2020 Spring NTHU iPhD Program Intensive Course

Quantum machine learning 量子機器學習

Instructor: Dr. Alexey Melnikov (Postdoctoral Research Scientist, Department of Physics, University of Basel, Switzerland)

Schedule of the Intensive Course:

     April 10, 18:00-21:00

     April 11, 10:00-12:00、14:00-18:00

     April 17, 18:00-21:00

     April 18, 10:00-12:00、14:00-18:00

Venue: Room 205, B side, General Building II

Credit: 1

Course Number: IPHD5002

Course Description:

     What is the role of quantum physics in machine learning and, vice versa, the role of machine learning in quantum physics? In this course, both questions will be addressed by connecting quantum physics and machine learning in different ways.

     1. Objectives:
     learn about the interplay, both fundamental and practical, between machine learning and quantum physics.
     2. Course Contents:
       (1) Introductory session: basics of quantum physics
       (2) Introductory session: basics of machine learning
       (3) A subject of quantum machine learning
       (4) Quantum-physics-inspired reinforcement learning
       (5) Programming session: reinforcement learning in Python
       (6) Quantum-enhanced reinforcement learning
       (7) Designing quantum experiments with reinforcement learning
       (8) Improving Bell inequality violation with reinforcement learning
       (9) Programming session: Bell nonlocal correlations in Python
       (10) Quantum walks analysis with supervised learning
       (11) Programming session: quantum dynamics simulation in Python
       (12) Programming session: convolutional neural networks for quantum dynamics classification in Python
     3. Requirements:
     interest in machine learning, interest in quantum physics, at least some programming experience.

This course is offered in English, please select it in academic system directly.