QUANTUM ALGORITHMS AND ERROR CORRECTION
Dive into the quantum computing stack by starting with real-world applications and progressing through the essential components needed for fault-tolerant quantum computers. Learn about key areas such as quantum algorithms, and advanced quantum error correction. Explore algorithms for scientific applications, including quantum phase estimation and the HHL algorithm, and examine the derivation, trade-offs, and implementation of sophisticated error correction techniques. Learn to analyze and estimate the full-stack quantum resources required for novel quantum algorithms by utilizing classical computational tools, in order to develop and evaluate scalable, high-utility quantum computing solutions.
Prerequisites & course information
Requisites: PHYSICS 709 Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Spring 2026 Learning Outcomes: 1. Summarize how to estimate quantum resources, starting from a high-utility application, through quantum algorithms, error correcting codes, and physical qubit parameters. Audience: Graduate 2. Discuss quantum algorithms for scientific applications, including quantum phase estimation, time-stepping schemes (Trotterization, qubitization), initial state preparation, and the HHL algorithm. Audience: Graduate 3. Describe advanced quantum error correction codes, their derivation, trade-offs between different codes, physical overheads, decoders, and threshold calculations. Audience: Graduate 4. Use and develop classical computational tools to study various aspects of quantum computers. Audience: Graduate Learning Outcomes: 1. Summarize how to estimate quantum resources, starting from a high-utility application, through quantum algorithms, error correcting codes, and physical qubit parameters. Audience: Graduate 2. Discuss quantum algorithms for scientific applications, including quantum phase estimation, time-stepping schemes (Trotterization, qubitization), initial state preparation, and the HHL algorithm. Audience: Graduate 3. Describe advanced quantum error correction codes, their derivation, trade-offs between different codes, physical overheads, decoders, and threshold calculations. Audience: Graduate 4. Use and develop classical computational tools to study various aspects of quantum computers. Audience: Graduate
Sources
- Course catalogue ↗2026-2027