论文标题
量子电路切割，最大似然层析成像
Quantum Circuit Cutting with Maximum Likelihood Tomography
论文作者
论文摘要
我们将最大似然片段断层扫描（MLFT）作为改进的电路切割技术，用于在量子设备上运行群集量子电路，量子数量有限。除了最大程度地减少电路切割方法的经典计算开销外，MLFT还发现了量子电路输出的最可能的概率分布，鉴于从电路的片段获得的测量数据。我们证明了MLFT的好处，可以通过在随机单一电路上进行数值实验准确估算碎片量子电路的输出。最后，我们表明，电路切割可以估计比全电路执行更高的限制电路的输出，从而激发了将电路切割作为在量子硬件上运行群集电路的标准工具的使用。
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.
