Quantum Hardware, High Performance Computing

Qblox Control Systems Enable HPE’s Scalable Quantum Integration

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June 25, 2026 by Ivy Delaney

Qblox control systems are now part of Hewlett Packard Enterprise’s strategy to integrate quantum technologies with existing high-performance computing and artificial intelligence infrastructure. The collaboration aims to bridge the gap between quantum processors and classical supercomputing environments, a critical step as quantum systems move beyond isolated laboratory settings. Qblox’s modular control hardware is designed to support development of these hybrid classical-quantum environments across multiple qubit modalities, promising versatility for a range of quantum processors. “HPE brings unparalleled AI-native and high-performance computing infrastructure and a determined vision of the industry’s future to our partnership,” said Niels Bultink, CEO of Qblox. This work intends to advance computational workflows and enable scalable quantum technologies applicable to both scientific and industrial challenges.

Qblox Control Systems Enable HPE’s Hybrid Classical-Quantum Integration

This isn’t simply about adding quantum processors; it’s about establishing a reliable interface connecting those processors to classical HPC systems, addressing a key bottleneck in the field. Qblox systems are engineered to provide the scalable, deterministic control electronics necessary for these increasingly complex architectures as they transition from isolated laboratory settings to full integration with HPC and AI environments. This collaboration will focus on developing integrated testbeds for hybrid algorithm co-design, software interoperability, and system-level performance benchmarking, essential steps in refining computational workflows that leverage both HPC and quantum resources. Masoud Mohseni, Director of HPE Quantum and Senior Distinguished Technologist at HPE Labs, underscored the importance of scalable, high-precision control in merging classical HPC with quantum computing, noting that hybrid architectures support interoperability and performance at scale. Qblox’s role is not merely to supply hardware, but to enable the development of tailored hybrid classical-quantum computing environments designed for large-scale scientific and industrial workloads, representing a significant step toward realizing the full potential of quantum computation.

HPE brings unparalleled AI-native and high-performance computing infrastructure and a determined vision of the industry’s future to our partnership.

Niels Bultink, CEO of Qblox
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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