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Ordinary differential equations I

General data

Course ID: 1000-114bRRZIb
Erasmus code / ISCED: 11.132 Kod klasyfikacyjny przedmiotu składa się z trzech do pięciu cyfr, przy czym trzy pierwsze oznaczają klasyfikację dziedziny wg. Listy kodów dziedzin obowiązującej w programie Socrates/Erasmus, czwarta (dotąd na ogół 0) – ewentualne uszczegółowienie informacji o dyscyplinie, piąta – stopień zaawansowania przedmiotu ustalony na podstawie roku studiów, dla którego przedmiot jest przeznaczony. / (unknown)
Course title: Ordinary differential equations I
Name in Polish: Równania różniczkowe zwyczajne z laboratorium
Organizational unit: Faculty of Mathematics, Informatics, and Mechanics
Course groups: Obligatory courses for 2nd grade JSEM
Obligatory courses for 2nd grade JSIM (3M+4I)
Obligatory courses for 2rd grade Mathematics
Obligatory courses for 4th grade JSIM (3I+4M)
ECTS credit allocation (and other scores): 7.50 Basic information on ECTS credits allocation principles:
  • the annual hourly workload of the student’s work required to achieve the expected learning outcomes for a given stage is 1500-1800h, corresponding to 60 ECTS;
  • the student’s weekly hourly workload is 45 h;
  • 1 ECTS point corresponds to 25-30 hours of student work needed to achieve the assumed learning outcomes;
  • weekly student workload necessary to achieve the assumed learning outcomes allows to obtain 1.5 ECTS;
  • work required to pass the course, which has been assigned 3 ECTS, constitutes 10% of the semester student load.

view allocation of credits
Language: Polish
Type of course:

obligatory courses

Prerequisites (description):

(in Polish) Oczekuje się dobrej znajomości zagadnień ujętych w sylabusach przedmiotów Analiza matematyczna I.2 oraz Analiza matematyczna II.1.

Short description:

Ordinary differential equations (ODEs), their properties and applications. Solution methods for ODEs: using paper and pencil, and using numerical schemes. Computer lab experiments: numerical and symbolic ODE packages.

Full description:

Differential equation and its solution, first order and higher order equations, systems of differential equations, direction field, solution methods for simple types equations.

Simple numerical one- and multistep schemes. Runge-Kutta methods. Explicit and implicit schemes. Ways to derive numerical methods for ODEs.

Local existence and uniqueness theorems. Prolongation of the solution. Dependence on a parameter or on the initial condition; differentiability with respect to the parameter.

Systems of linear ODEs, the basis of the solutions. The fundamental matrix. Wronskian, Liouville's theorem. Systems with constant coefficients. Exponential of a matrix, nonhomogeneous systems. Higher order linear ODEs with constant coefficients.

Difference equations and their properties. Convergence theory for one-step methods. Consistency and stability. Stability and strong stability of multistep methods.

Nonlinear ODEs and stability. Lyapunov function. Phase plane and taxonomy of phase curves of autonomous systems. Singular points on a plane.

Absolute stability and the region of absolute stability. Stiffness and how to cope with it.

Computer lab experiments: numerical and symbolic ODE packages.

Bibliography:

E. Hairer, S. P. Norsett, G. Wanner "Solving Ordinary Differential Equations", Springer

V.I.Arnold, R.Crooke "Ordinary differential equations", Springer

Boyce, DiPrima, "Elementary differential equations", Wiley

Learning outcomes:

Knowledge and skills:

The students:

  1. know the concepts of differential equation, the solutions of initial value problem (IVP), can verify whether the specified function is the solution of ODE or IVP;
  2. can solve: separable, homogeneous, Bernoulli ODEs;
  3. know the sufficient conditions of existence and uniqueness of solution of IVP;
  4. can give an example of IVP with infinite number of solutions;
  5. know the theorem about extending solutions of ODEs and can give an example of IVP which cannot be extended beyond some finite interval;
  6. can solve the linear ODEs;
  7. can convert higher order ODE to a system of the first order ODEs;
  8. can find the fundamental matrices for systems of linear ODEs;
  9. know the concept of vector field;
  10. know the concept of equilibrium points and know the definitions of asymptotic and Lyapunov stabilities of equilibrium points;
  11. can verify the stability of an equilibrium point;
  12. know examples of applications of ODEs in sciences and real life.

Competence:

  1. The students understand the role of ODEs in modelling natural processes.
Assessment methods and assessment criteria: (in Polish)

Zaliczenie na podstawie kolokwium, prac domowych, aktywności na zajęciach, projektów komputerowych.

Egzamin pisemny i w wyjątkowych przypadkach ustny.

Ocena końcowa na podstawie punktów z kolokwium, ćwiczeń, laboratorium i egzaminu.

Classes in period "Summer semester 2023/24" (in progress)

Time span: 2024-02-19 - 2024-06-16
Selected timetable range:
Navigate to timetable
Type of class:
Classes, 30 hours more information
Lab, 15 hours more information
Lecture, 30 hours more information
Coordinators: Piotr Kowalczyk
Group instructors: Bartosz Bieganowski, Marcin Choiński, Piotr Kowalczyk, Norbert Mokrzański, Magdalena Szafrańska
Students list: (inaccessible to you)
Examination: Examination

Classes in period "Summer semester 2024/25" (future)

Time span: 2025-02-17 - 2025-06-08
Selected timetable range:
Navigate to timetable
Type of class:
Classes, 30 hours more information
Lab, 15 hours more information
Lecture, 30 hours more information
Coordinators: Piotr Kowalczyk
Group instructors: Bartosz Bieganowski, Michał Borowski, Roman Korsak, Piotr Kowalczyk, Norbert Mokrzański
Students list: (inaccessible to you)
Examination: Examination
Course descriptions are protected by copyright.
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