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Qualifier: Yuxuan Zhang
Monday, November 11, 2019, 03:00pm

Yuxuan Zhang, UT-Austin

"A Quantum Approximate Optimization Algorithm for Edge-Disjoint Paths Problem"

Abstract: The Quantum Approximate Optimization Algorithm (QAOA) is a class of promising quantum-classical hybrid algorithms for near-term quantum device implementations, for it naturally requires low circuit depth. In this work, we present a QAOA method to solve a specific type of combinatorial optimization problem, the edge-disjoint paths (EDP) problem on planar graphs. Given a graph and k-pairs of vertices, the goal of the EDP problem is to find k-disjoint paths to connect each pair of vertices. By introducing a lattice QED inspired mixing Hamiltonian, we are guaranteed to always obtain feasible solutions from the algorithm.

Location: RLM 5.116