CAMEL: Physically Inspired Crosstalk-Aware Mapping and gatE scheduLing for Frequency-Tunable Quantum Chips

• URL: http://arxiv.org/abs/2311.18160v3
• Date: Wed, 09 Oct 2024 07:04:43 GMT
• Title: CAMEL: Physically Inspired Crosstalk-Aware Mapping and gatE scheduLing for Frequency-Tunable Quantum Chips
• Authors: Bin-han Lu, Peng Wang, Zhao-yun Chen, Huan-yu Liu, Tai-ping Sun, Peng Duan, Yu-chun Wu, Guo-ping Guo,
• Abstract summary: Crosstalk represents a formidable obstacle in quantum computing. We introduce a Crosstalk-Aware Mapping and gatE Scheduling (CAMEL) approach to mitigate crosstalk. In contrast to approaches serializing crosstalk gates, CAMEL successfully suppresses decoherence.
• Score: 5.882878136245986
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• Abstract: Crosstalk represents a formidable obstacle in quantum computing. When quantum gates are executed parallelly, the resonance of qubit frequencies can lead to residual coupling, compromising the fidelity. Existing crosstalk solutions encounter difficulties in mitigating crosstalk and decoherence when dealing with parallel two-qubit gates in frequency-tunable quantum chips. Inspired by the physical properties of frequency-tunable quantum chips, we introduce a Crosstalk-Aware Mapping and gatE Scheduling (CAMEL) approach to address these challenges. CAMEL aims to mitigate crosstalk of parallel two-qubit gates and suppress decoherence. Utilizing the features of the tunable coupler, the CAMEL approach integrates a pulse compensation method for crosstalk mitigation. Furthermore, we present a compilation framework, including two steps. Firstly, we devise a qubit mapping approach that accounts for both crosstalk and decoherence. Secondly, we introduce a gate timing scheduling approach capable of prioritizing the execution of the largest set of crosstalk-free parallel gates to shorten quantum circuit execution times. Evaluation results demonstrate the effectiveness of CAMEL in mitigating crosstalk compared to crosstalk-agnostic methods. Furthermore, in contrast to approaches serializing crosstalk gates, CAMEL successfully suppresses decoherence. Finally, CAMEL exhibits better performance over dynamic-frequency awareness in low-complexity hardware.

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