Hybrid Control Unlocking Quantum Supercomputers

Quantum computation at useful scales requires tight integration between real-time quantum control systems and high-throughput classical accelerators. This work presents Quantum Machines' vision for a heterogeneous, distributed architecture that spans multiple latency regimes and diverse classical resources. We illustrate example of workflows enabled by this novel system, for optimization and large-scale calibration routines based on reinforcement learning, together with a quantum error correction decoding on classical accelerators. Together, these components define a practical roadmap to utility-grade, fault-tolerant quantum supercomputers grounded in hybrid control.