PHYSICS 7534 - Computational Physics

North Terrace Campus - Semester 1 - 2015

This hands-on course provides an introduction to computational methods in solving problems in physics. It teaches programming tactics, numerical methods and their implementation, together with methods of linear algebra. These computational methods are applied to problems in physics, including the modelling of classical physical systems to quantum systems, as well as to data analysis such as linear and nonlinear fits to data sets. Applications of high performance computing are included where possible, such as an introduction to parallel computing and also to visualization techniques.

  • General Course Information
    Course Details
    Course Code PHYSICS 7534
    Course Computational Physics
    Coordinating Unit School of Physical Sciences
    Term Semester 1
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Up to 6 hours per week
    Available for Study Abroad and Exchange Y
    Prerequisites Sufficient Physics and Mathematics knowledge equivalent to 'Assumed Knowledge'
    Incompatible PHYSICS 3534
    Assumed Knowledge PHYSICS 2510, PHYSICS 2532, PHYSICS 2534, MATHS 2101 or MATHS 2201, MATHS 2102 or MATHS 2202 or equivalent
    Course Description This hands-on course provides an introduction to computational methods in solving problems in physics. It teaches programming tactics, numerical methods and their implementation, together with methods of linear algebra. These computational methods are applied to problems in physics, including the modelling of classical physical systems to quantum systems, as well as to data analysis such as linear and nonlinear fits to data sets. Applications of high performance computing are included where possible, such as an introduction to parallel computing and also to visualization techniques.
    Course Staff

    Course Coordinator: Dr Rodney Crewther

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes

    On completion of this course, students should be able to:

    1. identify modern programming methods and describe the extent and limitations of computational methods in physics,
    2. identify and describe the characteristics of various numerical methods.
    3. independently program computers using leading-edge tools,
    4. formulate and computationally solve a selection of problems in physics,
    5. use the tools, methodologies, language and conventions of physics to test and communicate ideas and explanations.
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)
    Knowledge and understanding of the content and techniques of a chosen discipline at advanced levels that are internationally recognised. 1 – 2
    The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner. 3 – 5
    An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems. 1 – 5
    Skills of a high order in interpersonal understanding, teamwork and communication. 5
    A proficiency in the appropriate use of contemporary technologies. 1 – 5
    A commitment to continuous learning and the capacity to maintain intellectual curiosity throughout life. 1 – 5
    A commitment to the highest standards of professional endeavour and the ability to take a leadership role in the community. 5
  • Learning Resources
    Recommended Resources

    This course requires the following texts and other resources:

    Text

    -         Fortran 95/2003 Explained, Metcalf, Reid and Cohen (Oxford)

    References

    -         Fortran 90/95 Explained, Metcalf and Reid (Oxford)

    -         Fortran 90/95 for Scientists and Engineers, Chapman (McGraw-Hill Higher Education)

    -         Fortran 90 Programming, Ellis, Philips and Lahey (Addison-Wesley)

    -         Numerical Recipes in FORTRAN: The Art of Scientific Computing, Press, et al. (Cambridge University Press)

    -         Computational Physics -Fortran Version, Koonin and Meredith (Addison Wesley).

    -         "Mastering Matlab 7" by Duane C. Hanselman and Bruce L. Littlefield, Prentice Hall, 2005
  • Learning & Teaching Activities
    Learning & Teaching Modes

    No information currently available.

    Workload

    No information currently available.

    Learning Activities Summary

    No information currently available.

  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary

    No information currently available.

    Assessment Detail

    No information currently available.

    Submission

    No information currently available.

    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

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