Offered to students admitted to Year 1 in ALL
Major/Minor ALL
Course Type
Offer in 2018 - 2019 Y N
Course Code PHYS4150
Date2019/07/23 19:16
Enquiry for Course Details
PHYS4150 Computational physics (6 credits) Academic Year 2018
Offering Department Physics Quota ---
Course Co-ordinator Prof J Wang, Physics < jianwang@hku.hk >
Teachers Involved (Prof J Wang,Physics)
Course Objectives The aim of the course is show how the power of computers enables to computational approach to solving physics problems to be adopted, which is distinct from, and complimentary to, traditional experimental and theoretical approaches. The material covered will be found useful in any project or problem solving work that contains a strong computational or data analysis element. The course is designed such that a significant fraction of the student's time is spent actually programming specific physical problems rather than learning abstract techniques.
Course Contents & Topics The course will cover the following problems: Introductory computational physics and computer algebra, integration and differentiation, interpolation and extrapolation, ordinary differential equation such as those of classical mechanics, partial differential equations (such as the Maxwell's equation, the diffusion equation, and the Schrodinger equation), matrix methods (such as systems of equations and eigenvalue problems applied to Poisson's equation and electronic structure calculations), Monte Carlo (Metropolis algorithm) and other simulation methods (such as molecular dynamics), and several physics projects.
Course Learning Outcomes
On successful completion of this course, students should be able to:

CLO 1 demonstrate knowledge in essential methods and techniques for numerical computation in physics
CLO 2 apply Monte Carlo method and other simulation methods to solve deterministic as well as probabilistic physical problems
CLO 3 employ appropriate numerical method to interpolate and extrapolate data collected from physics experiments
CLO 4 use appropriate numerical method to solve the differential equations governing the dynamics of physical systems
Pre-requisites
(and Co-requisites and
Impermissible combinations)
Pass in (MATH3301 or MATH3401 or MATH3403 or MATH3405 or PHYS3150); and
Pass in any three of the following courses: PHYS3350, PHYS3351, PHYS3450, PHYS3550
Course Status with Related Major/Minor /Professional Core 2018 Major in Physics ( Disciplinary Elective )
2018 Minor in Physics ( Disciplinary Elective )
2017 Major in Astronomy ( Disciplinary Elective )
2017 Major in Mathematics/Physics ( Disciplinary Elective )
2017 Major in Physics ( Disciplinary Elective )
2017 Minor in Physics ( Disciplinary Elective )
2016 Major in Astronomy ( Disciplinary Elective )
2016 Major in Mathematics/Physics ( Disciplinary Elective )
2016 Major in Physics ( Disciplinary Elective )
2016 Minor in Physics ( Disciplinary Elective )
2015 Major in Astronomy ( Disciplinary Elective )
2015 Major in Mathematics/Physics ( Disciplinary Elective )
2015 Major in Physics ( Disciplinary Elective )
2015 Minor in Physics ( Disciplinary Elective )
2014 Major in Astronomy ( Disciplinary Elective )
2014 Major in Mathematics/Physics ( Disciplinary Elective )
2014 Major in Physics ( Disciplinary Elective )
2014 Minor in Physics ( Disciplinary Elective )
Course to PLO Mapping 2018 Major in Physics < PLO 1,2,3,4 >
2017 Major in Astronomy < PLO 1,2,3,4 >
2017 Major in Mathematics/Physics < PLO 1,2,3,4 >
2017 Major in Physics < PLO 1,2,3,4 >
2016 Major in Astronomy < PLO 1,2,3,4 >
2016 Major in Mathematics/Physics < PLO 1,2,3,4 >
2016 Major in Physics < PLO 1,2,3,4 >
2015 Major in Astronomy < PLO 1,2,3,4 >
2015 Major in Mathematics/Physics < PLO 1,2,3,4 >
2015 Major in Physics < PLO 1,2,3,4 >
2014 Major in Astronomy < PLO 1,2,3,4 >
2014 Major in Mathematics/Physics < PLO 1,2,3,4 >
2014 Major in Physics < PLO 1,2,3,4 >
Offer in 2018 - 2019 Y        1st sem    Examination Dec     
Offer in 2019 - 2020 Y
Course Grade A+ to F
Grade Descriptors
A Demonstrate thorough mastery at an advanced level of extensive knowledge and skills required for attaining all the course learning outcomes. Show strong analytical and critical abilities and logical thinking, with evidence of original thought, and ability to apply knowledge to a wide range of complex, familiar and unfamiliar situations. Apply highly effective organizational and presentational skills. Apply highly effective lab skills and techniques. Critical use of data and results to draw appropriate and insightful conclusions.
B Demonstrate substantial command of a broad range of knowledge and skills required for attaining at least most of the course learning outcomes. Show evidence of analytical and critical abilities and logical thinking, and ability to apply knowledge to familiar and some unfamiliar situations. Apply effective organizational and presentational skills. Apply effective lab skills and techniques. Correct use of data of results to draw appropriate conclusions.
C Demonstrate general but incomplete command of knowledge and skills required for attaining most of the course learning outcomes. Show evidence of some analytical and critical abilities and logical thinking, and ability to apply knowledge to most familiar situations. Apply moderately effective organizational and presentational skills. Apply moderately effective lab skills and techniques. Mostly correct but some erroneous use of data and results to draw appropriate conclusions.
D Demonstrate partial but limited command of knowledge and skills required for attaining some of the course learning outcomes. Show evidence of some coherent and logical thinking, but with limited analytical and critical abilities. Show limited ability to apply knowledge to solve problems. Apply limited or barely effective organizational and presentational skills. Apply partially effective lab skills and techniques. Limited ability to use data and results to draw appropriate conclusions.
Fail Demonstrate little or no evidence of command of knowledge and skills required for attaining the course learning outcomes. Lack of analytical and critical abilities, logical and coherent thinking. Show very little or no ability to apply knowledge to solve problems. Organization and presentational skills are minimally effective or ineffective. Apply minimally effective or ineffective lab skills and techniques. Misuse of data and results and/or unable to draw appropriate conclusions.
Course Type Lecture with laboratory component course
Course Teaching
& Learning Activities
Activities Details No. of Hours
Laboratory 12
Lectures 36
Tutorials 8
Reading / Self study 80
Assessment Methods
and Weighting
Methods Details Weighting in final
course grade (%)
Assessment Methods
to CLO Mapping
Assignments 20 CLO 1,2,3,4
Examination 2-hour written exam 40 CLO 1,3,4
Presentation 15 CLO 1
Project report 25 CLO 1,2,3,4
Required/recommended reading
and online materials
Lecture notes provided by Course Coordinator
Samuel S.M. Wong: Computational Methods in Physics and Engineering (World Scientific)
N.J. Giordano and N. Nakanishi: Computational physics (Pearson Education Inc.).
Course Website NIL
Additional Course Information NIL
Back  /  Home