Quantum Integer Programming & Quantum Machine Learning II
Course Number: 47785
This course is primarily designed for graduate students (and advanced undergraduates) interested in integer programming (with non-linear objective functions) and the potential of near-term quantum and quantum-inspired computing for solving combinatorial optimization problems.
Degree: PhD
Concentration: Operations Management
Academic Year: 2023-2024
Semester(s): Mini 2
Required/Elective: Elective
Units: 6
Format
Lecture: 100min/wk and Recitation: 50min/wkLearning Objectives
By the end of the semester, someone enrolled in this lecture should be able to:
- Identify the current status of quantum computing and its potential uses for integer programming
- Access and use quantum computing resources (such as DWave Quantum Annealers)
- Set up a given integer program to be solved with quantum computing
- Work in groups collaboratively on a state-of-the-art project regarding applications of quantum computing and integer programming