Quantum Divide and Compute and its Application

We introduce a "Quantum Divide and Compute" technique that allows dividing a quantum circuit in smaller sub circuits that can run on devices with a limited number of qubits. The naïve Quantum Divide and Compute algorithm does not ensure that recombined output distribution is well defined as a probability distribution. We introduce Maximum Likelihood Fragment Tomography (MLFT) to ensure that all reconstructed probability distributions are strictly non-negative and normalized. We also provide numerical evidence and theoretical arguments that circuit cutting can estimate the output of a clustered circuit with a higher fidelity than full circuit execution for certain types of circuits. We illustrate the application of these techniques on quantum approximate optimization circuits.