Infleqtion and Nvidia Reduce the Physical-to-Logical Qubit Ratio

Quantum computing development now extends beyond quantum processors and hardware fundamentals. Companies are working on system architectures, subsystems, software, algorithms, scalability, and integration with high-performance computing environments.

A major barrier to commercial quantum computing remains error correction. Qubits are highly fragile and can lose their quantum properties because of noise from light, sound, temperature, or interactions with other qubits. Systems with excessive errors are not commercially practical, so multiple entangled physical qubits are combined to form more reliable logical qubits.

This approach introduces substantial costs. Creating one logical qubit can require thousands of physical qubits, while additional qubits increase cooling and manufacturing requirements and may introduce more noise. Reducing the number of physical qubits required for each logical qubit is therefore an important objective.

“An unofficial law of physics is ‘there’s no such thing as a free lunch,’” Quantinuum executives wrote earlier this year. “Creating high quality, low error-rate logical qubits often costs many physical qubits, thus reducing the size of calculations you can run, despite your new, lower-than-ever error rates.”

Researchers, standards organizations, and quantum-computing vendors are working to improve this ratio. Sheir Yarkoni, director of quantum software for Qarakal Quantum, said the startup’s Pangaea architecture is intended to reduce physical-qubit requirements by a factor of 10. D-Wave has made a similar claim for its developing dual-rail superconducting systems. In a paper published in March, Quantinuum described technology that produces 48 error-corrected and 64 error-detected logical qubits from 98 physical qubits.

At the IEEE Quantum Week event in Toronto, Infleqtion executives said that integrating the company’s open-source quantum low-density parity-check (qLDPC) software library with Nvidia’s CUDA-Q Logical produced a validated, high-rate quantum error-correction code. The code uses 98 physical data qubits for 18 logical qubits, or approximately 5.4 physical qubits per logical qubit, representing an 18.4 percent encoding rate.

Infleqtion uses neutral atoms in its Sqale systems to create qubits. Using an early-access version of CUDA-Q Logical, the company built a hypergraph-product simplex (HGPS) code block, created stabilizers and logical operators, and implemented the required algebra, according to Victory Omole, a senior quantum research engineer at Infleqtion.

The code includes 49 X checks and 49 Z checks. These checks detect specific types of physical errors, and each has weight six. The canonical logical representatives returned by the qLDPC software have weight four.

“Many familiar QEC constructions devote a large number of data qubits to each logical qubit,” Omole wrote. “High-rate qLDPC codes change that arithmetic by encoding multiple logical qubits in one block while keeping each stabilizer check sparse. The appeal is obvious: if the rest of the architecture cooperates, more of the machine can carry useful logical information.”

The condition that the rest of the architecture must cooperate is significant. Although the physical-to-logical qubit ratio is important, other parts of a quantum-computing system must preserve the result across the full stack. These include syndrome ancilla qubits used for error-syndrome measurements, scheduling, readout, control, and classical decoding.

CUDA-Q Logical addresses parts of this problem. Infleqtion’s qLDPC software supplies the mathematical foundation for the code, while CUDA-Q Logical provides the logical ownership, block allocation, and compilation model.

“CUDA-Q Logical supplies the logical ownership, block allocation, and compilation model,” Omole wrote. “The code interface in CUDA-Q Logical takes sparse row supports. A small adapter converts the dense NumPy arrays, after which the qLDPC software-generated checks and logical operators can be declared as an 18-port CUDA-Q Logical code.”

By combining qLDPC with CUDA-Q Logical, Infleqtion engineers built and validated the code structure and then created a compiler pipeline. The resulting block contains multiple logical qubits within a single encoded structure. The pipeline builds on architecture research conducted by Fred Chong, Infleqtion’s chief scientist for quantum software.

The integration also confirmed that the stabilizer matrices commute with the X and Z checks. The CUDA-Q code has 18 logical ports, along with 49 X checks and 49 Z checks. The compiled workflow also supports two distinct logical-qubit owners within one encoded block.

“This integration focuses on code construction, logical ownership, and compilation,” Omole wrote. “In coming work, we plan to extend this workflow through physical syndrome extraction, neutral-atom noise modeling, detector generation, and decoder benchmarking.”

Research in Chong’s laboratory focuses on reconfigurable neutral-atom arrays. Their parallel operations and flexible connectivity make them suitable for high-rate qLDPC codes.

“For our team, the opportunity is to trace that promise through a real machine model,” Chong wrote. “That means accounting for where ancillas live, how atoms move, which checks can run in parallel, how leakage and loss appear in readout, and whether the classical decoder can keep up with the syndrome stream. Logical performance emerges from the coordination of hardware, control, compilation, and classical compute.”

Infleqtion’s broader quantum-computing plans

Infleqtion was founded in 2007 after spinning out of atomic-physics research at the University of Colorado. The company initially operated under the name ColdQuanta and rebranded as Infleqtion in 2022. Its roadmap targets more than 1,000 logical qubits by 2030.

The work with Nvidia and CUDA-Q Logical is part of a broader period of activity for the company. Recent developments include a $20 million follow-on contract with NASA to continue developing the Quantum Gravity Gradiometer Pathfinder, a Jet Propulsion Laboratory mission intended to fly the first space-based quantum gravity sensor; the opening of the Colorado Quantum Innovation Center; and three projects awarded through the U.S. Department of Energy’s Genesis Mission.

The Genesis Mission is intended to accelerate research and innovation using AI. Its quantum program includes the goal of deploying the world’s first fault-tolerant quantum computer.

Infleqtion has also announced plans to combine its neutral-atom quantum systems and sensors with Cisco Systems’ quantum networking portfolio through a joint research and development effort. The work is intended to help scale quantum computing by networking multiple systems.

Cisco began developing a quantum network architecture in 2025 and unveiled its Universal Quantum Switch in April. The prototype is designed to connect quantum systems from different vendors that use different modalities, as well as quantum sensors, within a single network.

Neutral atoms can interact naturally with photons, which carry quantum information across networks. Infleqtion’s engineers said this makes the company’s systems suitable for network connections and compatible with Cisco’s vision for a modality-agnostic quantum network architecture.