无限大混合自旋模型单层量子近似优化算法的实例无关性
Instance Independence of Single Layer Quantum Approximate Optimization Algorithm on Mixed-Spin Models at Infinite Size
摘要：
本文研究了量子近似优化算法（QAOA）在大自旋数限制下对具有随机多体耦合的自旋玻璃模型的应用。我们表明，对于这样的混合自旋模型的深度$1$ QAOA的性能是独立的具体情况下，在无限大系统的极限，我们给出了一个明确的公式预期的性能。我们还给出了明确的表达式的期望能量的高阶矩，从而证明了QAOA的期望性能集中。
英文摘要：
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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