General Information

An introduction to quantum computing for students who have not necessarily had prior exposure to quantum mechanics. This course is intended for physicists, electrical engineers, and computer scientists. Topics include: foundational algorithmic building blocks and quantum algorithms; variational quantum algorithms (for physics simulation and for combinatorial optimization); quantum machine learning; basic physics of quantum computing hardware implementation. There will be substantial programming exercises implementing quantum algorithms to run on simulators and quantum computers in the cloud.

Outcome 1: Students will be able to understand and have the knowledge to implement core quantum algorithms.

Outcome 2: Students will be able to apply some of the quantum algorithms studied to new application problems.

Outcome 3: Students will be able to explain key challenges in constructing quantum computers and in running quantum algorithms on current quantum computers.

Prerequisites

Prerequisite: MATH 2940 or equivalent, and CS 1110 or equivalent exposure to Python. Co-meets with AEP 5310.

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