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2010/1 Module Catalogue
 Module Code: PHY1011 Module Title: EXPERIMENTAL PHYSICS MULTIPLE MODULE
Module Provider: Physics Short Name: PH1M-EXPP
Level: HE1 Module Co-ordinator: HOSEA TJ Dr (Physics)
Number of credits: 30 Number of ECTS credits: 15
 
Module Availability

Semester 1 and Semester 2.

Assessment Pattern

Assessment Pattern

 

Unit(s) of Assessment

 

Weighting Towards Module Mark( %)

 

Semester 1 Laboratory Coursework

 

33%

 

Semester 2 Laboratory Coursework

 

33%

 

Fortran Coursework

 

26%

 

Data Handling Coursework

 

8%

 

Qualifying Condition(s): 

 

University general regulations refer.

 

 

Assessment Schedule

 

Semester 1 Coursework:

 

Laboratory diary aggregate mark (17%)

 

Laboratory written report (8%)

 

Laboratory class test (8%)

 

 

Semester 2 Coursework:

 

Laboratory diary aggregate mark (17%)

 

Laboratory written report (8%)

 

Laboratory poster presentation (8%)

 

 

Computational Coursework:

 

Data analysis (8%)

 

Fortran assignments (18%)

 

Fortran class test (8%)

 

Note: the weight of each Coursework element to the total module mark is indicated.

 


Module Overview

Practical 1:

 

A series of experiments of varying length designed to provide a common set of laboratory skills for students arriving from various backgrounds.

 

 

Practical 2:

 

A series of two-week experiments designed to allow students to continue developing their laboratory skills.  The experiments will include at least one on a subject related to each student's chosen degree programme.

 

 

Computational Laboratory:

 

The processing of experimental data and the evaluation of uncertainties and errors are developed in Excel. Numerical methods and their implementation in the Fortran 95 programming language are introduced. The visualisation and presentation of results using graphics packages within both windows and X-windows environment is introduced.

 

Prerequisites/Co-requisites

Practical 1, Practical 2 and Computational Laboratory:

 

Pre-university education to Advanced Level standard.

 

 

Module Aims

Practical 1:

 

To provide an appropriate introduction and lay a secure foundation for the development of the skills of an experimental physicist.  To provide an opportunity to become familiar with:

 

-     Standard laboratory equipment

 

-     Data and error analysis methods

 

-     Good laboratory practice

 

-     Presentation of scientific results

 

 

Practical 2:

 

To provide an opportunity for students to continue to develop a range of practical skills in the use of scientific apparatus, data analysis, and scientific communication (written and verbal).

 

 

Computational Laboratory:

 

To know the basic elements of probability distributions and to be able to undertake simple statistical and error analysis.  To be able to use a computer spreadsheet to do such analysis, plot graphs and perform curve fitting.  To introduce editors and scientific programming constructs.  To introduce and, through sample programs and practical classes, to teach the use of those Fortran 95 language elements necessary to write, compile and run computer programs for simple data manipulations.  To develop and enhance a student’s Fortran 95 programming skills and to introduce a number of practical numerical and simulation methods applicable to physical problems.

 

 

Learning Outcomes

Practical 1:

 

By the end of this component, the student should be able to (i) follow detailed instructions in order to carry out simple experiments which demonstrate physical principles (ii) analyse the results of said experiments and in particular provide a detailed error analysis (iii) fully and accurately record the experiment (iv) write a detailed account of the experiment following standard scientific writing and reporting methods.

 

 

Practical 2:

 

By the end of this component, the student should be able to (i) follow experimental procedures and develop their own strategies for acquiring data in order to investigate a range of physical phenomena; (ii) analyse the results of experiments and, in particular, provide a detailed error analysis; (iii) fully and accurately record the experiment; (iv) write a detailed account of the experiment following standard scientific writing and reporting method; and (v) present the results of an experiment in the form of a poster.

 

 

Computational Laboratory:

 

At the end of this component students should have developed good programming practice in Fortran 95 and be able to apply their knowledge to solve a number of physical problems numerically.  Students should be able to analyse and present reduced experimental and probabilistic results of the multiple measurements of physical observables.  Specifically they should be able to quote averages and errors of such variables.  They should be able to fit theoretical predictions to graphs where one independent observable is changing using the method of least squares, and find the errors in the fitting parameter(s).  Students should be able to use simple error theory to find the errors of quantities dependent on (combinations of) the observables.  They should be able to use simply probability distributions to predict the outcome of experiments.

 

Module Content

Practical 1:

 

For the first three weeks, students undertake a series of short experiments lasting typically one hour which covers areas such as errors, electrical measurement, waves, simple optics, Fourier synthesis and resonance.  These are followed by a set of one-week experiments related to the core physics modules and or to the specialist physics courses.

 

 

Practical 2:

 

A series of two-week experiments (eight hours each) covering areas related to the core physics modules, including electronics.  At least one experiment will be offered in an area relevant to each student’s particular degree specialisation (e.g. nuclear physics).

 

 

Computational Laboratory:

 

Probability:                                                                  Discrete and continuous distributions,                                                                                                expectation values.  Binomial, Gaussian and                       Poisson distributions.  The Central Limit                                              Theorem.

 

Statistics:                                                                    Mean, standard deviation, standard error in                                                                                        mean.

 

Data Handling:                                                            Propagation of errors, least-squares fitting, X2                                                                                   distribution.

 

Spreadsheets:                                                            Excel spreadsheets including calculations and                                                                                  graphs.

 

Units, Matrices, Computer Algebra:                           Introduction to some features of MathCad.

 

Introduction to the Fortran 95 Language:                   Constant and variable types and their                                                                                                 declaration, parameters, arithmetic operators                      and expressions, arithmetic assignments,                                   intrinsic functions, simple input/output,                                                                                               relational expressions, logical expressions, the                    forms of the IF statement, subprograms, DO                          loops, arrays and their use for subscripted                                                                                         variables, general input/output, the format                                                                                         statement.

 

Introductory Programming Exercises:                       Averages, running sums/products, function                                                                                        evaluation, iteration, simple simulation, use of                      input and output, integers and reals, random                             number simulations, use of arrays.

 

Five Computing Assignments Covering:                   1) Roots of equations (Newton-Raphson); 2)                                                                                     numerical differentiation; 3) numerical                                                                                               integration; 4) random number simulations and                   5) linear algebra.

 

 

Methods of Teaching/Learning

Practical 1:

 

Twelve half-days (48 hours) of laboratory classes.

 

 

Practical 2:

 

Twelve half-days (48 hours) of laboratory classes.

 

 

Computational Laboratory:

 

Semester 1:                                                     CPTL: 13 two-hour computing laboratory sessions. 

 

                                                                         DH: one-hour lecture followed by one-hour tutorial session in a computing laboratory, weekly for six weeks.

 

                                                                         PC:  2 hours introductory lectures during week 3.

 

Semester 2:                                                     CPTL: 12 two-hour computing laboratory sessions.

 

 

Selected Texts/Journals

 

Practical 1 and Practical 2:

 

Required Reading :

 

i.                Dr D Lancefield, Physics Laboratory Handbook: Level 1, Physics Department (a copy will be given to all students).

 

 


Recommended Reading :

 

i.                L Kirkup, Experimental Methods: An introduction to the analysis and presentation of data, John Wiley and Sons, New York , 1994.

 

ii.              R J Barlow, Statistics, Manchester Physics Series, Wiley, IBSN 0471-92295-1.

 

iii.             P R Bevington and D K Robinson, Data Reduction and Error Analysis for the Physical Sciences, [Second Edition], McGraw Hill, 1992.  The first edition with only Bevington as the author is in the Library: 519.286 BEV

 

iv.            J R Taylor , An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements, [Second Edition], Scinu Books, 1997.

 

 

Computational Laboratory:

 

i.                T M R Elis , I R Philips and T M Lahey, Fortran 90 Programming, Addison-Wesley.

 

ii.              Metcalf and Reid, Fortram 90/95 explained, Oxford University Press, Oxford , 1996.

 

iii.             FORTRAN 95 programming on the Departmental Intranet, http://web.ph.surrey.ac.uk/fortweb/

 

iv.            Dr D Lancefield, Physics Laboratory Handbook: Level 1, Physics Department (given to all students in Practical I).

 

v.              R J Barlow, Statistics, Manchester Physics Series, J Wiley, ISBN 0471-92295-1.

 

Last Updated

August 2010.