Google researchers have demonstrated a method to continuously recalibrate superconducting quantum processors during operation by leveraging data from quantum error correction. This approach uses reinforcement learning to adjust control parameters in real-time, addressing the issue of hardware drift that typically limits the duration and complexity of quantum calculations.
Background
Superconducting qubits, such as transmons, suffer from parameter drift over time, requiring periodic recalibration that traditionally interrupts computation. This development marks a significant step toward fault-tolerant quantum computing by integrating calibration into the operational workflow.
- Source
- Ars Technica
- Published
- Jul 11, 2026 at 07:02 AM
- Score
- 8.0 / 10