Online Detection of Golden Circuit Cutting Points

Quantum circuit cutting has emerged as a promising method for simulating large quantum circuits using a collection of small quantum machines. Running low-qubit circuit “fragments” not only overcomes the size limitation of near-term hardware, but it also increases the fidelity of the simulation. However, reconstructing measurement statistics requires computational resources-both classical and quantum-that grow exponentially with the number of cuts. In this manuscript, we introduce the concept of a golden cutting point, which identifies unnecessary basis components during reconstruction and avoids related downstream computation. We propose a hypothesis-testing scheme for identifying golden cutting points, and provide robustness results in the case of the test failing with low probability. Lastly, we demonstrate the applicability of our method on Qiskit's Aer simulator and observe a reduced wall time from identifying and avoiding obsolete measurements.