Hierarchical Quantum Circuit Cutting

Circuit cutting allows quantum circuits that exceed a target processor to be evaluated as smaller subexperiments, but quasiprobability decomposition (QPD) introduces sampling and reconstruction overhead that can grow rapidly with the number of cuts. We present a distributed hierarchical circuit-cutting workflow that combines Qiskit Addon Cutting with MPI. The contribution is an execution and reconstruction strategy, not a new global cut-search heuristic: subcircuits are recursively decomposed, QPD streams are assigned deterministically to MPI ranks, leaf subcircuits are executed in parallel, and expectation values are reconstructed bottom-up through the same hierarchy. For a 16-qubit hardware-efficient ansatz benchmark, the reported QPD sampling overhead of the three-level workflow is 27,135, compared with 4,782,969 for a direct sequential circuit-cutting baseline.