¹û¶³Ó°Ôº

Outline:

This module provides an introduction to basic specialist skills required by the practicing astrophysicist,Ìýthrough a revision of basic statistics used in astrophysics, the handling of concepts relevant toÌýinstrumentation and the effect it can have on astrophysical data and an experiment (selected amongÌýa range available) at ¹û¶³Ó°ÔºO together with an introduction to Numerical Methods and the Python programming language

Aims:

All Lab-based modules within the Department contribute to the continuing development of students’Ìýpractical skills, extending throughout the four/three years of the MSci/BSc degrees. Collectively theÌýcourses have the overall aim of equipping the student with those practical skills which employersÌýexpect to find in graduates in physics whether they are employed in scientific research orÌýdevelopment, or in a wider context. Intended mainly for students following the Astrophysics degree programme, PHAS0020 aims to build on and extend the skills acquired in the first-year lab course, focusing more on the computing aspect and the way in which astrophysical data is affected by the instrumentation which acquires it.

Intended Learning Outcomes:

By the end of the module the students should have:

• Improved skill and confidence in the acquisition and analysis of experimental data through the performance of experiments and exercises beyond the introductory level encountered inÌýthe first-year lab course.
• Improved ability to record their work concisely and precisely, through repeated practice guided by frequent feedback from teachers
• Improved appreciation of the validity of the data obtained and consequent results; the abilityÌýto be able to identify the major sources of uncertainties; and to propagate measurementÌýuncertainties through to estimated uncertainty on final results
• Improved ability to record measurements, analysis, and results in concise, but complete,Ìýaccurate reports
• Gained greater insight into some of the phenomena treated in astronomy lecture courses inÌýyears 1 and 2 by performing related experiments and exercises
• Grasped basic principles of computer programming in a relevant language to a range ofÌýphysical problems and data-analysis tasks

Teaching and Learning Methodology:

In the computing sessions, students will work individually with python-based tools to familiarize with a wide range of data analysis and statistical tools, which they will subsequently put to use with a range of astronomical programs and libraries. Sessions are designed to provide a tool hand-over element where students learn to use specific data analysis tools through the use of python code and a subsequent application element where students combine their incremental coding language with each session-tool to expand and apply this to a different range of astronomical problems.

In the practical sessions, students work by following prescriptive scripts. Great emphasis is placed on the formation of good habits in the keeping of a laboratory notebook for which students are given detailed advice. Demonstrators not only help students understand experiments and observations and overcome difficulties as they arise, but also inspect student notebooks to provide instant correctives to any bad practice arising. The course will be run from the ¹û¶³Ó°Ôº Observatory.

Self-study: In addition to timetabled hours it is expected that you engage in self-study in order to master the material. This can take the form of studying the material, practicing problem questions, preparing for laboratory sessions, writing up reports and further reading in textbooks and online.

Indicative Topics:

Treatment of Experimental Data: This module reinforces and extends the module given in the First Year and examines some more practical aspects of good data-taking techniques to make students awareÌýthat bad practice in taking data can affect the precision of results.

Computing: The computing element of the module takes place mostly in the first half of term. UsingÌýthe Jupyter Notebook as the main format, Python programming skills acquired during PHAS0007 willÌýbe developed and extended, using structured coursework assignments based on a range ofÌýastronomical examples related to lecture and laboratory course material. The module will cover a rangeÌýof topics in advanced data analysis, numerical analysis techniques and computational physics.

Experimental mini-group-project: An experiment is chosen among a range of available experimentsÌýintended to develop some basic techniques of laboratory astrophysics instrumentation. Data takingÌýand analysis will put in practice things learned through the use of python in the first part of the moduleÌýwith a final guided write-up in LaTeX.