The quantum approximate optimization algorithm (QAOA) has been introduced as a heuristic digital quantum computing scheme to find approximate solutions of combinatorial optimization problems. We present a scheme to parallelize this approach for arbitrary all-to-all connected problem graphs in a layout of quantum bits (qubits) with nearest-neighbor interactions. The protocol consists of single qubit operations that encode the optimization problem, whereas interactions are problem-independent pairwise CNOT gates among nearest neighbors. This allows for a parallelizable implementation in quantum devices with a planar lattice geometry. The basis of this proposal is a lattice gauge model, which also introduces additional parameters and protocols for QAOA to improve the efficiency.
CITATION STYLE
Lechner, W. (2020). Quantum Approximate Optimization With Parallelizable Gates. IEEE Transactions on Quantum Engineering, 1. https://doi.org/10.1109/TQE.2020.3034798
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