COMP 193/293: Introduction to Quantum Computing (Fall 2026)
Course Description
his course is a comprehensive exploration of the foundations and practical applications of quantum computing. The course offers students a rigorous examination of quantum computing principles, focusing on hands-on experience, coding, simulation, and real-world implications. Through practical exercises, students will develop a profound understanding of key concepts such as qubits, quantum gates, superposition, and entanglement. Practical implementation is emphasized throughout the course. Topics including quantum networking and secure communication using quantum computing are explored. The course also covers essential quantum algorithms, such as the Deutsch-Jozsa algorithm, quantum search algorithms, integer factorization algorithms, etc.
Prerequisites: Completion of Fundamental Skills and COMP 053
with a "C-" or better.
When enrolling in this course, you should be relatively proficient in using Java.
In addition to being a competent Java programmer, you should have an understanding of
common data structures, e.g., classes, arrays, lists, etc. We will use Strange Framework
to develop quantum circuits. Beforehand knowledge of Strange Framework is not required.
Website: Syllabus, Canvas LMS
Credits: 4 units
Course Catalog: https://catalog.pacific.edu/search/?search=comp+293&caturl=%2F
Administration
Instructor: Sepehr Amir
Email: samir1@pacific.edu
Class time/location: TR 13:00 – 14:20, Chambers 113
Office hours: TR 12:00 – 1:00, Chambers 122
Teaching Assistant: N/A
Email: N/A
Learning Objectives
The vision for this course is: What do I, as a computer scientist, need to understand about the principles of quantum computing and what are the different features of quantum computing that I may leverage using quantum computers, once they are publicly available?
You will have many different opportunities to gain this knowledge through:
- Labs
- Getting exposed to state-of-the-art advances in QC
- Presentations
- Lecture videos
- Class discussions, quizzes, and reading assignments
After taking this course, you should be able to:
- Differentiate quantum computing from classical computing.
- Understand the mathematical underpinnings of quantum computing enough to help in practical scenarios.
- Use quantum simulators to construct quantum circuits.
- Understand the basics concepts in quantum computing, including qubits, superposition, entanglement, quantum gates, etc. in practical settings.
- Understand well-known quantum algorithms, including Grover's search algorithm, Deutsch-Jozsa algorithm, quantum transportation algorithm, etc.
- Use quantum computing knowledge in designing new quantum algorithms.
University of the Pacific Core Competencies: This course reflects the following university‑wide core competencies:
- Critical Thinking
- Information Literacy
- Quantitative Reasoning
Outcomes for COMP program: Assessed outcomes per ABET:
- Outcome 1: Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions.
- Outcome 2: Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program's discipline.
- Outcome 6: Apply computer science theory and software development fundamentals to produce computing-based solutions.
Course Material
We will use the following textbook along with additional resources that are referred through the semester:
- Quantum Computing in Action by Johan Vos, Manning Publications Co., 2022.
Slides, assignments, and supplementary material will be posted on Canvas.
Major topics include:
- Mathematical foundationsof quantum computing
- Strange Framework, as a quantum simulator
- Basics of quantum computing
- Quantum networking, and secure communication
- Quantum algorithms including Deutsch-Jozsa and Grover search algorithm
Grading and Attendance Policy
Grades are assigned on the scale below:
| A | A- | B+ | B | B- | C+ | C | C- | D+ | D | F |
|---|---|---|---|---|---|---|---|---|---|---|
| [93,100] | [90,93) | [87,90) | [83,87) | [80,83) | [77,80) | [73,77) | [70,73) | [67,70) | [60,67) | [0,60) |
Final grades are based on:
- Reading assignments: 0%
- Quizzes: 10%
- Labs: 25%
- Class activities: 30%
- Presentations: 15%
- Exams: 20%
Attendance:
- Given the active learning format of this course, attendance and active participation are mandatory. Each class session includes a Class Activity assignment worth 30% of the course grade. Absence from a session will result in a zero for that day's activity, with no make-up opportunities.
- Students are expected to arrive prepared, having completed all required work (including the assigned reading, lecture video, and quiz for that session) before class begins. Failure to do so may impact both participation and overall performance.
- You will only be allowed two excused or unexcused class misses during the semester. Excuses for professional, academic or athletic activities must be approved by the instructor in advance.
- Students missing a class are responsible for making up the material studied in that class on their own. Students are responsible for being aware of any announcements made during their absence.
Exams
3-4 exams will be conducted during the semester. The schedule will be announced in class and content and format will be discussed prior to the exams. Make up exams will only be scheduled in emergency situations.
Assignment Guidelines
Release and Submission
- Reading/Watching Assignments: These assignments will be released on the course Canvas page at most one or two days before each lecture session. Students must study/watch the referred material before each class session. There are not any submissions for reading assignments, however it is highly recommended to follow these assignments before each lecture session in order to be prepared for classroom activities. Reading/Watching assignments are considered as individual efforts.
- Quizzes: Each session comes with a brief quizz (5-10 minutes) that reflects on the material covered in the reading/watching assignment associated with that class session. Quizzes are published and automatically graded in Canvas. They are due at the beginning of each class session. Quizzes are considered as individual efforts.
- Labs: Labs will be released on the course Canvas page at latest at the beginning of each lecture session. Submissions after 11:59PM of the next day will not be accepted. The due date for labs might be postponed, if considered necessary during the semester. Lab assignments are considered to be group-based. Group sizes cannot exceed 2 students, defined at the beginning of the semester. The goal is to accomplish all labs and submit in Canvas until the next day.
- Class Activities: These activities involve participation during in-class collaborative exercises. The aim is to actively engage in discussions, problem-solving, or any assigned tasks alongside peers during each session. The grade for this category will be subjective, based on the level of engagement and contribution demonstrated by each student during the class. Class activities serve as a more meaningful measure of attendance. Class activities are considered to be group-based. These groups will be created in ad-hoc manner each session, and their size may vary from session to session.
- Presentations: This assignment involves presenting and leading a full-class discussion on a recent state-of-the-art quantum computing research paper, with an emphasis on quantum programming languages, compilers, verification, semantics, software systems, or closely related topics. Each group of 3 students will prepare and deliver a deep technical presentation covering the paper's motivation, main contributions, key technical ideas, relationship to course concepts, strengths, limitations, and open questions. Detailed requirements and grading criteria will be provided in advance. This assignment is considered group-based.
| Assignment Type | Score (%) | Group Sizes | Due Times |
|---|---|---|---|
| Reading/Watching | 0% | Individual | Before each session (no submission) |
| Quizzes | 10% | Individual | Start of session |
| Labs | 25% | 2 | 11:59 PM next day (unless extended) |
| Class Activities | 30% | Ad‑hoc | During session |
| Presentations | 15% | 3 | Presentation day |
| Exams | 20% | Individual | Scheduled date |
Solutions: Quiz/sample‑exam/midterm solutions may be submitted via Canvas or on paper when appropriate.
All work is individual unless otherwise specified, and subject to the Academic Honesty Policy.
Academic Honesty
The Honor Code calls upon each student to exhibit maturity, responsibility, and integrity. Students are expected to:
- Act honestly in all matters
- Encourage academic integrity
- Discourage cheating or dishonesty
- Inform the instructor/administration with good‑faith evidence of violations
Violations are referred to the Office of Student Conduct and Community Standards and may result in penalties up to failure/suspension/dismissal. See Tiger Lore and online policy.
Course‑specific policy:
- Collaboration on planning/strategy/debugging is encouraged.
- Do not submit someone else’s work.
Marginal cases may be resolved via oral examination to assess individual understanding.
Accommodations for Students with Disabilities
If you require accommodations, visit pacific.edu/disabilities to contact SSD and request services.
- New students: apply via New Students Apply Here.
- Returning students: request letters each semester via Returning Students Login Here.
SSD: McCaffrey Center (2nd Floor) • 209‑946‑3221 • ssd@pacific.edu • website
Nondiscrimination Policy
The University of the Pacific does not discriminate in the administration of its programs/activities based on race, color, national and ethnic origin, handicap, sexual orientation or preference, sex, or age.
The instructor reserves the right to change these policies and guidelines at any time, and students agree to abide by the most recent version of this syllabus.