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Superconducting Qubits Quantum Error Correction Fault Tolerance Quantum Machine Learning Quantum Compilation Routing Architecture

A Compilation Framework for Quantum Circuits with Mid-Circuit Measurement Error Awareness

arXiv
Authors: Ming Zhong, Zhemin Zhang, Xiangyu Ren, Chenghong Zhu, Siyuan Niu, Zhiding Liang

Year

2025

Paper ID

17159

Status

Preprint

Abstract Read

~2 min

Abstract Words

178

Citations

N/A

Abstract

Mid-circuit measurement (MCM) provides the capability for qubit reuse and dynamic control in quantum processors, enabling more resource-efficient algorithms and supporting error-correction procedures. However, MCM introduces several sources of error, including measurement-induced crosstalk, idling-qubit decoherence, and reset infidelity, and these errors exhibit pronounced qubit-dependent variability within a single device. Since existing compilers such as the Qiskit-compiler and QR-Map (the state-of-art qubit reuse compiler) do not account for this variability, circuits with frequent MCM operations often experience substantial fidelity loss. In thie paper, we propose MERA, a compilation framework that performs MCM-error-aware layout, routing, and scheduling. MERA leverages lightweight profiling to obtain a stable per-qubit MCM error distribution, which it uses to guide error-aware qubit mapping and SWAP insertions. To further mitigate MCM-related decoherence and crosstalk, MERA augments as-late-as-possible scheduling with context-aware dynamic decoupling. Evaluated on 27 benchmark circuits, MERA achieves 24.94% - 52.00% fidelity improvement over the Qiskit compiler (optimization level 3) without introducing additional overhead. On QR-Map-generated circuits, it improves fidelity by 29.26% on average and up to 122.58% in the best case, demonstrating its effectiveness for dynamic circuits dominated by MCM operations.

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  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
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  • Mid-circuit measurement (MCM) provides the capability for qubit reuse and dynamic control in quantum processors, enabling more resource-efficient algorithms and supporting...

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