QAP-Router: Tackling Qubit Routing as Dynamic Quadratic Assignment with Reinforcement Learning

Researchers have introduced QAP-Router, a novel approach to tackling qubit routing as a dynamic quadratic assignment problem using reinforcement learning. This method addresses the NP-hard nature of qubit routing, which is a critical challenge in quantum compilation. By leveraging reinforcement learning, QAP-Router can make more informed decisions than existing heuristic methods, which rely on local rules with limited lookahead. The dynamic nature of qubit routing makes local decisions propagate and compound over time, requiring a more global and efficient solution. QAP-Router's approach has the potential to improve the efficiency of quantum compilation, which is essential for the development of practical quantum computing applications¹. As quantum computing advances, the need for quantum-resistant cryptography, such as post-quantum cryptography (PQC), becomes more urgent, making QAP-Router's contributions to quantum compilation particularly significant. This development narrows the timeline for cryptographic migration, emphasizing the importance of PQC planning.