qGDP: Quantum Legalization and Detailed Placement for Superconducting Quantum Computers

Junyao Zhang, Guanglei Zhou, Feng Cheng, Jonathan Ku, Qi Ding, Jiaqi Gu, Hanrui Wang, Hai Li, Yiran Chen
Duke University, Massachusetts Institute of Technology, Arizona State University
(* indicates equal contribution)

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Hanrui WangqGDP
 team
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Abstract

Noisy Intermediate-Scale Quantum (NISQ) computers are currently limited by their qubit numbers, which hampers progress towards fault-tolerant quantum computing. A major challenge in scaling these systems is crosstalk, which arises from unwanted interactions among neighboring components such as qubits and resonators. An innovative placement strategy tailored for superconducting quantum computers can systematically address crosstalk within the constraints of limited substrate areas. Legalization is a crucial stage in placement process, refining post-global-placement configurations to satisfy design constraints and enhance layout quality. However, existing legalizers are not supported to legalize quantum placements. We aim to address this gap with qGDP, developed to meticulously legalize quantum components by adhering to quantum spatial constraints and reducing resonator crossing to alleviate various crosstalk effects. Our results indicate that qGDP effectively legalizes and fine-tunes the layout, addressing the quantum-specific spatial constraints inherent in various device topologies. By evaluating diverse NISQ benchmarks. qGDP consistently outperforms state-of-the-art legalization engines, delivering substantial improvements in fidelity and reducing spatial violation, with average gains of 34.4x and 16.9x, respectively.

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Citation

@article{zhang2024qgdp,  title={qGDP: Quantum Legalization and Detailed Placement for Superconducting Quantum Computers},  author={Zhang, Junyao and Zhou, Guanglei and Cheng, Feng and Ku, Jonathan and Ding, Qi and Gu, Jiaqi and Wang, Hanrui and Li, Hai and Chen, Yiran and others},  journal={DATE},  year={2025}}

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