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Numerical Recipes in Astrophysics

Vak
2021-2022

Admission requirements

Students should be experienced with programming in either C/C++ or Python. Knowledge of calculus at the bachelor’s level is also required. In terms of the Leiden Astronomy bachelor's curriculum, the prerequisites for this course are Programming NA and Analyse 3 (NA).

Description

In this course you will learn how and why some of the most powerful and broadly used algorithms in astrophysics work and gain a deeper understanding of numerical methods.This will allow you to identify the right tool for the job for whatever computational problem you may encounter in astrophysics, and to program more effectively, whether you are fitting data, sampling a distribution, integrating orbits or optimizing your computational model.

During the lectures we will discuss numerics and consider and derive specific algorithms that are useful in astrophysics. During the problem classes students will work together on applying this knowledge to a computational problem through coding.

The topics covered in the course include:

  • Numerical error and precision

  • Solving linear equations

  • Solving differential equations

  • Inter- and extrapolation

  • Numerical integration and differentiation

  • Random numbers and distribution sampling

  • Root finding, minimization and maximization

  • • Fast Fourier transforms and applications

  • Modelling data

Course objectives

Upon completion of this course you will be able to judge which numerical algorithm or tool is right for any computational problem typically encountered in
astrophysics.

In specific, after this course, you will be able to:

  • Evaluate the outcomes of computational codes

  • Construct an efficient computer program

  • Solve a wide array of astrophysical problems

Soft skills

After completing this course you will be able to:

  • Work collaboratively on numerical problems

  • Program effectively

Timetable

See Astronomy master schedules

Mode of instruction

  • Lectures

  • Exercise classes

Assessment method

Brightspace

Brightspace will be used to communicate with students and to share lecture slides, homework assignments, and any extra materials. To have access, you need a student ULCN account.

Reading list

  • Numerical Recipes: The Art of Scientific Computing, Third Edition (W.H. Press, S.A. Teukolsky, W.T. Vetterling, B.P. Flannery), ISBN: 9780521880688 (optional)

Registration

Via uSis. More information about signing up for your classes can be found here. Exchange and Study Abroad students, please see the Prospective students website for information on how to apply.

Contact information

Lecturer: Dr. M.P. (Marcel) van Daalen
Assistants: Dario Campisi, Folkert Nobels