Freedom of mixer rotation-axis improves performance in the quantum approximate optimization algorithm

• URL: http://arxiv.org/abs/2107.13129v1
• Date: Wed, 28 Jul 2021 02:13:01 GMT
• Title: Freedom of mixer rotation-axis improves performance in the quantum approximate optimization algorithm
• Authors: L. C. G. Govia, C. Poole, M. Saffman and H. K. Krovi
• Abstract summary: Variational quantum algorithms such as the quantum approximate optimization algorithm (QAOA) are attractive candidates for implementation on near-term quantum processors. We present a modification to QAOA that adds additional variational parameters in the form of freedom of the rotation-axis in the $XY$-plane of the mixer Hamiltonian. We show that this leads to a drastic performance improvement over standard QAOA at finding solutions to the MAXCUT problem on graphs of up to 7 qubits.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Variational quantum algorithms such as the quantum approximate optimization algorithm (QAOA) are particularly attractive candidates for implementation on near-term quantum processors. As hardware realities such as error and qubit connectivity will constrain achievable circuit depth in the near future, new ways to achieve high-performance at low depth are of great interest. In this work, we present a modification to QAOA that adds additional variational parameters in the form of freedom of the rotation-axis in the $XY$-plane of the mixer Hamiltonian. Via numerical simulation, we show that this leads to a drastic performance improvement over standard QAOA at finding solutions to the MAXCUT problem on graphs of up to 7 qubits. Furthermore, we explore the Z-phase error mitigation properties of our modified ansatz, its performance under a realistic error model for a neutral atom quantum processor, and the class of problems it can solve in a single round.

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