Researchers have developed a real-time detector for charge jumps in superconducting qubits using a dilated causal convolutional neural network (DCCNN). This new method, designed for in-the-loop deployment on the Quantum Instrumentation Control Kit (QICK) platform, significantly reduces latency compared to existing offline detection techniques. The DCCNN achieves a per-inference latency of 6.19 μs and demonstrates detection efficiency comparable to the established offline χ² algorithm, without requiring per-qubit hyperparameter tuning. This advancement enables adaptive protocols that can respond to radiation-induced events in situ, benefiting both fault-tolerant quantum computing error mitigation and quantum sensing applications. AI
IMPACT Enables real-time error mitigation and enhanced quantum sensing capabilities by integrating AI into quantum control loops.
RANK_REASON Academic paper detailing a novel application of AI for scientific research. [lever_c_demoted from research: ic=1 ai=1.0]
- arXiv
- Daniel Gaytan-Villarreal
- Fermilab
- Northwestern Experimental Underground Site (NEXUS)
- Quantum Instrumentation Control Kit (QICK)
- Zynq UltraScale+ RFSoC ZCU216
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