Quantum infrastructure startup AQSolotl and automation developer QuantrolOx have announced a strategic partnership to integrate their hardware and machine learning software layers. The collaboration focuses on linking AQSolotl’s Chronos-Q quantum control system directly with QuantrolOx’s Quantum EDGE automation software platform. By unifying the control and calibration stacks, the companies aim to transition noisy quantum processors from slow, manual laboratory tuning loops toward automated, machine learning-driven execution frameworks designed for scalable, production-ready infrastructure. Machine Learning-Driven Low-Latency Control Topologies As quantum processing units (QPUs) scale beyond isolated laboratory prototypes, tracking multi-qubit error intersections and performance drifts through manual tuning becomes physically impractical. The [...]

Zapata Quantum and NVIDIA have partnered to integrate agentic AI into quantum algorithm development by automating quantum resource estimation workflows. The collaboration focuses…

UK-based photonic quantum computing company Aegiq has unveiled a series of technical milestones that integrate artificial intelligence and tensor network mathematics into its…