Insider Brief
Aegiq integrated NVIDIA Ising AI models into the calibration workflow of its Artemis photonic quantum computer, reducing manual calibration requirements and improving operational efficiency.
The deployment achieved a threefold reduction in weekly engineering time by automating the optimization of quantum source performance metrics such as brightness, purity, and indistinguishability.
Aegiq plans to expand AI-assisted calibration and quantum error correction capabilities as it develops larger-scale fault-tolerant photonic quantum computing systems.
PRESS RELEASE — Quantum computers are inherently unstable systems, requiring frequent calibration to maintain optimal performance. Traditionally, this process relies on manual intervention, as traditional algorithmic approaches struggle to interpret complex data and balance competing figures of merit in this nascent technology. As systems scale-up, these manual processes can limit uptime, incur substantial engineering time and cost, and become a critical bottleneck. Addressing this challenge is essential to enable practical, large-scale quantum computing.
