Diraq and QM Technologies Showcase AI Integration with Quantum Computers Using NVIDIA DGX Quantum

Transforming Quantum Computing with AI Integration



In a significant advancement that merges classical computing power with quantum technologies, Diraq and QM Technologies Inc. have announced a historic collaboration involving the integration of Graphics Processing Units (GPUs) and silicon-based quantum processors utilizing the NVIDIA DGX Quantum architecture. This pioneering development marks a leap forward in real-time communication capabilities between quantum hardware and NVIDIA's Grace-Hopper superchips at impressive speeds of just 3.3 microseconds.

This collaboration took place in Diraq's laboratories in Sydney, where engineers from both companies showcased how leveraging GPU acceleration can effectively tackle critical challenges faced within quantum computing realms. The research team successfully implemented three disparate applications that address underlying scaling challenges. These applications include enhancements in real-time readout processes, the automation of calibration using advanced machine learning techniques, and the acceleration of quantum state preparations—tasks once limited to post-processing approaches.

Remarkably, these results were achieved in just a week following the installation of the DGX Quantum system at Diraq's facilities. The architecture's capacity to exert a swift and profound impact on quantum computing research emphasizes its revolutionary potential. By combining NVIDIA's Grace Hopper architecture with QM's OPX1000 control system, Diraq's quantum processors now harness real-time AI capabilities alongside GPU-accelerated computations.

Andrew Dzurak, the CEO and Founder of Diraq, remarked on the profound implications of merging classical computing with next-generation quantum systems. He stated, "The importance of integrating classical computing power with future quantum computers can't be understated. This collaboration pushes the limits of real-time quantum control, highlighting the remarkable integration potential of Diraq's silicon qubit arrays. We would not be able to achieve these results so fast if it weren't for our partnerships with QM and NVIDIA."

A hallmark accomplishment of this endeavor was the implementation of correlated readouts in real time, building upon methodologies derived from Diraq's existing research. This intricate task of signal processing typically exceeds the computational powers of conventional FPGAs, showcasing the necessity of GPU acceleration in modern quantum computing advances. Additionally, through the utilization of machine learning algorithms on GPUs, Diraq achieved automated calibration processes that traditionally entailed extensive manual tuning, saving valuable time and resources.

Itamar Sivan, CEO and Co-Founder of QM, expressed confidence in the integration of quantum-AI technology, stating, "When we first envisioned DGX Quantum, we knew the real test would be whether quantum computing teams could achieve meaningful results quickly. Diraq's success in developing three distinct applications within a week proves that quantum-AI integration has moved beyond the hype stage. We're seeing researchers solve real problems by combining quantum and classical processing in ways that weren't possible before."

Central to these advancements is the low latency of 3.3 microseconds in the feedback loop between the quantum processor and GPU. This rapid communication is essential for effective practical quantum computing, enabling commands to be dispatched and responses garnered before quantum information deteriorates—a critical requirement for optimal functionality in quantum systems.

Tim Costa, Senior Director of Quantum and CUDA-X at NVIDIA, underscored the momentous impact of this collaboration. He stated, "This collaboration exemplifies the future of computing, with GPU and QPU seamlessly integrated to expand what can be achieved with accelerated computing. DGX Quantum enables the huge advances made in AI algorithms and hardware to be brought to quantum computing workloads and allows the development of hybrid algorithms that will pioneer new areas of computing."

Looking ahead, the integration of DGX Quantum is poised to support real-time error-correction protocols on a hybrid quantum-classical architecture, aligning Diraq's hardware directly with NVIDIA's open-source quantum development platform, NVIDIA CUDA-Q. Such advancements reveal the feasibility of GPU-based control in shaping the future of quantum computing.

The outcomes of this collaboration will be highlighted during the upcoming GTC Paris 2025 event, where NVIDIA's Director of Quantum Algorithm Engineering, Elica Kyoseva, will deliver insights on the future of hybrid quantum-classical algorithm development.

About Diraq


Diraq is recognized as a global pioneer in the fabrication of quantum processors utilizing silicon 'quantum dot' technology. Founded in 2022, the company has developed proprietary technologies stemming from two decades of extensive research in the field. Headquartered in Sydney, Australia, with branches in Palo Alto, California, and Boston, Massachusetts, Diraq aims to revolutionize quantum computing by producing significant advancements facilitated by existing semiconductor manufacturing processes. Their goal seeks to enhance the societal and economic potential of quantum computing.

About QM Technologies


QM Technologies Inc. has emerged as a leader in quantum control solutions, dedicated to evolving the quantum computing landscape with its innovative Hybrid Control solutions. By synchronizing quantum and classical operations, QM strives to eliminate friction and optimize performance across technology platforms. This approach allows researchers and developers within the industry to experiment, troubleshoot, and materialize groundbreaking concepts effectively.

As quantum computing technology continues to evolve, the partnership between Diraq and QM Technologies exemplifies the integration of AI and quantum systems, paving the way for revolutionary advancements in computational capabilities.

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