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Quantum circuit cutting with maximum-likelihood tomography

机译:具有最大似然断层扫描的量子电路切割

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We introduce maximum-likelihood fragment tomography (MLFT) as an improved circuit cutting technique for running clustered quantum circuits on quantum devices with a limited number of qubits. In addition to minimizing the classical computing overhead of circuit cutting methods, MLFT finds the most likely probability distribution for the output of a quantum circuit, given the measurement data obtained from the circuit's fragments. We demonstrate the benefits of MLFT for accurately estimating the output of a fragmented quantum circuit with numerical experiments on random unitary circuits. Finally, we show that circuit cutting can estimate the output of a clustered circuit with higher fidelity than full circuit execution, thereby motivating the use of circuit cutting as a standard tool for running clustered circuits on quantum hardware.
机译:我们将最大似然片段断层扫描(MLFT)引入了一种改进的电路切割技术,用于在量子器件上运行具有有限数量的Qubits上的集群量子电路。 除了最小化电路切割方法的经典计算开销之外,考虑到从电路的碎片获得的测量数据,MLFT发现量子电路输出的最可能概率分布。 我们展示了MLFT的益处,用于准确地估计分段量子电路的输出,在随机整体电路上具有数值实验。 最后,我们表明电路切割可以估计具有更高保真度的聚类电路的输出,而不是完全电路执行,从而激励电路切割作为在量子硬件上运行聚类电路的标准工具。

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