Welcome to SMU‑Quantum – the official repository for quantum computing research at Singapore Management University. Our work is driven by innovation and expertise under the guidance of Prof. Hoong Chuin Lau.

SMU‑Quantum is a collaborative initiative bringing together researchers, students, and industry partners to explore the frontiers of quantum computing. We focus on developing novel quantum optimization techniques and algorithms to tackle real-world challenges.

Explore our flagship projects:

• Quantum Optimization Benchmarks
  Benchmarking the performance of quantum optimization methods.

• Quantum Optimization Algorithms
  Developing advanced algorithms for quantum optimization.

• Cutting Slack
  Exploring and comparing slack-free constraint-handling techniques in quantum combinatorial optimization

• Hybrid Learning and Optimization for CVRP
  hybrid framework that uses Reinforcement Learning (RL) to automate parameter tuning for an Augmented Lagrangian Method (ALM) solver for the Capacitated Vehicle Routing Problem (CVRP)

Stay tuned: We are continuously expanding our portfolio with new projects and updates!

We are proud to share some of our latest research contributions:

1. Quantum-Enhanced Simulation-Based Optimization for Newsvendor Problems
   2024 IEEE International Conference on Quantum Computing and Engineering (QCE), Volume 01, Pages 457–468, 2024
   View Publication

2. Quantum Monte Carlo Methods for Newsvendor Problem with Multiple Unreliable Suppliers
   View Publication

3. Quantum Relaxation for Solving Multiple Knapsack Problems
   2024 IEEE International Conference on Quantum Computing and Engineering (QCE), Volume 01, Pages 692–698, 2024
   View Publication

4. A Comparative Study of Quantum Optimization Techniques for Solving Combinatorial Optimization Benchmark Problems
   View Publication
   View Code

5. Implementing Slack-Free Custom Penalty Function for QUBO on Gate-Based Quantum Computers
   2025 IEEE International Conference on Quantum Computing and Engineering (QCE)
   View Publication

6. Solving Constrained Combinatorial Optimization Problems with Variational Quantum Imaginary Time Evolution
   2025 IEEE International Conference on Quantum Computing and Engineering (QCE)
   View Publication

7. Adaptive Graph Shrinking for Quantum Optimization of Constrained Combinatorial Problems
   View Publication

8. Cutting Slack: Quantum Optimization with Slack-Free Methods for Combinatorial Benchmarks
   View Publication
   View Code

9. Hybrid Learning and Optimization methods for solving Capacitated Vehicle Routing Problem
   AAAI 2026 Workshop on Quantum Computing (QC), to appear in Communications in Computer and Information Science (CCIS), Springer Nature. View Publication
   View Code

And more are coming soon…

At SMU‑Quantum, we are dedicated to:

• Innovative Research: Merging theoretical insights with practical implementations.
• Open Collaboration: Welcoming contributions from developers, researchers, and enthusiasts.
• Community Engagement: Sharing knowledge and fostering a vibrant community around quantum computing.

We invite you to join our journey:

• Explore & Contribute: Check out our repositories, submit issues, or propose enhancements.
• Join the Conversation: Connect with us on GitHub and share your ideas.
• Collaborate: Whether you're a seasoned researcher or a curious beginner, your input is invaluable.

All projects under the SMU‑Quantum organization are released under open source licenses. Please refer to the individual repository licenses for more details.

• GitHub Organization: SMU‑Quantum
• Singapore Management University: SMU
• Faculty Profile: Prof. Hoong Chuin Lau

Empowering the future of quantum computing—one qubit at a time.