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.

我们引入最大似然碎片层析成像（MLFT）作为一种改进的电路切割技术，用于在量子位数有限的量子设备上运行群集量子电路。除了最大程度地减少电路切割方法的传统计算开销外，MLFT还可以找到量子电路输出的最可能的概率分布，并给出从电路碎片中获取的测量数据。我们通过对随机FT电路的数值实验证明了MLFT的好处，它可以准确地估计碎片化量子电路的输出。最后，我们证明电路切割可以比全电路执行更高的保真度来估计集群电路的输出，从而激发电路切割作为在量子硬件上运行集群电路的标准工具的使用。