The Department of Energy’s Oak Ridge National Laboratory, NVIDIA, and HPE will seek to open new insights into quantum computing and identify potential strategies toward the integration of quantum, artificial intelligence and high-performance computing for scientific discovery.

“Maintaining America’s leadership in high-performance computing requires us to build the bridge to the next era of computing: accelerated quantum supercomputing,” said U.S. Secretary of Energy Chris Wright. “The deep collaboration between our national laboratories, startups and industry partners like NVIDIA is central to this mission — and NVIDIA NVQLink provides the critical technology to unite world-class GPU supercomputers with emerging quantum processors, creating the powerful systems we need to solve the scientific challenges of our time.”

At ORNL’s Oak Ridge Leadership Computing Facility (OLCF), lab researchers will leverage NVIDIA NVQLink and NVIDIA CUDA-Q programming tools — designed to integrate classical computing clusters with quantum processors for performing control tasks like quantum error correction and running hybrid quantum-classical algorithms. NVIDIA CUDA-Q also allows running GPU-accelerated simulations mimicking actual quantum hardware. These are crucial tools for a novel testbed that will explore and compare these advanced technologies side by side.

The platforms will run on an NVIDIA GB200 NVL72 system built by HPE that will be installed in early 2026 at the OLCF data center, also home to Frontier, the world’s first exascale supercomputer.

“Our partnerships at ORNL with NVIDIA and HPE usher in a new era of hybrid computing,” said ORNL Director Stephen Streiffer. “We look forward to taking these steps toward quantum acceleration of HPC.”

Quantum initiative continues to push quantum computing capabilities 

Quantum computing relies on quantum bits, or qubits, to store information. Qubits, unlike the binary bits used in classical computing, can exist in more than one state simultaneously via quantum superposition, which allows combinations of physical values to be encoded on a single object. 

Researchers theorize that ability could lead to faster, more efficient ways to solve complex scientific problems that so far have defied traditional approaches — even at exascale, which offers computing speeds faster than a quintillion calculations per second, and for emerging AI models. 

“We believe the future of scientific computing lies in finding ways to harmonize these three computing platforms and draw on the unique strengths of each approach,” said Georgia Tourassi, director of ORNL’s Computing and Computational Sciences Directorate, which oversees the OLCF.

High-resolution digital simulations on a quantum computer could help crack computationally expensive fundamental questions in physics, chemistry, materials science and more.

The primary obstacle to reaching that quantum computing has been the relatively high error rate caused by the delicate nature of qubits. Various solutions remain in development. The final technology for quantum computing also has yet to be settled, with various systems employing neutral atoms, trapped ions, superconductors and other materials.

As a first step, ORNL’s machine will maneuver around some of those roadblocks by combining classical technology, such as the traditional GPUs and CPUs that power most supercomputers, with hybrid computing platforms through CUDA-Q that use NVIDIA technology to both connect with quantum processors as well as emulate their quantum operations without the noise from degrading qubits. The platform will combine HPE’s integration expertise and NVIDIA’s hardware innovation to advance state-of-the-art AI research while enabling the investigation of iterative, low-latency decoding that quantum error correction requires.

Because the platform won’t be tied to a single quantum computing protocol, researchers can adapt approaches as needed to apply those operations across the widest array of technologies and work in tandem with other machines, from the Frontier supercomputer to ORNL’s recently acquired Quantum Brilliance and IQM quantum computers.