Instance Independence of Single Layer Quantum Approximate Optimization Algorithm on Mixed-Spin Models at Infinite Size

• URL: http://arxiv.org/abs/2102.12043v3
• Date: Tue, 7 Sep 2021 15:16:03 GMT
• Title: Instance Independence of Single Layer Quantum Approximate Optimization Algorithm on Mixed-Spin Models at Infinite Size
• Authors: Jahan Claes and Wim van Dam
• Abstract summary: We show that for mixed-spin models the performance of depth $1$ QAOA is independent of the specific instance in the limit of infinite sized systems. We also give explicit expressions for the higher moments of the expected energy, thereby proving that the expected performance of QAOA concentrates.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper studies the application of the Quantum Approximate Optimization Algorithm (QAOA) to spin-glass models with random multi-body couplings in the limit of a large number of spins. We show that for such mixed-spin models the performance of depth $1$ QAOA is independent of the specific instance in the limit of infinite sized systems and we give an explicit formula for the expected performance. We also give explicit expressions for the higher moments of the expected energy, thereby proving that the expected performance of QAOA concentrates.

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