NSF’s Virtual Lab Expands With $4M Per Team for Two Years

A 20 million investment will expand the National Science Foundation’s National Quantum Virtual Laboratory, adding five new teams to the four already developing technologies ranging from long-distance quantum networks to single-cell sensors. Each team will receive 4 million over two years to refine development plans and prepare for implementation, building capabilities to integrate quantum sensors, networks, and computers for real-world applications. This concentrated funding reflects a broader U.S. push to strengthen leadership in quantum technology, as outlined in a recent Executive Order. “Across academia, government and industry, America has an unmatched array of brilliant people working on quantum science and tech with incredible potential to improve our quality of life,” says Brian Stone, performing the duties of the NSF director, “But too often they are working independently in silos. We need to bring their talent and ideas together, and NSF is uniquely positioned to make that happen.”

NSF Funds Five Teams in National Quantum Virtual Laboratory Design

A collective $20 million in new funding from the National Science Foundation will accelerate the development of practical quantum technologies, adding five teams to an existing cohort of four already engaged in the National Quantum Virtual Laboratory program. This substantial investment underscores a concentrated effort to move quantum research beyond theoretical exploration and toward tangible applications, ranging from secure long-distance communication to advanced cellular-level sensing. The projects showcase the breadth of quantum technology being pursued; one team aims to create quantum networks capable of transmitting information at speeds approximately 100,000 times faster than current systems over distances reaching 60 miles. Another is focused on developing sensors utilizing protein-based qubits, designed to measure properties inside single cells, a capability with profound implications for biological research and medical diagnostics. A third team will focus on accelerating fault-tolerant quantum logic, unifying error-correcting code, hardware, and algorithms into a cohesive development process.

These efforts are not occurring in isolation; the projects involve partnerships with over two dozen U.S. companies including Boeing, Honeywell, and NVIDIA, as well as federal agencies like the Air Force Research Laboratory and NASA. This emphasis on collaboration is deliberate, addressing a key challenge in the field. The agency anticipates selecting the first teams to move into the implementation phase later this year, contingent upon congressional appropriations, furthering the goals outlined in the National Quantum Initiative Act passed by Congress in.

The team will design a high-fidelity quantum networking system approximately 100,000 times faster than current quantum networks and able to carry information over distances of about 60 miles.

NSF
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Ivy Delaney

Ivy Delaney has been working with neural networks and machine learning since the mid-nineties, back when a couple of hidden layers and a long afternoon of training counted as ambitious. She has watched the field go from academic curiosity to the thing quietly running underneath everything, and she brings that long view to quantum computing. For Quantum Zeitgeist she covers the ground where the two fields meet. That means quantum machine learning and the variational algorithms it leans on, and it also means the less glamorous but more interesting story of classical machine learning already doing real work inside quantum machines, decoding error-correcting codes, calibrating noisy hardware and learning the error models that simulators depend on. She writes about the hardware those algorithms have to run on too, and about the post-quantum cryptography scramble that the same hardware has set off. Her stories typically start with the paper, whether that is peer-reviewed work, conference proceedings or an arXiv preprint, with the source linked so you can hold a claim up against the research it came from. She is unimpressed by benchmarks that will not say what they beat, and by demonstrations that only work in the press release.

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