release of the Radial Velocity Experiment (RAVE) -- I: Survey Description, Spectra and Radial Velocities
We present part 1 of the 6th and final Data Release (DR6 or FDR) of the Radial Velocity Experiment (RAVE), a magnitude-limited (9<I<12) spectroscopic survey of Galactic stars randomly selected in the southern hemisphere. The RAVE medium-resolution spectra (R~7500) cover the Ca-triplet region (8410-8795A) and span the complete time frame from the start of RAVE observations on 12 April 2003 to their completion on 4 April 2013. Wavelength-calibrated and flux-normalized spectra for 518,387 observations of 451,783 unique stars are presented. The final data release presented in this publication consists of spectra, error spectra, spectral classification, derived radial velocities, and cross matches with other relevant catalogs. The data can be accessed via the RAVE Web site (http://rave-survey.org) or the Vizier database.
- Open Access
- 1 August 2018
- Published by Cambridge University Press (CUP) in Proceedings of the International Astronomical Union
- Vol. 14 (S344) , 130-133
VMC proper motions of the Magellanic Bridge
Dwarf galaxies enable us to study early phases of galaxy evolution and are key to many open questions about the hierarchical structure of the Universe. The Large and Small Magellanic Cloud (LMC and SMC) are the most luminous dwarf galaxy satellites of the Milky Way (MW). They are most likely gravitationally bound to each other, and their last interaction occurred about 200 Myr ago. Also, they are in an early phase of minor merging with the MW and will impact the Galactic structure in the future because of their relatively large mass. However, there are still major uncertainties regarding their origin and their interactions with one another and with the Milky Way. We cross-correlated the VMC and Gaia DR2 data to select a sample of stars that likely belong to the Magellanic Bridge, a feature formed of gas and stars which is connecting the LMC and the SMC. We removed potential MW foregound stars using a combination of parallax and colour-magnitude criteria and calculated the proper motions of the Bridge member stars. Our analysis supports a motion of star towards the LMC, which was found to be in good agreement with a dynamical simulation, of the SMC being stripped by the LMC.
- 1 August 2018
- Published by Cambridge University Press (CUP) in Proceedings of the International Astronomical Union
- Vol. 14 (S344) , 130-133
Open AccessVMC proper motions of the Magellanic Bridge
Dwarf galaxies enable us to study early phases of galaxy evolution and are key to many open questions about the hierarchical structure of the Universe. The Large and Small Magellanic Cloud (LMC and SMC) are the most luminous dwarf galaxy satellites of the Milky Way (MW). They are most likely gravitationally bound to each other, and their last interaction occurred about 200 Myr ago. Also, they are in an early phase of minor merging with the MW and will impact the Galactic structure in the future because of their relatively large mass. However, there are still major uncertainties regarding their origin and their interactions with one another and with the Milky Way. We cross-correlated the VMC and Gaia DR2 data to select a sample of stars that likely belong to the Magellanic Bridge, a feature formed of gas and stars which is connecting the LMC and the SMC. We removed potential MW foregound stars using a combination of parallax and colour-magnitude criteria and calculated the proper motions of the Bridge member stars. Our analysis supports a motion of star towards the LMC, which was found to be in good agreement with a dynamical simulation, of the SMC being stripped by the LMC.