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Simulation and Modeling in Astrophysics (AMUSE)


Admission requirements

  • Bachelor's degree in Astronomy and/or Physics

  • Solid proficiency in programming

  • Experience with programming in LINUX work environment


During this course you will learn how to perform research with existing computational tools and simulation codes. This will be done using the Astrophysics Multipurpose software Environment (AMUSE) software. You will learn how to set up a computer experiment, write the code to carry out the simulations, perform the calculations, collect and analyze the data, and critically assess the results.

Students, in groups of two or three, will work on their joined projects, and report on the results by written report and a presentation.

The final project is chosen in discussion with the teacher from a wide range of topics. From a computational point of view the topic should generally include at least two fundamental physical phenomena:
gravitational dynamics, hydrodynamics, radiative transfer, or stellar astrophysics.

The work will be carried out using AMUSE to perform a number of simulations to study astrophysical phenomena. The course ends with a presentation and report on the final project.

Course objectives

How to perform, judge, select and adapt the proper numerical tools for conducting your own research, and how to validate the work of others.


See Astronomy master schedule

You will find the timetables for all courses and degree programmes of Leiden University in the tool MyTimetable (login). Any teaching activities that you have successfully registered for in MyStudyMap will automatically be displayed in MyTimeTable. Any timetables that you add manually, will be saved and automatically displayed the next time you sign in.

MyTimetable allows you to integrate your timetable with your calendar apps such as Outlook, Google Calendar, Apple Calendar and other calendar apps on your smartphone. Any timetable changes will be automatically synced with your calendar. If you wish, you can also receive an email notification of the change. You can turn notifications on in ‘Settings’ (after login).

For more information, watch the video or go to the 'help-page' in MyTimetable. Please note: Joint Degree students Leiden/Delft have to merge their two different timetables into one. This video explains how to do this.

Mode of instruction

  • Lectures

  • Practical classes

  • Presentations

Assessment method

  • Homework assignments

  • Team projects

  • Final project presentation

Reading list

Course material is available online via the git wiki, these include:


As a student, you are responsible for registering on time, i.e. 14 days before the start of the course. This can be done via Mystudymap. You do this twice a year: once for the courses you want to take in semester 1 and once for the courses you want to take in semester 2. Please note: late registration is not possible.

Registration for courses in the first semester is possible from July; registration for courses in the second semester is possible from December. First-year bachelor students are registered for semester 1 by the faculty student administration; they do not have to do this themselves. For more information, see this page.

In addition, it is mandatory for all students, including first-year bachelor students, to register for exams. This can be done up to and including 10 calendar days prior to the exam or up to five calendar days in case of a retake exam. You cannot participate in the exam or retake without a valid registration in My Studymap.

Extensive FAQ's on MyStudymap can be found here.


Lecturer: Prof.dr. S.F. (Simon) Portegies Zwart


The course starts with a test on basic knowledge and skills essential for successfully finishing the course. The result of this test will be used to judge the suitability of the candidate for the course, and may result in an advice to the student to stop the course work.


  • AMUSE in general

  • Gravitational dynamics

  • Stellar evolution

  • Hydrodynamics

  • Code coupling strategies

  • Project management

  • Visualization

  • Presentation and reporting

  • Algorithms

  • Python

  • Software sustainability

  • High-performance computing

Soft skills
In this course, students will be trained in the following behavior-oriented skills:

  • Problem solving (recognizing and analyzing problems, solution-oriented thinking)

  • Analytical skills (analytical thinking, abstraction)

  • Critical assessment (asking questions, assumption validation)

  • Creativity (resourcefulness, lateral thinking)

  • Collaboration (extreme programming, joined research)

  • Management of their own research endeavor

Brightspace and Git

Brightspace will be used to communicate with students. But to share lecture slides, homework assignments, or any extra materials, we will be using git.