Astronomical catalogues and databases
Course: Astrophysics
Structural unit: Faculty of Physics
Title
Astronomical catalogues and databases
Code
OK10
Module type
Обов’язкова дисципліна для ОП
Educational cycle
Second
Year of study when the component is delivered
2023/2024
Semester/trimester when the component is delivered
1 Semester
Number of ECTS credits allocated
3
Learning outcomes
obtaining deep and systematic knowledge of methods and instruments for research using general astrometry methods, which includes acquiring knowledge about modern methods of astrometry and their use in practice (including the latest ones, such as radio interferometry and laser location), as well as about the errors of experimental research (observations), the features of methods for processing and interpreting observation data, and generalizing the results obtained. Developing the ability to search, process and analyze information from various sources, including electronic resources, and the ability of students to abstract thinking, analysis and synthesis of material from various physical, mathematical and computer disciplines.
Form of study
Full-time form
Prerequisites and co-requisites
Know the basic laws of mechanics, trigonometry, algebra and physics within the general university courses. Have basic knowledge of astronomy and astrophysics. Be able to apply previous knowledge within the initial mathematics and physics courses. Have elementary skills in calculating derivatives, integrals, actions and operations with vectors, graphically plot function graphs, define and expand functions into series. Have an idea of the least squares method, statistics, nonlinear regression, etc.
Course content
The course on astronomical catalogs and databases is a special astronomical course for students. It includes mastering the basic physical laws, mastering the methods and principles of research adopted in data science and observational astronomy in general, mastering the approaches and methods of interpreting observational data, and generalizing the results obtained under the conditions of large and very large observational arrays.
Recommended or required reading and other learning resources/tools
M.Lutz Programming Python, Ed.4, 2019.
Planned learning activities and teaching methods
Lectures
Assessment methods and criteria
Semester assessment:
1. Tests: 2, each – 15 points
2. Short independent tasks – 10 points
- final assessment (in the form of an exam/complex exam,
differentiated assessment): Exam – 60 points
- conditions for admission to the final exam:
at least 10 points during the semester
Language of instruction
Ukrainian
Lecturers
This discipline is taught by the following teachers
Andrii
Oleksandrovych
Simon
Astronomy and Space Physics Department
Faculty of Physics
Faculty of Physics
Departments
The following departments are involved in teaching the above discipline
Astronomy and Space Physics Department
Faculty of Physics