Information Package / Course Catalogue
Computer Programming in Physics
Course Code: FİZ206
Course Type: Required
Couse Group: First Cycle (Bachelor's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 0
Credit: 3
Lab: 2
ECTS: 6
Objectives of the Course

The aim of this course is to teach the fundamentals of Fortran( or Python) programming language and to enable students to solve the problems they will encounter during their physics undergraduate education with numerical methods.

Course Content

Fundamentals of Fortran and Python programming language, Series expansions, differentiation and integration, solution of simple differential equations, solution of differential equations for two and three dimensional systems, solution of Eigenvalue Eigenvector problem, Random Numbers and their simple applications in integration (Monte Carlo Method), Solution of Basic Statistical Physics Problems and Quantum Mechanics

Name of Lecturer(s)
Prof. Cesur EKİZ
Learning Outcomes
1.can provide basic information about the Fortran or Python programming languages.
2.be able to perform the simple numeric solutions (Euler method) of differential equations.
3.can make simple computer algorithms using the Fortran or Python programming languages.
4.be able to solve dynamic problems by using more complex methods (Runge-Kutta).
5.be able to model the physical phenomenon related to probability laws by using the computer’s ability of producing random number.
6.can explain random events and Monte Carlo simulations.
Recommended or Required Reading
1.Fortran ve Python ile Sayısal Fizik, B. Karaoğlu, Seçkin Yayıncılık, Ankara 2013
2.Computational Physics: Problem Solving with Python, Rubin H. Landau, M. J. Paez, C.C. Bordeianu, Wiley
3.Numerical Methods for Physics, A. L. Garcia
4.An Introduction to Computer Simulations Methods,H.Gould,J.Tobochnick,Addison-Wesley,1996,New York
5.Fiziğin Temelleri , David Halliday, Robert Resnick, and Pearl Walker
Weekly Detailed Course Contents
Week 1 - Theoretical
Python Installation with Anaconda and alternatives
Week 2 - Theoretical
Series Expansions, interpolation and data fitting
Week 3 - Theoretical
Derivatives
Week 4 - Theoretical
Integrals
Week 5 - Theoretical
Differential Equations I: Fundamental and 1-Dimensional problems
Week 6 - Theoretical
1 -Dimensional Problems
Week 7 - Theoretical
Differential Equations II: Multidimensional problems
Week 8 - Theoretical & Practice
Review (Midterm exam)
Week 9 - Theoretical
Eigenvalue Problems
Week 10 - Theoretical
Random numbers and their simple applications in integration (Monte-Carlo)
Week 11 - Theoretical
Fermat principle, probability and the investigation of refraction of the light
Week 12 - Theoretical
The application of probability laws on particles moving under the effect of different potentials (Path integral)
Week 13 - Theoretical
Partial differential equations and numeric solutions
Week 14 - Theoretical
Numerical solutions of simple Schrödinger problems
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%30
Final Examination1%60
Assignment2%10
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140456
Assignment202040
Midterm Examination115217
Final Examination135237
TOTAL WORKLOAD (hours)150
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
PÇ-11
PÇ-12
PÇ-13
PÇ-14
OÇ-1
4
4
3
OÇ-2
2
5
2
4
4
2
OÇ-3
2
5
3
3
2
4
4
2
OÇ-4
2
5
3
3
2
4
3
2
OÇ-5
2
5
3
3
2
4
4
2
OÇ-6
2
1
3
3
4
Adnan Menderes University - Information Package / Course Catalogue
2026