• Instructor: Yongshan Ding. Office Hour: Tuesdays 3-4PM (Zoom). Contact information announced on Canvas.
• Course Assistants: To be announced on Canvas.
• Syllabus (general information): PDF
• Canvas (course resources): link
• Ed Discussion (announcement and Q&A forum): Access through Canvas
• Gradescope (assignments and grades): Access through Canvas
• Yale Course Search (registration): Link

This course introduces topics in quantum computer and networking systems in the following ways:

• Lectures. We will introduce the core concepts and techniques. Lectures will be recorded and posted on Canvas.
• Think-Pair-Share (TPS). Following the “think-pair-share” collaborative learning strategy, we will hold in-class discussion sessions where students form teams to understand research papers. Students are expected to form in-class discussion groups and share findings with the class.

There is no required textbook for this course. Instead, we have a list of recommended textbooks and some course readings (which will be updated and linked from the schedule below). Recommended textbooks and references:

• D&C: Quantum Computer Systems, by Ding and Chong. Free access via Yale VPN [link].
• N&C: Quantum Computation and Quantum Information, by Nielsen and Chuang.
• W: Theory of Quantum Information, by Watrous. [link]

Assignments are due on Gradescope (accessed through Canvas) at 11:59PM US Eastern Time unless otherwise indicated on the assignment.

Problem Sets consist of multiple-choice questions and are submitted individually. Each student has a total of two late days for the entire semester, which may be used without notifying the course staff by submitting to Gradescope after the original deadline. Once all late days are used, late submissions will receive a 15% penalty.

• Problem Set 1: Quantum information theory.
• Problem Set 2: Fault tolerant quantum computing.
• Problem Set 3: Quantum memories.

TPS sessions are discussion based and require active preparation and participation. Before each TPS class, students must complete the assigned readings and prepare answers to the pre-distributed discussion questions. During the session, students will work in groups to discuss ideas, consolidate answers, and share key points with the class. Each group must submit one TPS report as a single PDF by the end of the same day. The report should list all group members at the beginning, and each paragraph should clearly indicate who wrote it or contributed to that discussion.

• TPS 1: Surface code experiments.
• TPS 2: qLDPC codes.
• TPS 3: Quantum advantage.
• TPS 4: Noise resilience of QRAM.
• TPS 5: Dirty ancilla qubits.
• TPS 6: Quantum repeater networks.

Students in CPSC 5490 are required to conduct a final project on selected topics. More information will be provided on Ed.

• Online/In-class discussion: 15% .
• Problem Sets (3): 15% + 15% + 15% = 45%
• TPS reports (7): 40% (for CPSC 4490 students), 20% (for CPSC 5490 students).
• Project (for CPSC 5490 students only): 20%

Engagement with the course. There are multiple ways to engage with the course both inside and outside of the classroom:

• We will have frequent group discussions during live lectures to enhance learning and student interactions.
• Lecture recordings will be posted on Canvas to allow students to review offline at their own pace.
• Hybrid office hours provide the students with flexibility in ways to reach out to the instructor and the course staff.
• Students are encouraged to use Ed Discussion to ask questions after class.

Collaboration policy: To facilitate learning, collaboration on the assignments is encouraged. A discussion may take place in a small group (on a whiteboard or on a scratch paper, etc.), but notes or recordings of the discussion are prohibited. All assignments should be written up on one’s own after sufficient time (i.e., at least two hours) has elapsed since any discussion. You must list all your collaborators on every assignment. If you have used external reference materials, please also note this on the assignment. The objective is to demonstrate that you can (re)create a solution on your own. It is prohibited, however, to share solutions or provide hints to other students after you have already arrived at the solution. Take a moment to familiarize yourself with Yale’s Academic Integrity Policy, if you have not done so already. If you have any questions about what does or does not constitute plagiarism, ask! Plagiarism is a serious offense and will not be treated lightly. Fortunately, it is also easy to avoid and if you are careful about giving credit where credit is due you should not run into any problems.

Generative AI Tools Policy. Unless stated otherwise, you may use generative AI (GAI) as writing and coding assistants, as long as you give proper credit. You can use AI tools to help you generate code or designs, or to polish writing you’ve already drafted. However, for TPS readings, relying on AI summaries alone is not sufficient, as they may miss important details. Your TPS responses should reflect your own understanding and thinking. Keep in mind that AI tools aren’t perfect and can make mistakes or “hallucinate.” That’s why every submission, AI-assisted or not, needs to be carefully checked and tested. Bottom line is: you are fully responsible for what you submit. When in doubt, don’t hesitate to reach out!

Well-being. The well-being of students is important to us at Yale. If you or anyone you know are experiencing any stress, anxiety, or isolation, please consider reaching out to a friend, family member, or faculty you trust. If you have a personal emergency that might impact your work in the class, please let Yongshan know so that appropriate arrangements can be made. You may also consider some helpful resources available on campus -- The Good Life Center is the official student wellness center of Yale University and is supported by the Yale Well Initiative.

A tentative course schedule can be found below. Please refresh page frequently for updates. All lectures are held in person unless otherwise indicated.

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Monday, 01/12

Lecture 1: Overview

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Wednesday, 01/14

Lecture 2: Quantum States, Circuits, and Measurements

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Monday, 01/19

Lecture: No class (MLK Jr Day)

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Wednesday, 01/21

Lecture 3: Density Operators and Quantum Probability

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Friday, 01/23

Lecture 4: Quantum Information Theory: Basics

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Monday, 01/26

Lecture 5: Classical Simulation of Quantum Circuits
Due: Assignment 1 at 11:59PM ET on Gradescope

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Wednesday, 01/28

Lecture 6a: QPU Technologies and ISAs - Part A

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Monday, 02/02

Lecture 6b: QPU Technologies and ISAs - Part B

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Wednesday, 02/04

Lecture 7: Quantum Error Correction

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Monday, 02/09

Lecture 8: Surface Code

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Wednesday, 02/11

TPS 1: Surface Code Experiments
Due: TPS 1 report at 11:59PM ET on Gradescope

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Monday, 02/16

Lecture 9: Quantum Fault Tolerance

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Wednesday, 02/18

Lecture 10: Teleportation and Magic States
Due: Assignment 2 at 11:59PM ET on Gradescope

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Monday, 02/23

TPS 2: qLDPC Code
Due: TPS 2 report at 11:59PM ET on Gradescope

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Wednesday, 02/25

Lecture 11: Hamiltonian Simulations

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Monday, 03/02

TPS 3: Quantum Advantage
Due: TPS 3 report at 11:59PM ET on Gradescope

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Wednesday, 03/04

Lecture 12: Quantum Memory and Storage

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Monday, 03/09

Lecture: No class (Spring recess)

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Wednesday, 03/11

Lecture: No class (Spring recess)

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Monday, 03/16

Lecture: No class (Spring recess)

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Wednesday, 03/18

Lecture: No class (Spring recess)

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Monday, 03/23

Lecture: Canceled

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Wednesday, 03/25

Lecture 13: Quantum Random Access Memory

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Monday, 03/30

TPS 4: Noise Resilience of QRAM
Due: TPS 4 report at 11:59PM ET on Gradescope

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Wednesday, 04/01

Lecture 14: Quantum Ancillary Memory

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Monday, 04/06

TPS 5: Dirty Ancilla Qubits
Due: TPS 5 report at 11:59PM ET on Gradescope

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Wednesday, 04/08

Lecture 15: Quantum Networking Systems
Due: Assignment 3 at 11:59PM ET on Gradescope

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Monday, 04/13

Lecture 16: Flying Qubits

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Wednesday, 04/15

TPS 6: Quantum Repeater Networks
Due: TPS 6 report at 11:59PM ET on Gradescope

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Monday, 04/20

Showcase: Project Presentations

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Wednesday, 04/22

Showcase: Project Presentations

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Monday, 04/27

Due (CPSC 5490 students only): Project Report at 11:59PM ET on Gradescope

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