The Seeker quantum processor from Quantum Circuits now supports Nvidia's CUDA-Q, enabling developers to combine quantum computing with AI and machine learning.
Quantum Circuits announced that its dual-rail Seeker quantum processing unit now supports Nvidia’s CUDA-Q programming language, a move designed to help developers combine quantum computing with AI and machine learning workloads as the two technologies increasingly intersect.
Nvidia’s CUDA-Q is a quantum programming language that can run on any hardware and supports both C++ and Python. It’s especially useful for combining quantum computing with HPC and AI workloads.
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Since Nvidia isn’t building its own quantum computer, the CUDA-Q platform is completely hardware-agnostic, says 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. It includes Microsoft, Nvidia, Oak Ridge National Laboratory, Quantinuum, Quantum Circuits, and Rigetti Computing on its steering committee.
“Really, it’s QIR that is the load-bearing project in this equation,” says Sanders. “But QIR does not have a marketing team, and as the implementation is stable and feature-complete, it doesn’t need one.”
CUDA-Q is already supported by IonQ, QuEra, Quantinuum, Rigetti and several other quantum computing manufacturers —Nvidia says that it currently integrates with 75% of publicly available quantum processing units.
Nvidia announced AWS Braket support at the end of 2024. CUDA-Q is also available on Nvidia’s own Quantum Cloud platform, which combines GPUs and quantum processors with AI.
The other major quantum computing platform is IBM’s Qiskit, which Quantum Circuits was already supporting. Qiskit also works with IBM, IonQ, Rigetti, Alice & Bob, and Quantinuum, and it’s available on Amazon Bracket, Microsoft Azure Quantum, and the IBM Quantum Platform.
A different take on quantum hardware
Quantum Circuits’ dual-rail chip means that it combines two different quantum computing approaches — superconducting resonators with transmon qubits. The qubit itself is a photon, and there’s a superconducting circuit that controls the photon. “It matches the reliability benchmarks of ions and neutral atoms with the speed of the superconducting platform,” says Andrei Petrenko, head of product at Quantum Circuits.
There’s another bit of quantum magic built into the platform, he says — error awareness. “No other quantum computer tells you in real time if it encounters an error, but ours does,” he says. That means that there’s potential to correct errors before scaling up, rather than scaling up first and then trying to do error correction later.
In the near-term, the high reliability and built-in error correction makes it an extremely powerful tool for developing new algorithms, says Petrenko. “You can start kind of opening up a new door and tackling new problems. We’ve leveraged that already for showing new things for machine learning.”
It’s a different approach to what other quantum computer makers are taking, 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.
Right now, Seeker is only available via Quantum Circuits’ own cloud platform and only has eight qubits.
“We’re in alpha access right now,” says Petrenko, “working with select partners. This gives us an opportunity to understand the classes of problems that our close partners are interested in right now. We learn from them, and they learn from us about our unique feature set.”
Only having eight qubits puts the company far behind the industry leaders. But while other quantum computing companies have more qubits, as they scale up, the number of errors grows quickly. “The quantum computing industry can’t wait for such a brute-force method,” says Sanders. “It requires different approaches to building a qubit.” That creates a window of opportunity for companies experimenting with other approaches, such as Quantum Circuits.
“The approach could prove to be beneficial, but more work is needed across the industry to realize a fully qualified, general purpose quantum computer,” says Sanders.
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