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QSNL advances scalable and secure quantum systems through innovative research in quantum networking, distributed quantum computing (DQC), quantum applications, quantum machine learning, and quantum security. Our work delivers generalizable frameworks, reproducible benchmarks, and robust tools and guidelines to enable secure computation and communication in future quantum systems and networks.
Research
Distributed Quantum Computing and Networking
How can connected quantum processors work together to execute computations beyond the capacity of a single device?
We develop networking and orchestration methods for distributed quantum computing, focusing on entanglement routing, remote gate scheduling, and noise-aware circuit partitioning and compilation. Through reproducible benchmarks, we study how network resources, hardware noise, and scheduling decisions affect execution time, resource use, and computational fidelity.
Topics: Entanglement distribution and routing; distributed circuit execution; network-aware compilation; resource allocation and scheduling.
Quantum Optimization Across Domains
Which optimization problems are promising candidates for quantum approaches, and under what conditions can those approaches be useful?
We investigate methods such as quantum annealing and Quantum Approximate Optimization Algorithm (QAOA) for problems across science and engineering. Our work develops reusable problem formulations and reproducible benchmarks to compare quantum and hybrid methods with classical approaches, identify practical limitations, and guide their integration into application workflows.
Topics: Quantum and hybrid optimization; application-driven problem formulations; comparisons with classical baselines; reproducible performance evaluation.
Security of Quantum Systems and Networks
How can quantum computation and communication remain trustworthy in the presence of imperfect devices and adversarial behavior?
We investigate threats to quantum systems and networks, develop attack models, and evaluate protocols for protecting entanglement distribution, quantum state transfer, and distributed computation. Our goal is to understand security limitations and develop practical tools and design guidelines for more resilient quantum infrastructure.
Topics: Quantum network threat models; protocol security; attacks on quantum communication; security evaluation and mitigation.
People
Zebo Yang, Ph.D.
Assistant Professor, Department of Electrical Engineering and Computer Science
Bhavani Shankar Neeluri
Ph.D. student. Research: Quantum Optimization.
Yeong Lim Tan
Master’s student. Research: DQC; Quantum Optimization.
Lola Torres
Master’s student. Research: Quantum Security.
Adam Brown
Undergraduate researcher. Research: Quantum Optimization.
Romina Gotzmann
Master’s (alumni). Research: Quantum Applications.
Santiago Delgado Montoya
Master’s (alumni). Research: Quantum Security.
Publications
Our research spans DQC, quantum networking, optimization, and security.
Resources
We support reproducible research through shared implementations, benchmarks, and evaluation tools.
- SimDisQ-Net — A network-aware simulator for executing quantum circuits across connected quantum processors. It extends SimDisQ with configurable routing, scheduling, entanglement purification, and security-aware path selection. It support comparing network strategies and explore trade-offs among execution latency, fidelity, and modeled security risk. Github.
- SimDisQ — A simulator for partitioning, executing, and visualizing quantum circuits across multiple quantum processors. It supports heterogeneous QPU configurations and models local hardware and communication noise. Useful for investigating distributed circuit execution and exploring how partitioning and hardware choices affect measurement results. Github.
Contact
Quantum Systems & Networking Lab (QSNL)
Zebo Yang
Engineering East (EE) 518
Department of Electrical Engineering and Computer Science
Florida Atlantic University