Quantum Circuit Partitioning For Effective Utilization of Quantum Resources

TL;DR

This paper evaluates quantum circuit partitioning techniques to improve fidelity and scalability on near-term quantum hardware, analyzing their effectiveness across different circuit types and sizes.

Contribution

It provides a comparative analysis of circuit partitioning methods, identifying when and which circuits benefit most from partitioning on current quantum hardware.

Findings

Partitioning improves fidelity for larger, highly interconnected circuits.

Custom circuit cutting reduces error by up to 55%.

Partitioning can degrade performance for certain circuit types at larger scales.

Abstract

Near-term hardware is constrained by high error rates, small qubit counts, and relatively low output fidelity, making the execution of large, high performance quantum circuits difficult. Circuit partitioning (or circuit cutting) has emerged as a promising approach to circumvent these limitations by decomposing circuits into smaller subcircuits at two-qubit interaction points. However, it remains unclear which classes of circuits benefit the most from partitioning and under what hardware conditions it is most effective. In this work, we evaluate the suitability of quantum circuits for partitioning from three perspectives: improving fidelity, enabling distributed execution, and scaling to larger circuit sizes. Specifically, we compare uncut circuit execution against two circuit partitioning approaches: Qiskit's automatic cut finding technique and a custom performance optimized circuit cutting method. We also measure these across GHZ, QFT, brickwork, and random quantum circuits ranging from 4 to 14 qubits, using mean absolute error of expectation values and overall output fidelity. Our results show that partitioning benefits larger, highly interconnected circuits, with our custom method reducing error by up to 55\% and improve fidelity for GHZ circuits, but degrading performance for brickwork circuits at larger scales.