The Role of Entanglement in Quantum-Relaxation Based Optimization Algorithms

Understand

Quantum Random Access Optimizer (QRAO) is a quantum-relaxation based optimization algorithm proposed by Fuller et al.

• that utilizes Quantum Random Access Code (QRAC) to encode multiple variables of binary optimization in a single qubit.
• Differing from standard quantum optimizers such as QAOA, it utilizes the eigenstates of local quantum Hamiltonians that are not diagonal in the computational basis.
• There are indications that quantum entanglement may not be needed to solve binary optimization problems with standard quantum optimizers because their maximal eigenstates of diagonal Hamiltonians include classical states.