RESEARCH TECHNIQUES IN ASTRONOMY - 2023/4
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
Mathematics & Physics
Module Leader
GUALANDRIS Alessia (Maths & Phys)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 6
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 117
Lecture Hours: 11
Laboratory Hours: 22
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:
Data analysis: Handling large astronomic data files, extracting physical quantities of interest, image analysis, copying with noise and systematic errors; Imaging; Spectroscopy.
- Numerical methods: Sorting, histograms, distributions.
Statistics: Error analysis, probability density distributions and moments; Sampling, fitting, comparing data and models.
Assessment pattern
| Assessment type | Unit of assessment | Weighting |
|---|---|---|
| Coursework | Imaging coursework | 30 |
| Coursework | Spectroscopy coursework | 30 |
| Coursework | Statistics coursework | 40 |
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 three pieces of coursework:
Imaging coursework
Spectroscopy coursework
- Statistics coursework
Formative assessment and feedback
Detailed written feedback will be provided for each pieace of submitted coursework. 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 | ||
| 002 | Understand basic numerical methods for astrophysical research like integration and root finding | KCPT |
| 005 | Understand and apply key statistical concepts like error analysis, sampling and fitting | KCPT |
| 004 | Analyse and manipulate photometric and spectroscopic data sets to extract physical properties | KPT |
| 001 | Design and construct programs and scripts in the modern and flexible Python language to perform tasks on real or simulated data | KCPT |
| 003 | Visualise real or simulated data | PT |
Attributes Developed
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
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
https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: PHY3054
Programmes this module appears in
| Programme | Semester | Classification | Qualifying conditions |
|---|---|---|---|
| Mathematics and Physics MPhys | 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 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 |
| Physics with Quantum Technologies MPhys | 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 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 |
| Physics with Quantum Technologies 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 MSc | 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 |
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 2023/4 academic year.