Abstract Quantum annealing solves combinatorial optimization problems by finding the energetic ground states of an embedded Hamiltonian. However, quantum annealing dynamics under the embedded Hamiltonian may violate the principles of adiabatic evolution and generate excitations that correspond to errors in the computed solution. Here we empirically benchmark the probability of chain breaks and identify sweet spots for solving a suite of embedded Hamiltonians. We further correlate the physical location of chain breaks in the quantum annealing hardware with the underlying embedding technique and use these localized rates in a tailored post-processing strategies. Our results demonstrate how to use characterization of the quantum annealing hardware to tune the embedded Hamiltonian and remove computational errors.

中文翻译：

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在量子退火中对嵌入式链断裂进行基准测试 *

摘要 量子退火通过找到嵌入哈密顿量的高能基态来解决组合优化问题。然而，嵌入哈密顿量下的量子退火动力学可能违反绝热演化原理并产生与计算解中的误差相对应的激发。在这里，我们凭经验对链断裂的概率进行基准测试，并确定解决一组嵌入式哈密顿量的最佳点。我们进一步将量子退火硬件中链断裂的物理位置与底层嵌入技术相关联，并在定制的后处理策略中使用这些局部化速率。我们的结果展示了如何使用量子退火硬件的特性来调整嵌入式哈密顿量并消除计算错误。