Laboratory and Computing Skills for Physicists - PH370

Location Term Level Credits (ECTS) Current Convenor 2019-20
Canterbury Autumn and Spring
View Timetable
4 30 (15) DR G Roch

Pre-requisites

UK Advanced Level Physics Examinations with a normal minimum attainment of a
Grade C on the main Physics A - Level. Any generally accepted equivalent of this
content and attainment is regarded as an acceptable prerequisite.
Co-requisites:
PH311 Mathematics I, PH312 Mathematics II, PH304 Introduction to Special Relativity, Astronomy, Astrophysics and Cosmology, PH321 Mechanics, PH322 Electricity and Light, PH323 Thermodynamics and Matter.

Restrictions

None

2019-20

Overview

Standard Lectures:
How Physical Sciences are taught at Kent.
Library use. Bibliographic database searches.
Error analysis and data presentation. Types of errors; combining errors; Normal distribution; Poisson distribution; graphs – linear and logarithmic.
Probability and Statistics. Probability distributions, laws of probability, permutations and combinations, mean and variance.
Academic integrity and report writing skills.

Laboratory experiments:
A number of experiments in weekly sessions; some of the experiments require two consecutive weeks to complete.
Experiments introduce students to test equipment, data processing and interpretation and cover subjects found in the Physics degree program which include the following topics:
Mechanics, Astronomy/Astrophysics, statistical and probability analysis, numerical simulations, electric circuits and Thermodynamics.

Computing Skills:
Introduction to the concept of programming/scripting languages. Introduction to operating systems: including text editors, the directory system, basic utilities and the edit-compile-run cycle.
Introduction to the use of variables, constants, arrays and different data types; iteration and conditional branching.
Modular design: Use of programming subroutines and functions. Simple input/output, such as the use of format statements for reading and writing, File handling, including practical read/write of data files.
Producing graphical representation of data, including histograms. Interpolating data and fitting functions.
Programming to solve physical problems.
Introduction to typesetting formal scientific documents.

Details

Contact hours

30 hours of lectures, 20 hours console sessions and 40 laboratory hours.
Total study hours: 300.

Availability

This is not available as a wild module.

Method of assessment

100% Coursework; Library Quiz 4%, 10 short lab reports with included computing elements 38%; 5 long lab reports 38%; 5 computing assignments 20%

Indicative reading

  • Experimental methods, Kirkup, L., 1994
  • An Introduction to Error Analysis, Taylor, J., 1997
  • C. Jackson: Learning to program using Python, Jackson, C., 2011

    See the library reading list for this module (Canterbury)

  • Learning outcomes

  • An ability to identify relevant principles and laws when dealing with problems, and to make approximations necessary to obtain solutions.
  • An ability to execute and analyse critically the results of an experiment or investigation and draw valid conclusions. To evaluate the level of uncertainty in these results and compare them with expected outcomes, theoretical predictions or with published data; thereby to evaluate the significance of their results in this context.
  • An ability to communicate scientific information, in particular to produce clear and accurate scientific reports.
  • A familiarity with laboratory apparatus and techniques, including relevant aspects of Health & Safety.
  • The ability to systematically and reliably record experimental data.
  • An ability to make use of appropriate texts, research-based materials or other learning resources as part of managing their own learning.
  • A systematic understanding of how computers work according to human's instructions.
  • Knowledge and understanding of computer programming principles, and their application to diverse problems.
  • An ability to solve problems in physics/mathematics using appropriate mathematical tools. Ability to use computational methods for the practical application of theory and to use information technology and data-processing skills to search for, assess and interpret data.
  • An ability to use mathematical techniques and analysis to model physical behaviour including the use of computer programming along with development of simple algorithms.
  • Competence in the use of appropriate C&IT packages/systems for the analysis of data and the retrieval of appropriate information.
  • An ability to present and interpret information graphically including the use of computer programming.

  • Problem-solving and Programming skills, in the context of both problems with well-defined solutions and open-ended problems; an ability to formulate problems in precise terms and to identify key issues, and the confidence to try different approaches in order to make progress on challenging problems. Numeracy is subsumed within this area.
  • Investigative skills in the context of independent investigation including the use of textbooks and other available literature, databases, and the interaction with colleagues to extract important information.
  • Communication skills in the area of dealing with surprising ideas and difficult concepts, including listening carefully, reading demanding texts and presenting complex information in a clear and concise manner. C&IT skills are an important element to this.
  • Analytical skills – associated with the need to pay attention to detail and to develop an ability to manipulate precise and intricate ideas, to construct logical arguments and to use technical language correctly.
  • Personal and interpersonal skills – the ability to work independently, to use initiative, to organise oneself to meet deadlines and to interact constructively with other people within a professional environment. Including the ability to communicate and interact with professionals from other disciplines.

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