Quantum Computing (量子計算) 2025

Lecturer: 江振瑞
Teaching Assistants (TAs): 黃文翰林橋毅
Time: 週二 14:00~16:50
Place: 週二工五館 E6-A210
EEClass: (CE5082)

Goal: Leading students to understand the basic principles of quantum computing and the developments and the applications of the latest quantum computing technologies. (帶領學生了解量子計算基本原理及最新量子計算技術之發展與應用)

Scoring：

midterm project (programming) (30%)
oral report in class (25%)
term project (programming) (30%)
homework, reports and in-class participation (15%)

Textbooks:

江振瑞, 輕鬆學量子程式設計 -- 從量子位元到量子演算法, 碁峰資訊, ISBN: 9786263242715, 2022/08.

Reference Books:

張元翔, 量子電腦與量子計算, 碁峰資訊, 2020.
陳建宏(譯), 量子計算實戰, 碁峰資訊, 2020.
莊永裕(譯), 圖解量子電腦入門, 臉譜, 2020.
林志鴻, 張仁瑀, 徐育兆, 林橋毅, 劉子睿, 林侑恆, 量子電腦應用與世界級競賽實務, 2021.
Jack D. Hidary, Quantum Computing: An Applied Approach (2nd Ed), 2021.
Chris Bernhardt, Quantum Computing for Everyone, 2020.
Nihal Mehta, Quantum Computing -- Program Next-Gen Computers for Hard, Real-World Applications, 2020.
Michael A. Nielsen, and Isaac L. Chuang, Quantum Computation and Quantum Information, 2002.

Syllabus: (2025-Quantum-Computing.pdf)

(9/2) Week 1. Introduction to Quantum Computing -- From quantum bit to quantum algorithm (qc-talk.pptx)
(9/9) Week 2. Quantum programming for the first time (Introduction to IBM Q quantum computer and D-Wave quantum computer) (QBookCh1.zip)
Homework1:
Textbook Exercises (Select one from 1.1-1.3)(and 1.4)(and 1.5 Bonus) (deadline: by noon before next class)
(9/16) Week 3. QUBO建模、PyQUBO程式設計與量子位元疊加態程式設計(2025-0916-PyQUBO.zip) (QBookCh2.zip)(Quantum_Course_Slides(Week3).zip)
Homework 2: (A) Max-Cut Prob. PyQUBO programming for the G22 dataset and (B) Ex2.1 to Ex.2.5.
Deadline: 9/22 23:59
(9/23) Week 4. Quantum-inspired Annealers (2025-GPUA.zip), metaheuristic algorithms (metaheuristics.pptx) as well as Quantum Gates, Quantum Entanglement and Quantum Teleportation (QBookCh3.zip)(QBookCh4.zip)(qexp.pptx)
Homework 3: (A) Write a report to introduce ES, SA, DE, TCA, VNS, TS, or GSA (bonus: with an example using a program to solve an NP-hard problem). (TA will announce the problem assignment soon.) (B) Ex4.1 to Ex4.5. Deadline: 9/29 23:59
(9/30) Week 5. Paper Oral Reports (1/3)
(1) Introduction to Fujitsu Digital Annealer with Examples. (Fujitsu_DA_Constraints.docx)(TA: 林橋毅)
(2) de Queiroz, T. A., Iori, M., Locatelli, A., & Parizy, M. (2025, July).
Solving the Cubic Knapsack Problem using the Quantum-Inspired Digital Annealer Technology. In Proceedings of the Genetic and Evolutionary Computation Conference (pp. 890-897).
(3) Codognet, P., Diaz, D., & Abreu, S. (2022, July). Quantum and digital annealing for the quadratic assignment problem. In 2022 IEEE International Conference on Quantum Software (QSW) (pp. 1-8). IEEE.
(10/7) Week 6. Paper Oral Reports (2/3)
(4) Jehn-Ruey Jiang, and Chun-Wei Chu, "Classifying and Benchmarking Quantum Annealing Algorithms Based on Quadratic Unconstrained Binary Optimization for Solving NP-hard Problems," IEEE Access, vol. 11, pp. 104165-104178, 2023.
Jehn-Ruey Jiang, Yu-Chen Shu, and Qiao-Yi Lin, "Benchmarks and Recommendations for Quantum, Digital, and GPU Annealers in Combinatorial Optimization," IEEE Access, vol. 12, pp. 125014-125031, 2024.
(5) Zeng, Q. G., Cui, X. P., Liu, B., Wang, Y., Mosharev, P., & Yung, M. H. (2024). Performance of quantum annealing inspired algorithms for combinatorial optimization problems. Communications Physics, 7(1), 249.
(6) Lee, H., & Jun, K. (2025). Range dependent Hamiltonian algorithms for numerical QUBO formulation. Scientific Reports, 15(1), 8819.
(10/14) Week 7. Paper Oral Reports (3/3)
(7) Nakano, K., Takafuji, D., Ito, Y., Yazane, T., Yano, J., Ozaki, S., ... & Mori, R. (2023, May). Diverse adaptive bulk search: a framework for solving QUBO problems on multiple GPUs. In 2023 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW) (pp. 314-325). IEEE.
(8) Andreou, A., Mavromoustakis, C. X., Markakis, E., Bourdena, A., & Mastorakis, G. (2025). Sustainable AI With Quantum-Inspired Optimization: Enabling End-to-End Automation in Cloud-Edge Computing. IEEE Access.
(9) Kaseb, Z., Moller, M., Vergara, P. P., & Palensky, P. (2024). Power flow analysis using quantum and digital annealers: a discrete combinatorial optimization approach. Scientific Reports, 14(1), 23216.

(10/21) Week 8. Midterm Project (No Class Today)
Using the QUBO solver to solve a large scale 0/1 knapsack problem instance based on the slack-variable-range-search problem decomposition mechanism (ref: 2025-ECICE-QUBO-Decomposition(1008).zip). The scoring will be based on how close you solution approaches the best known solution and how well you describe your program. (TA will announce the problem instance via EE-Class soon.) (Due: 10/27 23:59)
(10/28) Week 9. Background knowledge for gate-based quantum algorithms and Grover's algorithm and its variants (QBookCh4.zip)(QBookCh5.zip)
Homework: Ex4.1, Ex4.3~Ex4.5, Ex5.1, Ex5.3 (Deadline: 11/3 23:59)
(11/4) Week 10. Grover's algorithm and its variants (1/2).
(QBookCh6.zip)(2023-VTS-APWCS-0825(REV).pptx)
Paper: Jehn-Ruey Jiang, and Yu-Jie Wang, "Using a Simplified Quantum Counter to Implement Quantum Circuits Based on Grover’s Algorithm to Tackle the Exact Cover Problem," Mathematics, 13(1), 90, 2025. (SCI)(IF: 2.2); Mathematics (Q1).
Homework: Ex6.1-Ex6.4 (Deadline: 11/10 23:59)
(11/11) Week 11. Grover's algorithm and its variants (2/2).
Paper: Jehn-Ruey Jiang, and Yu-Jie Wang, "Dicke State Quantum Search for Solving the Vertex Cover Problem," Mathematics, 13(18), 3005, 2025.
(11/18) Week 12. ~~Shor's algorithm and its variants.~~ ~~(~~QBookCh7.zip~~)~~
Paper Oral Reports: 20 minutes for each paper with well-prepared slides uploaded to the folder assigned by TAs.
1. Hong, Y. Y., Rioflorido, C. L. P. P., & Zhang, W. (2024). Hybrid deep learning and quantum-inspired neural network for day-ahead spatiotemporal wind speed forecasting. Expert Systems with Applications, 241, 122645.
2. Hong, Y. Y., Lopez, D. J. D., & Wang, Y. Y. (2024). Solar irradiance forecasting using a hybrid quantum neural network: A comparison on gpu-based workflow development platforms. IEEE Access, 12, 145079-145094.
3. Liu, C. Y., Chen, S. Y. C., Chen, K. C., Huang, W. J., & Chang, Y. J. (2025, March). Programming variational quantum circuits with quantum-train agent. In 2025 International Conference on Quantum Communications, Networking, and Computing (QCNC) (pp. 544-548). IEEE.
4. Liu, C. Y., Chen, S. Y. C., Chen, K. C., Huang, W. J., & Chang, Y. J. (2025). Federated quantum-train long short-term memory for gravitational wave signal. arXiv preprint arXiv:2503.16049.
5. Liu, C. Y., Chen, K. C., Chen, Y. C., Chen, S. Y. C., Huang, W. H., Huang, W. J., & Chang, Y. J. (2025). Quantum-Enhanced Parameter-Efficient Learning for Typhoon Trajectory Forecasting. arXiv preprint arXiv:2505.09395.
6. Sie, M. F., Chang, Y. J., Lin, C. L., Chang, C. R., & Liao, S. W. (2025). Efficient Bitcoin address classification using quantum-inspired feature selection. Quantum Machine Intelligence, 7(2), 75.
7. Chang, Y. J., Wang, W. T., Liu, C. Y., Wang, Y. Y., & Chang, C. R. (2025). Quantum Walks-Based Adaptive Distribution Generation with Efficient CUDA-Q Acceleration. arXiv preprint arXiv:2504.13532.
(11/25) Week 13. Speeches by Prof. Ying-Yi Hong (洪穎怡) (中原大學電機系講座教授、前副校長與研發長)
Topic 1. 當深度學習在能源預測遇見量子計算
Topic 2. A Robust Quantum AI Model for Short-Term Wind Speed Forecasting
(12/02) Week 14. Speeches by Prof. Yen-Jui Chang (張晏瑞 ) (中原大學量子資訊中心教授).
(12/09) NCU Quantum Day. 9:00-17:30.
10:00-11:40 114年余紀忠講座-蔡兆申院士主講「走進未來：超導量子電腦如何改變世界」
14:00-16:00 成功大學陳岳男教授 Simulating open system dynamics using cloud quantum computers
(12/16) Week 16. Term Project (No Class Today) Problem: Using Grover's algorithm to solve the vertex cover problem
(The datasets will be announced soon.) (Due: 12/29 23:59)