• Offered by Research School of Physics
  • ANU College ANU Joint Colleges of Science
  • Course subject Physics
  • Areas of interest Physics
  • Academic career UGRD
  • Course convener
    • AsPr Matthew Sellars
    • Prof Gregory Lane
  • Mode of delivery In Person
  • Offered in First Semester 2022
    Second Semester 2022
    See Future Offerings

See https://www.anu.edu.au/covid-19-advice. In Sem 1 2022, this course is delivered on campus with adjustments for remote participants.

Physics is concerned with the nature, properties and understanding of matter and energy in the universe. The primary method of testing whether physical theories are correct is through comparison of theoretical predictions with measurements of physical properties. Indeed, it could be said that the pursuit of ever more accurate and precise measurements is the bedrock of modern physics. The Physics Advanced Laboratory course will consist of lectures, smaller laboratory experiments, computational exercises, and, most importantly, the design and performance of complex, open-ended experiments using high-end equipment in real research laboratories, such as high precision lasers and a 15MV electrostatic tandem accelerator. The course is designed to develop the essential scientific and laboratory techniques required by experimental physicists, as well as oral and written communication skills, self-reliance, trouble-shooting abilities and a sophisticated understanding of measurement uncertainty.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Understand and be able to apply a broad range of measurement methods and techniques that are widely used in physics experiments;
  2. Understand the importance of noise and statistical uncertainties in measurements of physical processes;
  3. Design experiments and be able to make appropriate choices of measurement techniques and equipment;
  4. Be able to apply high-level computational and statistical techniques to datasets, including complex uncertainty analysis and model testing;
  5. Communicate effectively in both oral and written formats.

Other Information

Specific Skills Learned:

  • Mathematical: Statistics, Monte Carlo methods, Fourier analysis Computational: Computer control, data manipulation, data visualisation, model/curve fitting. A variety of computer languages will be used, with a focus on Python and Mathematica.
  • Experimental: Experimental design and techniques.
  • Communication: Written lab reports, oral presentations, oral exam.

Indicative Assessment

  1. Exam (30) [LO 1,2,3,4]
  2. Laboratory Reports (40) [LO 1,2,3,4,5]
  3. Oral presentation /defence of experimental results (20) [LO 5]
  4. Logbook (10) [LO 1,2,3,4]

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

The expected workload will consist of approximately 130 hours throughout the semester including:

• Face-to face component which may consist of 1 x 3 hour workshop per week and up to 30 hours of laboratory work over the semester

• Approximately 64 hours of self directed study which will include preparation for workshops and other assessment tasks.

Inherent Requirements

To be determined

Requisite and Incompatibility

Completion of a minimum of 18 units from PHYS2013, PHYS2020, PHYS2201, PHYS2016.

Prescribed Texts

N/A

Preliminary Reading

There is no prescribed text book, but the following books are recommended as references: “Building Scientific Apparatus” J.H. Moore, C.C. Davies, Michael Coplan and S. Greer (Cambridge University Press), “Radiation Detection and Measurement 4th edition” G.F. Knoll (Wiley US), “Numerical Recipes 3rd edition: The Art of Scientific Computing” H. William et al. (Cambridge University Press),

Assumed Knowledge

Since this course will focus on experimental skills and techniques, as well as data analysis and interpretation, much of the background physics will be assumed. Hence, completion of all the core second year physics courses is highly desirable. Dealing with large data sets and sophisticated data analysis methods involves programming and computer-based analysis. While a basic knowledge of programming and computational skills is advised, part of the purpose of the course is to develop these skills.

Fees

Tuition fees are for the academic year indicated at the top of the page.  

Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees

Student Contribution Band:
2
Unit value:
6 units

If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Domestic fee paying students
Year Fee
2022 $4200
International fee paying students
Year Fee
2022 $6000
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

First Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
3084 21 Feb 2022 28 Feb 2022 31 Mar 2022 27 May 2022 In Person N/A

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
6079 25 Jul 2022 01 Aug 2022 31 Aug 2022 28 Oct 2022 In Person N/A

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