Lecture and tutorial classes

Machine learning in quantum physics

(Winter term 2018/2019)

Quantum machine learning is an emerging research field. This first course focuses on the subfield where classical machine learning is applied in quantum physics. The goal of this course is to provide the students with the necessary skills to understand the main ideas and some details of the ongoing research.

Content

  1. Introduction to artificial neural networks and deep learning

  2. Applications in quantum physics

Exercises and other files will be uploaded here.

Formal things

Lecture and tutorial class (Übung) have been moved to

  • Tuesday 8:30am, room 25.33.00.61 (lecture)

  • Friday 8:30am, room 25.33.00.61 (tutorial class)

  • Prerequisites for attending are basic knowledge

    • Linear algebra,

    • Calculus, and

    • Quantum mechanics.

  • There will be a written exam at the end of the course. Time an place will be announced here.

  • Assignments (click here) will be uploaded every two weeks. The solutions to the assignment sheets need to be handed in. As a prerequisite for the exam, at least 70% of the assignment sheets need to be finished. There will be no corrections but the solutions will be discussed in the tutorial classes.

Note: Due to an unexpected high number of course participants student presentations turned out not to be feasible.

Preliminary schedule: 30 lectures (VL) and problem classes (Ü)

October (8)

  • 09 | VL (Motivation, course outline, formalities), exercise 1 handed out

  • 12 | Ü (Introduction, student questions & discussion)

  • 16 | VL (General ML & statistics)

  • 19 | Ü due date: discussion of exercise 1, exercise 2 handed out

  • 23 | VL (General ML & statistics)

  • 26 | Ü, (Student questions & discussion)

  • 30 | VL (General ML & statistics); due date: exercise 2, exercise 3 handed out

November (8)

  • 02 | Ü (discussion of exercise 2)

  • 06 | VL (DL)

  • 09 | Ü (Student questions & discussion)

  • 13 | VL (DL); due date: exercise 3, exercise 4 handed out

  • 16 | Ü (discussion of exercise 3)

  • 20 | VL (DL)

  • 23 | Ü (Student questions & discussion)

  • 27 | VL (RBMs); due date: exercise 4, exercise 5 handed out

  • 30 | Ü (discussion of exercise 4)

References