# Introduction¶

These pages contain a description of AST4310 and additional resources. The pages at the University web site will still be updated (in particular the messages), but the bulk of the materials will be linked here.

## Practicalities¶

• Four hours of lectures and two hours of exercise classes per week (see calendar)
• Classes will be held in person unless otherwise directed
• Given COVID-19 rules, students in quarantine/isolation will be able to participate remotely (see also Software and Tools)
• See separate page for syllabus and literature
• Visualisations and other in-lecture exercises will be shared under resources

## Communication¶

• We will use channel #AST4310 on element.io for communication. Element is a decentralised, encrypted chat network, that works similar to Mattermost or Slack (minus the surveillance and data harvesting).
• If you don't already have an account on Element, please create a free matrix.org account. To ensure anonymity it is recommended you chose a username that does not reveal your identity.
• The #AST4310 channel is invite-only and end-to-end encrypted, so when creating an account make sure you remember the security key - you will need it to join the channel.

## Assessment¶

The final grade is determined by an assessment of six projects. Project 1 is compulsory but only pass/fail, so it won't factor in the final grade. The following table lists deadline for handing in each project, how much each project weighs in the final grade, and the topic of each project. More details can be found under projects.

Project 1 04.09.2020 Pass/fail Basic spectral line formation
Project 2 18.09.2020 10% Line strengths and curve of growth
Project 3 02.10.2020 15% La Palma
Project 4 23.10.2020 25% Solar stratification and continua
Project 5 13.11.2020 25% LTE line formation
Project 6 11.12.2020 25% Different options

## Required software and tools¶

This course will have a strong computational component. Computations are not the end goal, but they will be an important tool to understand the topics we will cover. Research in astrophysics is becoming more and more computational; the course will equip students with the strategies and skills to deal with modern astrophysical problems.

Students are expected to have their own laptops, and bring them to classes (including lectures!). The assignments and projects can also be run on the linux machines at the Institute. This may be especially helpful for computationally-heavy calculations that need more compute power.

More details can be found under software and tools.

The projects are in Jupyter notebook format. Only two programming languages are allowed: Python or Julia. In the classes we will make extensive use of Jupyter lab. In addition, some basic familiarity with git is required - it will be used mostly to download and update assignments.