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Quantum computers must meet extremely stringent qualitative and quantitativerequirements on their qubits in order to solve real-life problems. Quantumcircuit fragmentation techniques divide a large quantum circuit into a numberof sub-circuits that can be executed on the smaller noisy quantum hardwareavailable. However, the process of quantum circuit fragmentation involvesfinding an ideal cut that has exponential time complexity, and also classicalpost-processing required to reconstruct the output. In this paper, we representa quantum circuit using a weighted graph and propose a novel classical graphpartitioning algorithm for selecting an efficient fragmentation that reducesthe entanglement between the sub-circuits along with balancing the estimatederror in each sub-circuit. We also demonstrate a comparative study overdifferent classical and quantum approaches of graph partitioning for findingsuch a cut. We present {\it FragQC}, a software tool that cuts a quantumcircuit into sub-circuits when its error probability exceeds a certainthreshold. With this proposed approach, we achieve an increase of fidelity by14.83\% compared to direct execution without cutting the circuit, and 8.45\%over the state-of-the-art ILP-based method, for the benchmark circuits.

FragQC: An Efficient Quantum Error Reduction Technique using Quantum Circuit Fragmentation