COURSE UNIT TITLE

: COMPUTATIONAL PHYSICS-II

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
PHY 5152 COMPUTATIONAL PHYSICS-II ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR GÜL GÜLPINAR

Offered to

PHYSICS
PHYSICS

Course Objective

The content serves the scope of presenting training in an algorithmic approach to problems in the sciences, represented here by the unity of three disciplines, physics, mathematics and informatics. This trinity outlines the emerging field of computational physics.

Learning Outcomes of the Course Unit

1   Acquire a deeper understanding of the laws of physics in selected sub-fields, set up and solve a variety of advanced problems in selected sub-fields, Thermodynamics and statistical physics, Symmetry and conservation laws, Mechanics, electromagnetism, and/or quantum/atomic physics.
2   Become proficient with the tools used to solve physics and engineering problems: math: ordinary and partial differential equations, Fourier analysis, apply these advanced methods to the solution of physics problems,computer: simulation of physical systems, 3D and stereo scientific visualization.
3   Experience independent learning, such as exploratory computational projects focused on specific systems, apply techniques or computer simulation to explore practical problems , research projects and teaching, participate in a research project under the direction of a faculty member and/or teach an elementary lab section
4   Communicate effectively in all classroom situations; full computational project reports, write a complete, self-contained report, understandable by student pers,scientific presentations, present results of a research project or lab exercise to peers and/or Faculty.
5   Being able to explain assumptions and logic steps in the numerical solution of a physics problem

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Random numbers-1
2 Random numbers-2
3 Monte Carlo Integration
4 Importance sampling
5 Monte Carlo Simulation of Ising model-1
6 Monte Carlo Simulation of Ising model-2
7 Molecular dynamics simulations-1
8 mid term 1
9 Molecular dynamics simulations-2
10 Modeling continuous systems-1
11 Modeling continuous systems-2
12 Symbolic computing

Recomended or Required Reading

Textbook:
N. Giordano and H. Nakanishi, Computational Physics 2nd Edition, Addison-Wesley; 2nd edition (2005), ISBN-13: 978-0131469907
References:
1. R. H. Landau, M. J. Paez and Cristtian C. Bordeianu, Computational Physics,
Problem Solving with Computers, 2nd Edition, Wiley-VCH (2007).
2. T. Pang , Introduction to Computational Physics, 2nd Edition Cambridge (2006).
3. W.H. Press, S. A. Teukolsky, W. T. Vetterling and B. P. Flannery, Numerical
Recipes, The Art of Scientific Computing, 3rd Edition, Cambridge University Press (2007).

Planned Learning Activities and Teaching Methods

Learning and Teaching Strategies:

1. Lecturing
2.Question-Answer
3.Discussing
4.Homework

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.40 + FIN * 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + RST * 0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

1. The homework and mid-term exams of the student is assessed as the achievement of them in the semester.
2. At %40 score of final examination is added directly to the others.

Language of Instruction

English

Course Policies and Rules

1. It is obligated to continue at least 70% of lessons.
2. If the student don t make the homework and attend mid-terms, he does not access the final exam

Contact Details for the Lecturer(s)

gul.gulpinar@deu.edu.tr

Office Hours

Monday and Wednesday between 10:00-11:00 a.m.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lecture 14 3 42
Weekly preparations before/after course 14 3 42
Preparations for mid-term exam 2 5 10
Preparations for final exam 1 10 10
Preparations for homework 12 7 84
Final Exam 1 3 3
Mid-term Exam 2 2 4
TOTAL WORKLOAD (hours) 195

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.15
LO.24543
LO.345
LO.45453
LO.534

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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