RESEARCH TECHNIQUES IN ASTRONOMY - 2018/9

Module code: PHY3054

Module Overview

In this module, students will learn key methods adopted in astrophysics to carry out advanced research: scientific computing, statistics and data analysis. Much of the course develops highly transferrable skills that apply to science research in general. The goal is to ensure that students are well-prepared for either their research year or their future careers.

Module provider

Physics

Module Leader

GUALANDRIS A Dr (Physics)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 6

JACs code: F500

Module cap (Maximum number of students): N/A

Module Availability

Semester 1

Prerequisites / Co-requisites

The module will assume prior knowledge equivalent to the following modules. If you have not taken these modules you should consult the module descriptors – Introduction to Astronomy (PHY2071)

Module content

Indicative content includes:


Scientific computing:

a first program in python, reading and writing data, visualising data, scripting tasks, numerical integration, differentiation, root finding
simulation techniques  i.e. N-body simulations, Monte Carlo simulations


Statistics:

Bayesian vs frequentist statistics, likelihood functions, distributions and moments, fitting, comparing data and models, error analysis


Data analysis

Handling  large data files, extracting physical quantities of interest, image analysis, copying with noise and systematic errors.




 

Assessment pattern

Assessment type Unit of assessment Weighting
Coursework COURSEWORK 50
Examination FINAL EXAM 50

Alternative Assessment

None.

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate understanding of the basic principles of python programming and scripting, statistics and data analysis, as detailed in the learning outcomes.

 

Thus, the summative assessment for this module consists of 1 piece of coursework and a final exam:



Coursework on scientific programming, scripting and simulation techniques (deadline week 8)


Final exam

 

For coursework the students will submit a report including a description of the problem and a critical discussion of the results obtained, and the original code developed for the task.



 

Formative assessment and feedback

Formative assessment consists of 1 piece of coursework (Coursework 0) on python programming and scripting (deadline week 5), for which the students will receive detailed feedback. Additional feedback will be provided during lab sessions by means of verbal feedback from the academics.

 

Module aims

  • Provide a clear perspective of how astrophysical research is conducted
  • Provide an introduction and hands-on experience of numerical tools used in scientific research

Learning outcomes

Attributes Developed
1 Design and construct programs and scripts in the modern and flexible Python language to perform tasks on real or simulated data KCPT
2 Understand basic numerical methods for astrophysical research like integration, differentiation and root finding KCPT
3 Visualise real or simulated data and prepare graphics and animations for presentations PT
4 Understand and apply key statistical concepts like Bayesian vs frequentist statistics, error analysis, fitting, comparison between data and models KCPT
5 Analyse and manipulate large data sets to extract physical properties KPT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Overall student workload

Lecture Hours: 11

Laboratory Hours: 22

Methods of Teaching / Learning

The learning and teaching strategy is designed to help students gain a basic understanding of the main research techniques used in astrophysics and prepare them for a research year or future career in science.

 

The learning and teaching methods include:



11 hours of lectures (1h/week)


22 hours of computational lab (2h/week)



 

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

Reading list for RESEARCH TECHNIQUES IN ASTRONOMY :

Programmes this module appears in

Programme Semester Classification Qualifying conditions
Physics BSc (Hons) 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics with Nuclear Astrophysics BSc (Hons) 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics with Astronomy BSc (Hons) 1 Compulsory A weighted aggregate mark of 40% is required to pass the module
Mathematics and Physics MPhys 1 Optional A weighted aggregate mark of 40% is required to pass the module
Mathematics and Physics BSc (Hons) 1 Optional A weighted aggregate mark of 40% is required to pass the module
Mathematics and Physics MMath 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics with Quantum Technologies BSc (Hons) 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics MPhys 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics with Quantum Technologies MPhys 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics with Nuclear Astrophysics MPhys 1 Optional A weighted aggregate mark of 40% is required to pass the module
Physics with Astronomy MPhys 1 Compulsory A weighted aggregate mark of 40% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2018/9 academic year.