Astronomy in Ukraine

The current and prospective status of astronomical research in Ukraine is discussed. A brief history of astronomical research in Ukraine is presented and the system organizing scientific activity is described, including astronomy education, institutions and staff, awarding higher degrees/titles, government involvement, budgetary investments and international cooperation. Individuals contributing significantly to the field of astronomy and their accomplishments are mentioned. Major astronomical facilities, their capabilities, and their instrumentation are described. In terms of the number of institutions and personnel engaged in astronomy, and of past accomplishments, Ukraine ranks among major nations of Europe. Current difficulties associated with political, economic and technological changes are addressed and goals for future research activities presented.Comment: Paper to be published in ``Organizations and Strategies in Astronomy'' -- Vol. 7, Ed. A. Heck, 2006, Springer, Dordrecht; 25 pages, 2 figs, 2 table

Machine learning technique for morphological classification of galaxies at z<0.1 from the SDSS

Methods. We used different galaxy classification techniques: human labeling, multi-photometry diagrams, Naive Bayes, Logistic Regression, Support Vector Machine, Random Forest, k-Nearest Neighbors, and k-fold validation. Results. We present results of a binary automated morphological classification of galaxies conducted by human labeling, multiphotometry, and supervised Machine Learning methods. We applied its to the sample of galaxies from the SDSS DR9 with redshifts of 0.02 < z < 0.1 and absolute stellar magnitudes of 24m < Mr < 19.4m. To study the classifier, we used absolute magnitudes: Mu, Mg, Mr , Mi, Mz, Mu-Mr , Mg-Mi, Mu-Mg, Mr-Mz, and inverse concentration index to the center R50/R90. Using the Support vector machine classifier and the data on color indices, absolute magnitudes, inverse concentration index of galaxies with visual morphological types, we were able to classify 316 031 galaxies from the SDSS DR9 with unknown morphological types. Conclusions. The methods of Support Vector Machine and Random Forest with Scikit-learn machine learning in Python provide the highest accuracy for the binary galaxy morphological classification: 96.4% correctly classified (96.1% early E and 96.9% late L types) and 95.5% correctly classified (96.7% early E and 92.8% late L types), respectively. Applying the Support Vector Machine for the sample of 316 031 galaxies from the SDSS DR9 at z < 0.1, we found 141 211 E and 174 820 L types among them.Comment: 10 pages, 5 figures. The presentation of these results was given during the EWASS-2017, Symposium "Astroinformatics: From Big Data to Understanding the Universe at Large". It is vailable through \url{http://space.asu.cas.cz/~ewass17-soc/Presentations/S14/Dobrycheva_987.pdf

Magnetic properties of vanadium-oxide nanotubes probed by static magnetization and {51}V NMR

Measurements of the static magnetic susceptibility and of the nuclear magnetic resonance of multiwalled vanadium-oxide nanotubes are reported. In this nanoscale magnet the structural low-dimensionality and mixed valency of vanadium ions yield a complex temperature dependence of the static magnetization and the nuclear relaxation rates. Analysis of the different contributions to the magnetism allows to identify individual interlayer magnetic sites as well as strongly antiferromagnetically coupled vanadium spins (S = 1/2) in the double layers of the nanotube's wall. In particular, the data give strong indications that in the structurally well-defined vanadium-spin chains in the walls, owing to an inhomogeneous charge distribution, antiferromagnetic dimers and trimers occur. Altogether, about 30% of the vanadium ions are coupled in dimers, exhibiting a spin gap of the order of 700 K, the other ~ 30% comprise individual spins and trimers, whereas the remaining \~ 40% are nonmagnetic.Comment: revised versio

High temperature ferromagnetism of Li-doped vanadium oxide nanotubes

The nature of a puzzling high temperature ferromagnetism of doped mixed-valent vanadium oxide nanotubes reported earlier by Krusin-Elbaum et al., Nature 431 (2004) 672, has been addressed by static magnetization, muon spin relaxation, nuclear magnetic and electron spin resonance spectroscopy techniques. A precise control of the charge doping was achieved by electrochemical Li intercalation. We find that it provides excess electrons, thereby increasing the number of interacting magnetic vanadium sites, and, at a certain doping level, yields a ferromagnetic-like response persisting up to room temperature. Thus we confirm the surprising previous results on the samples prepared by a completely different intercalation method. Moreover our spectroscopic data provide first ample evidence for the bulk nature of the effect. In particular, they enable a conclusion that the Li nucleates superparamagnetic nanosize spin clusters around the intercalation site which are responsible for the unusual high temperature ferromagnetism of vanadium oxide nanotubes.Comment: with some amendments published in Europhysics Letters (EPL) 88 (2009) 57002; http://epljournal.edpsciences.or