Grover Adaptive Search Based Hybrid Benders Decomposition for Mixed-Integer Linear Programs

Abstract: Mixed-integer linear programs are widely used to model optimization problems involving both discrete and continuous variables, but remain computationally challenging due to the combinatorial complexity. To exploit the potential advantages of quantum computing in tackling the combinatorial optimization part, recent efforts have explored hybrid quantum-classical Benders decomposition frameworks, which delegate the discrete master problem […]

Robust Design Under Uncertainty in Quantum Error Mitigation

Abstract: Error mitigation techniques are crucial to achieving near-term quantum advantage. Classical post-processing of quantum computation outcomes is a popular approach for error mitigation, which includes methods such as Zero Noise Extrapolation, Virtual Distillation, and learning-based error mitigation. However, these techniques have limitations due to the propagation of uncertainty resulting from the finite shot number […]