ASP2064 · Computation and data analysis in astrophysics

Overview

In this unit, you will be introduced to the computational and data analysis techniques used to turn modern astronomical observations into physical understanding. You will work with real astrophysical datasets (e.g., imaging, spectra, and time-domain data) to clean, visualise, model, and interpret measurements while quantifying uncertainty and assessing limitations. Emphasis is placed on building reproducible workflows using contemporary scientific computing practices, enabling students to develop robust and transferable skills for later astrophysics study and research. The unit culminates in an open-ended analysis task where you will communicate results in a professional scientific style.

Areas of study: Physics Astrophysics

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. Develop and implement structured, efficient, and well-documented code to address problems in astrophysics, using appropriate programming strategies, numerical libraries, and workflow design;
2. Employ key numerical algorithms, probability concepts, and statistical models to extract physical insights from data, estimate parameters, and evaluate uncertainties;
3. Critically evaluate observational data for noise, bias, artefacts, and systematic effects, and apply standard techniques for data cleaning, calibration, and validation;
4. Identify sources of error in astrophysical measurements, apply methods for propagating uncertainties through analytical and computational models, and interpret their impact on scientific conclusions;
5. Construct and apply computational forward models of astrophysical systems to predict observable quantities and compare theoretical expectations with real data;
6. Present complex astrophysical and data-driven concepts clearly and accurately for audiences with varying levels of scientific background.

Workload

• You will have 10 contact hours per fortnight, consisting 8 hours of workshop and 2 hours of applied classes. • 14 hours per fortnight will consist of self-study activities including working on group projects.

Student experience, not official rules. Nothing here changes what the Handbook says.