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Infleqtion And Nvidia Reduce Physical-to-Logical Qubit Ratio in Quantum Computers

A lot of advancements are being made in quantum computing that move beyond the basics of quantum processors (QPUs) and hardware fundamentals. Companies are expanding out into the architectural realm, subsystems for these machines are…

The Next Platform

Publisher

Sep 16, 2026 at 3:36 PM UTC · 5 분 소요

Infleqtion And Nvidia Reduce Physical-to-Logical Qubit Ratio in Quantum Computers
Image via The Next Platform

Key Signal

98 physical data qubits used

Last Updated

2일 전

번역 중…

A lot of advancements are being made in quantum computing that move beyond the basics of quantum processors (QPUs) and hardware fundamentals. Companies are expanding out into the architectural realm, subsystems for these machines are being pulled together, and quantum software and algorithms are being developed, while efforts to make quantum computing scalable and integrated into HPC environments are being made.

Still, a key to getting quantum computing from the research phase to commercial viability is solving the error correction challenge. Qubits are notoriously fragile and can split apart – and lose their quantum properties – due to various “noises” like light, sound, temperature, or the activity of other qubits, and a quantum system that makes too many errors isn’t commercially viable. To improve error correction, multiple entangled physical qubits are grouped together to create logical qubits.

However, that comes at a price, from the technical challenges of needing thousands of physical qubits to make a single logical one to cooling and manufacturing costs to adding more noise. Given that, reducing the number of physical qubits per logical qubit is important.

“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.”

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