Equations of mathematical physics
Course: System Analysis
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Equations of mathematical physics
        
    
            Code
        
        
            ННД.33
        
    
            Module type 
        
        
            Обов’язкова дисципліна для ОП
        
    
            Educational cycle
        
        
            First
        
    
            Year of study when the component is delivered
        
        
            2023/2024
        
    
            Semester/trimester when the component is delivered
        
        
            8 Semester
        
    
            Number of ECTS credits allocated
        
        
            3
        
    
            Learning outcomes
        
        
            PR 01. Know and be able to apply in practice differential and integral calculus, Fourier series and integrals, analytic geometry, linear algebra and vector analysis, functional analysis, and discrete mathematics to the extent necessary to solve typical problems of systems analysis.
PR 04. Know and be able to apply basic methods of qualitative analysis and integration of ordinary differential equations and systems, differential equations in partial derivatives, including equations of mathematical physics.
PR 09. Be able to create efficient algorithms for computational problems of systems analysis and decision support systems.
PR 15. Understand Ukrainian and foreign languages at a level sufficient for the processing of professional information and literature sources, and professional oral and written communication on professional topics.
        
    
            Form of study
        
        
            Full-time form
        
    
            Prerequisites and co-requisites
        
        
            For the successful study of the course “Equations of Mathematical Physics,” a student must meet the following requirements: Prerequisite courses: successful completion of Mathematical Analysis, Differential Equations, Algebra, Analytical Geometry. Knowledge: main topics of mathematical analysis, algebra, and analytical geometry. Skills: ability to find derivatives, compute integrals, analyze functions for extrema, solve systems of linear algebraic equations with parameters, and apply methods of matrix algebra. Competencies: ability to identify derivatives and antiderivatives of fundamental mathematical functions in various expressions; construct systems of algebraic equations; apply methods for finding polynomial roots; and use methods for analyzing qualitative characteristics of constructed mathematical models.
        
    
            Course content
        
        
            The aim of the course is to provide students with knowledge of the fundamental theoretical principles and methods for solving partial differential equations, approaches to solving initial-boundary value problems and Cauchy problems, the study of the correctness of boundary value problem formulations, and the acquisition of methods for constructing mathematical models of various physical processes in the form of boundary value problems for partial differential equations.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            1. Perestiuk M.O., Marynets V.V. Teoriia rivnian matematychnoi fizyky.-Kyiv: «Lybid», 1993, 250 p. 2. Virchenko N.O. Osnovni metody rozviazannia zadach matematychnoi fizyky.- Kyiv, KPI, 1997, 370 p. 3. Dovhyi S.O., Lifanov I.K. Metod Synhuliarnykh intehralnykh rivnian. Teoriia ta zastosuvannia. - Kyiv, «naukova dumka», 2004, 510 p. 4. Dovgiy, S.O., Lyashko, S.I., Cherniy, D.I. Algorithms of the Discrete Singularity Method for Computing Technologies // Cybernetics and Systems Analysis, 53 (6). - 2017. - pp. 950-962. DOI: 10.1007/s10559-017-9997-4.
        
    
            Planned learning activities and teaching methods
        
        
            Lectures, practical classes, independent work, elaboration of recommended literature, homework.
        
    
            Assessment methods and criteria
        
        
            The maximum number of points a student can obtain is 100 points: 1. Midterm test 1 (Part I): 30 points / 18 points. 2. Midterm test 2 (Part II): 30 points / 18 points. Continuous assessment: 40 points / 24 points. Final assessment: in the form of a credit test. It is based on the student’s performance throughout the semester and does not require additional assessment activities for students who have achieved satisfactory results.
        
    
            Language of instruction
        
        
            Ukrainian
        
    Lecturers
This discipline is taught by the following teachers
                    Dmytro
                    Ivanovych
                    Cherniy
                
                
                    Complex systems modelling 
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
                    Yaroslav
                    Pavlovych
                    Trotsenko
                
                
                    Complex systems modelling 
Faculty of Computer Science and Cybernetics
            Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
                        Complex systems modelling
                    
                    
                        Faculty of Computer Science and Cybernetics
                    
                
                        Complex systems modelling
                    
                    
                        Faculty of Computer Science and Cybernetics