Semester of Graduation
Spring 2026
Degree Type
Thesis
Degree Name
Masters in Computer Science
Department
College of Computing and Software Engineering
Committee Chair/First Advisor
Tu Nguyen
Second Advisor
Kun Suo
Third Advisor
Bobin Deng
Abstract
Quantum networking is causing a revolution in technology. It allows secure communication and spreads quantum computing through interactions based on entanglement. However, keeping qubit coherence and making sure transmission is high-quality are big problems. This is because of decoherence, the times spent waiting for entanglement, and the delays in synchronizing up. This study suggests an improved quantum memory system to tackle these issues. It does this through making entanglement in parallel using reinforcement learning to schedule jobs and advanced ways to stop decoherence. These include quantum error correction (QEC) and dynamic decoupling (DD). The study creates a math formula to make fidelity as good as possible. It shows that this problem can be solved in polynomial time. Tests show that this system improves how well fidelity is kept and how well quantum states are sent overall. This proves that the suggested system is a good way to create quantum networks that can grow and be trusted.