Carnegie Mellon University

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/wk

Learning 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