Quantum Approximate Optimization with Parallelizable Gates

TL;DR

This paper introduces a parallelizable version of the quantum approximate optimization algorithm (QAOA) suitable for quantum devices with nearest neighbor interactions, enhancing efficiency for combinatorial problems.

Contribution

It proposes a new scheme to parallelize QAOA on square lattice quantum devices using problem-independent pairwise CNOT gates and a lattice gauge model.

Findings

Enables parallel implementation of QAOA on 2D lattice hardware.

Incorporates additional parameters to improve QAOA efficiency.

Applicable to all-to-all connected problem graphs.

Abstract

The quantum approximate optimization algorithm (QAOA) has been introduced as a heuristic digital quantum computing scheme to find approximate solutions of combinatorial problems with shallow circuits. 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 consisting of single qubit operations that encode the optimization problem and all interactions are problem-independent pair-wise CNOT gates among nearest neighbors. This allows for a parallelizable implementation in quantum devices with a square 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.