Mapping the Universe with Professional Skills - PHY00023C

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  • Department: Physics
  • Module co-ordinator: Dr. Emily Brunsden
  • Credit value: 20 credits
  • Credit level: C
  • Academic year of delivery: 2019-20

Related modules

Pre-requisite modules

  • None

Co-requisite modules

  • None

Module will run

Occurrence Teaching cycle
A Autumn Term 2019-20 to Summer Term 2019-20

Module aims

The aim of this module is to develop the core competencies and knowledge required of any astrophysicist, including a general introduction to the subject, basic IT skills, report writing, use of information resources, experimental techniques, problem solving and computer programming. This will be achieved through a mix of activities, including laboratories, workshops, lectures, programming classes and small group teaching. The knowledge and skills learnt will be further developed in later years.

The astrophysics component of the module explores our place in the Universe by considering its constituents and the physical principles that govern them. The course frames these ideas using the Cosmic Distance Scale to map what is out there, where it is and the techniques we use to measure it.

Module learning outcomes

At the end of this module successful students will be able to:

  • Understand the role of the Cosmic Distance Ladder to establish the scale and structure of the Universe.
  • Explain the principle techniques used in measuring each 'rung' and compare and evaluate each method.
  • Explain the basic motions of the sky and the effects of the Sun and Moon on the Earth and other planets. 
  • Describe and compare the operation and location of optical and radio telescopes.
  • Explain the techniques of imaging, photometry and spectroscopy and their applicability to various types of astronomical observations.
  • Use the measured properties of stars to determine their intrinsic properties, including their evolution and relationships on a Hertzsprung- Russell diagram.
  • Describe the key stages of stellar evolution and the dominant physical processes that govern them.
  • Discuss the evidence for some of the more exotic constituents of the Universe; dark matter and dark energy. Describe the basic principles of cosmology, the Big Bang and origin and fate of the Universe.

In addition students will:

  • Use commercial office software applications confidently for scientific presentation.
  • Be able to use the library and retrieve information from the library using both paper and online resources.
  • Engage in constructive personal development planning activities.
  • Use computer software (such as Python and Origin) for numerical and graphing applications in physics.
  • Demonstrate “physicist” skills in small group discussions, for example, order-of- magnitude estimations, dimensional analysis, etc.
  • Be aware of ethical issues in physics and astrophysics.

Introduction to Experimental Laboratory

  • Demonstrate good experimental practice, including accurate record keeping,
  • The planning and execution of experiments,
  • The identification, assessment and analysis of errors
  • Write a scientific report using the accepted structure and style


  • Calculate probabilities
  • Write down expressions for binomial, Poisson and normal distributions and understand their applicability
  • Apply the properties of the normal distribution to experimental errors
  • Understand the statistical meaning of standard error


  • Employ problem-solving strategies to develop algorithms
  • Know the difference between declarations, expressions and control statements in programming
  • Modify simple Python programs
  • Use the Python module system to use external libraries
  • Define functions in Python to structure code
  • Evaluate mathematical expressions using built-in math functions
  • Modify 3D visualisation code to display animations

Introductory Python Programming (term 2)

This course introduces problem solving using computers, using Python as the programming language. The most difficult aspect of programming is designing a step-by- step recipe (algorithm) to solve a given problem. This kind of logical problem solving is a useful skill which is highly valued in research and in the commercial world, and which all physicists should learn through practice. Once an algorithm has been designed, it must be implemented in a programming language, which for this course is Python. Python is a modern language which is freely available for Windows, Linux/Unix and Mac OS with extensive documentation, tutorials and extensions available online. It is easy to learn but very powerful, and is increasingly being used commercially and in scientific research. Students will learn how to create programs in the Python language to solve physics problems and then visualise the results in 2D and 3D. The emphasis is on problem solving, and teaching skills which students can then apply to other areas of their study.

Module content

Professional Skills Syllabus

Induction Activities (weeks 1 and 2, term 1):

Introduction to communication skills, study skills, career planning, personal development planning (3 hour lecture). Library: tour of the JB Morrell library (1 hour) and information retrieval exercises. A basic introduction to IT (web, e-mail, etc) and use of Office applications for scientific presentation (3 hours of computer sessions).

Statistics (weeks 4-7, term 1):

Five lectures on basic concepts in probability and statistics, with weekly coursework problems. Covers the notion of probability and binomial, Poisson, and normal probability distributions.

Introduction to Experimental Laboratory

(weeks 2-3, term 1):

Three short workshops on experimental measurement techniques, plotting scientific data, and recording data and analysing errors.

(weeks 4-5, term 1):

A core experiment to be presented in a formal report (see First Year Laboratory Handbook for full details).

Scientific report writing (week 6, term 1):

An introduction to writing scientific reports (1- hour workshop).

Problem solving skills (fortnightly, term 1):

Small group discussions with your supervisor, to help develop “thinking-like- a-physicist” skills such as order of magnitude estimations, dimensional analysis, applying differential equations, and curve sketching and interpretation (5 x 1-hour tutorials).

Introductory Python Programming (term 2)

  • Problem solving strategies and algorithm development
  • Computer programming fundamentals and Python
  • Looping with and while loops
  • Control using if, elif and else
  • Getting input from the user, and printing results
  • Debugging and testing methods
  • Pythons module system and importing libraries
  • Defining functions and using built-in mathematical functions
  • Using Visual Python to produce animations of mechanics simulations

Mapping the Universe Syllabus

The Cosmic Distance Ladder

  • Radar, Parallax, H-R fitting, Cepheids, Cluster fitting, Type 1A SN, Tully-Fisher and Faber-Jackson relationships, Hubble’s Law.
  • The concept of a standard candle and the application of the magnitude scale to determine distances.

Motions of the Sky and Local Effects

  • Coordinates, stellar and planetary motion in the sky
  • Seasons, eclipses and tides
  • Kepler’s laws describing orbits
  • The application of the above to extra-solar planets

Telescopes and Instruments

  • Spectroscopic, photometric and imaging techniques and their applications
  • Principles of reflecting, refracting and radio telescopes and their locations


  • Basic observed and intrinsic properties and relationships on the H-R diagram
  • Basic sequence of birth, evolution and death of high- and low-mass stars
  • Clusters and their properties


  • Basic structure of the Milky Way- matter and dark matter
  • Galaxy classification and general properties


  • Olbers paradox and the cosmological principle
  • The Big Bang, evidence and implications
  • Dark energy and the fate of the Universe


Task Length % of module mark
Induction and laboratory activities
N/A 5
Laboratory reports
N/A 10
Marking of lab books
N/A 5
Physics Practice Questions
N/A 7
Python: assignments totalling
N/A 20
N/A 10
University - closed examination
Mapping the Universe
1.5 hours 43

Special assessment rules



Task Length % of module mark
Induction and laboratory activities
N/A 5
Laboratory reports
N/A 10
Marking of lab books
N/A 5
Python: assignments totalling
N/A 20
University - closed examination
Mapping the Universe
1.5 hours 43

Module feedback

Physics Practice Questions (PPQs) - You will receive the marked scripts via your pigeon holes. Feedback

solutions will be provided on the VLE or by other equivalent means from your lecturer. As feedback

solutions are provided, normally detailed comments will not be written on your returned work, although

markers will indicate where you have lost marks or made mistakes. You should use your returned scripts

in conjunction with the feedback solutions.


Exams - You will receive the marks for the individual exams from eVision. Detailed model answers will be

provided on the intranet. You should discuss your performance with your supervisor.


Advice on academic progress - Individual meetings with supervisor will take place where you can discuss

your academic progress in detail.

Indicative reading

Practical Physics by G L Squires (Cambridge University Press) ***

Python Programming: An Introduction to Computer Science by John Zelle **

Kay, Palen, Smith, Blumenthal: 21 st Century Astronomy

Zeilik M and Gregory SA: Introductory Astronomy and Astrophysics **

Freedman R and Kaufmann WJ: Universe **

The information on this page is indicative of the module that is currently on offer. The University is constantly exploring ways to enhance and improve its degree programmes and therefore reserves the right to make variations to the content and method of delivery of modules, and to discontinue modules, if such action is reasonably considered to be necessary by the University. Where appropriate, the University will notify and consult with affected students in advance about any changes that are required in line with the University's policy on the Approval of Modifications to Existing Taught Programmes of Study.