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Meeting: Decoder Benchmarking Results and Hardware Access Update
Date: 2025-01-22 Participants: Dr. Sarah Chen, Marcus Webb, Dr. Priya Patel, James Rodriguez, Dr. Elena Volkov
Discussion
Great news - IBM Quantum Network access was approved! We now have priority access to the 127-qubit Eagle processor. Dr. Chen demonstrated the initial calibration runs showing T1 times averaging 120μs and T2 times of 80μs across the device.
James presented the decoder benchmarking results:
- MWPM decoder (PyMatching): 94.2% accuracy at p=0.1% physical error rate
- Union-Find decoder: 93.8% accuracy, but 3x faster execution
- Neural network decoder (preliminary): 95.1% accuracy, training ongoing
Marcus showed the distance-5 surface code simulation results. With 49 physical qubits, we achieved a logical error rate of 0.8% at p=0.1% physical error rate. This is competitive with published results.
Dr. Volkov proposed an optimization to the syndrome extraction circuit that reduces depth by 15%. This could significantly improve performance on noisy hardware.
Dr. Patel raised concerns about the decoder latency requirements for real-time feedback. The neural network decoder currently takes 50ms per decode cycle, which exceeds the 10ms requirement.
Decisions
- Use Union-Find decoder for real-time experiments (meets latency requirements)
- Continue neural network decoder development for offline analysis
- Implement Dr. Volkov's circuit optimization immediately
- Schedule first hardware experiment for February 5th
- Target submission to Physical Review Letters by March
Action Items
- Marcus Webb: Implement Volkov's circuit optimization by 2025-01-26
- James Rodriguez: Optimize neural network decoder inference time by 2025-01-29
- Dr. Patel: Prepare hardware experiment protocol by 2025-02-01
- Dr. Volkov: Theoretical analysis of optimized circuit fidelity by 2025-01-30
- Dr. Chen: Book IBM Quantum time slots for February experiments by 2025-01-25
- Marcus Webb: Implement distance-5 surface code in Qiskit (completed)
- James Rodriguez: Integrate MWPM decoder from PyMatching library (completed)
Blockers
- Neural network decoder latency too high for real-time use - exploring FPGA implementation
- IBM device calibration drifts daily - need to implement recalibration protocol
- Publication embargo from IBM on hardware results until March 1st