Quantinuum Connecting Classical and Quantum Computing With NVIDIA

The NVIDIA QODA platform for quantum-classical applications brings the C++ language into the quantum ecosystem. Alex Chernoguzov, the Chief Engineer of Commercial Products at Quantinuum, is helping to bring this programming platform to Quantinuum’s world-class quantum hardware. 

“The more languages that support quantum, the better, because that opens up an opportunity for different software specialists to start programming in quantum environments,” Chernoguzov said. “We need to develop a new workforce that's educated on quantum information science topics and capable of generating new algorithms that can run on quantum computers.”

Tony Uttley, president and chief operating officer at Quantinuum, said platforms such as QODA are important for the company and the quantum computing industry. 

“At Quantinuum, our objective is to accelerate quantum computing’s utility to the world,” Uttley said. “By bringing forward additional tools like QODA, we expand the number of brilliant people aiming their talents at getting the most out of today’s quantum computers.”

Why we need QODA

Quantum computers speak a different language than classical machines. Also, the current landscape doesn’t have many effective quantum compilers to support interoperability with classical machines. The NVIDIA QODA platform aims to change that. Until recently, most quantum programming languages were based on Python because many scientists are familiar with it, Chernoguzov said.

“QODA adds quantum capabilities to C++ because this language is what's often used to program high performance computing machines,” he said. “Having a C++ dialect expands the possible languages that you can program quantum with.”

A classical-quantum bridge 

Chernoguzov said interoperability between classical and quantum systems was another core goal of this project. 

“Let’s say you have a hybrid program that has some classical parts and some quantum parts,” he said. “You compile the program. There is a classical piece that you can run on a CPU or a GPU, and there is a quantum piece that you need to send to a quantum computer. In a sense, you could look at it as a quantum processor acting as a co-processor for the other classical processors you need for your program. After completion, you gather everything together and do some more classical computations and repeat the process.”

Quantinuum’s H1 quantum machine will act as a quantum processor working in conjunction with larger classical systems. If a computational task has an element that could be solved more easily by a quantum architecture, this task can be passed off to H1 so researchers can solve quantum problems. This process will currently work in a similar fashion to other cloud-based services with programs submitted for execution over the cloud to H1. 

Quantinuum hardware and the NVIDIA QODA platform are bridging the gap between existing classical architectures and emerging quantum resources and using the strengths of each system to solve complex problems.

“Let’s say you want to model a complex chemical molecule. Atomic interactions are best handled by a quantum computer,” Chernoguzov said, “but directing the overall program flow to tell it what to model and how to model it is best done by the classical computers.” NVIDIA’s QODA platform helps reveal a world where these two ecosystems coexist and thrive together. 

Chernoguzov also explained the benefits of the Quantum Intermediate Representation (QIR) Alliance: a group of people and organizations who are committed to improving interoperability for quantum machines. This group’s work forms the basis for the hybrid approach that uses both classical and quantum machines.

“Interoperability in the quantum world is possible and the QIR is a good fit for that,” he said. “Quantum computers cannot do everything themselves, but classical compute is also clearly limited. We need both, and they need to work closely together to solve difficult problems that neither technology can solve on its own.”