Quantum Circuits Lands on Nvidia’s CUDA-Q Platform

Key points

• Quantum Circuits’ dual-rail Seeker quantum processing unit now supports Nvidia’s CUDA-Q programming language, allowing developers to combine quantum computing with AI and machine learning workloads.
• CUDA-Q is a hardware-agnostic platform that can run on any hardware and supports both C++ and Python, making it a great fit for high-performance computing.
• Quantum Circuits’ unique approach to quantum computing, using a dual-rail chip that combines superconducting resonators with transmon qubits, provides high reliability and built-in error correction, making it an extremely powerful tool for developing new algorithms.

According to sources, Quantum Circuits has announced that its dual-rail Seeker quantum processing unit now supports Nvidia’s CUDA-Q programming language. This move is designed to help developers combine quantum computing with AI and machine learning workloads as the two technologies increasingly intersect. CUDA-Q is a quantum programming language that can run on any hardware and supports both C++ and Python, making it a great fit for high-performance computing.

As reported by James Sanders, semiconductor industry analyst at TechInsights, CUDA-Q is built on top of Quantum Intermediate Representation (QIR), an open-source project that’s allied with the Linux Foundation. The project includes Microsoft, Nvidia, Oak Ridge National Laboratory, Quantinuum, Quantum Circuits, and Rigetti Computing on its steering committee. Sanders notes that QIR is the load-bearing project in this equation, but it doesn’t have a marketing team, and as the implementation is stable and feature-complete, it doesn’t need one.

CUDA-Q is already supported by several quantum computing manufacturers, including IonQ, QuEra, Quantinuum, and Rigetti. Nvidia announced AWS Braket support at the end of 2024, and CUDA-Q is also available on Nvidia’s own Quantum Cloud platform, which combines GPUs and quantum processors with AI.

In comparison, IBM’s Qiskit is another major quantum computing platform that works with IBM, IonQ, Rigetti, Alice & Bob, and Quantinuum. It’s available on Amazon Braket, Microsoft Azure Quantum, and the IBM Quantum Platform. However, Qiskit only supports Python, not C++, making CUDA-Q a better fit for high-performance computing.

Quantum Circuits’ unique approach to quantum computing, using a dual-rail chip that combines superconducting resonators with transmon qubits, provides high reliability and built-in error correction. This approach is different from other quantum computer makers, confirms TechInsights’ Sanders. According to Sanders, this dual-rail method combines the best of both types of qubits, lengthening coherence time, plus integrating error correction.

Currently, Seeker is only available via Quantum Circuits’ own cloud platform and only has eight qubits. However, the company is working with select partners to understand the classes of problems that they’re interested in, and to learn from them about their unique feature set. While other quantum computing companies have more qubits, as they scale up, the number of errors grows quickly. This creates a window of opportunity for companies experimenting with other approaches, such as Quantum Circuits. As Sanders notes, the approach could prove to be beneficial, but more work is needed across the industry to realize a fully qualified, general-purpose quantum computer. Microsoft and Nvidia are likely to play a crucial role in the development of quantum computing, and their involvement in QIR and CUDA-Q is a significant step forward.

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