Quantum circuit cutting with maximum-likelihood tomography

Abstract We introduce maximum-likelihood fragment tomography (MLFT) as an improved circuit cutting technique for running clustered quantum circuits on devices with a limited number of qubits. In addition to minimizing the classical computing overhead methods, MLFT finds most likely probability distribution output circuit, given measurement data obtained from circuit’s fragments. demonstrate benefits accurately estimating fragmented numerical experiments random unitary circuits. Finally, we show that can estimate higher fidelity than full execution, thereby motivating use standard tool hardware.