Course manual 2023/2024

Course content

Programming is an essential skill in any career after your MSc degree. This course teaches you advanced scientific problem-solving skills in Mathematica and Python. Starting from a rudimentary basis (see prerequisites) we will discuss how to import and export data, create data structures, visualize results and investigate numerical recipes to solve differential equations or integral relations.

Short lectures will introduce each topic, but most of the effort is getting hands-on experience through coding exercises. We will cover two popular languages: Mathematica and Python.

We will focus on the following topics in Mathematica:

Getting started (organizing Notebooks), using Lists.
Simple Algebra (differentiation, integration, substitution, Assignments simplification, etc.)
Solving ordinary differential equations; visualizing results with Animate[.] and Manipulate[.]
Constants, Units and external data
Advanced examples

We will focus on the following topics in Python:

Data types, floating point precision, good programming habits
data structures in Python, conditionals, loops, functions, and introduction to computational complexity
NumPy arrays for efficient numerical computing in Python
Numerical resolution of differential equations
Introduction to stochastic simulation

We will also discuss:

Data visualization with MatplotLib
Handling data with Panda

Study materials

Literature

For Python, good references are A Whirlwind Tour of Python and Python Data Science Handbook, by Jake VanderPlas, which are both freely available in their online version.

For Mathematica, a good reference is Using Mathematica for Quantum Mechanics: A Student's Manual, by Roman Schmied, freely available online.

Objectives

Teaching methods

Lecture
Laptop seminar
Self-study

Learning activities

Activity	Hours
Self study	84
Total	84	(3 EC x 28 uur)

Attendance

Requirements concerning attendance (OER-B).

In addition to, or instead of, classes in the form of lectures, the elements of the master’s examination programme often include a practical component as defined in article A-1.2 of part A. The course catalogue contains information on the types of classes in each part of the programme. Attendance during practical components is mandatory.

Assessment

Item and weight	Details
Final grade

The course will be assessed with a pass/fail mark based on submitted assignments and a final computational project.

Assignments

The course will be assessed with a pass/fail mark based on submitted assignments and a final computational project.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Weeknummer	Onderwerpen	Studiestof
1
2
3
4
5
6
7
8

Owner	Master Physics and Astronomy (joint degree)
Coordinator	dr. R.J.C. Spreeuw
Part of	Master Physics and Astronomy, track Advanced Matter and Energy Physics, Master Physics and Astronomy (joint degree), track General Physics and Astronomy,

Programming in Mathematica and Python