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This course is an introduction to modern quantum programming for students who want to familiarize with quantum computing technologies and learn about a new paradigm of computation.

We will review:

• Quantum mechanics basics
• Circuit model of quantum computation
• Quantum programming languages
• Quantum algorithms for long-term applications
• Quantum algorithms for mid-term applications
• Benchmarking QPUs

A physics and quantum mechanics background is not required, but you will need an understanding of linear algebra at the level of the intro courses. Moreover, you will need some familiarity with computer programming as this course is hands on using open source Python packages for working with publicly available quantum processors.

One lecture per week. 8:00 – 12:00, Friday:

• 21-28/02/20
• 13-20-27/03/20
• 3-10-17-24/04/20

• Quantum Computation and Quantum Information: 10th Anniversary Edition by Michael A. Nielsen and Isaac L. Chuang
• Quantum Algorithm Implementations for Beginners

Complementary readings will be posted online with the syllabus for each lecture. These are critical.

Final placement in the class will be determined by the following formula: 0.15 H + 0.6 P + 0.25 FP

• H is your score on the first written homework assignment.
• P is the weighted average grade on the three programming projects.
• FP is the score on your final project.

• Homework #1 (due date: 13/03/20)
• Project #1: Benchmarking a quantum computer (due date: 05/04/20)

• Github: https://github.com/bfedrici-phd/QC-2020-CPE
• Slack: https://qc-2020-cpe.slack.com