Stony Brook and Brookhaven expand New York’s quantum network

A $300 million investment from New York State is fueling an expansion of the quantum network created through a partnership between the State University of New York at Stony Brook and the U.S. Department of Energy’s Brookhaven National Laboratory. Researchers at the two institutions have demonstrated a key step toward what they claim is the nation’s largest quantum network, a development intended to improve computer operations, including those powering large language models.

“New York State is committed to investing in research and innovation in emerging fields that move our society forward,” said Governor Kathy Hochul. The expanded network aims to bolster research, cybersecurity, and unlock new opportunities for New Yorkers.

Stony Brook & Brookhaven Expand Network with Free-Space Optical Link

New York’s expanding quantum network recently achieved a key milestone by successfully transmitting quantum information through open air between Stony Brook University and Brookhaven National Laboratory, extending the reach of this emerging technology beyond traditional fiber-optic cables. Researchers utilized a laser to generate quantum states of light, containing only a few photons, originating from the Quantum Watchtower at Stony Brook. These photons traveled 13 miles to Brookhaven’s Quantum Lighthouse in Upton, New York, exiting a core just five microns in diameter, less than one-tenth the width of a human hair.

This free-space optical (FSO) link, alongside facilities at Yale University, adds a wireless component to a quantum network already spanning 161 miles across Long Island and the New York City metropolitan area. The network currently connects eight nodes across several institutions, and the FSO link represents a critical step toward building a truly expansive, interconnected quantum infrastructure.

Successfully transmitting photons across free-space links demonstrates a promising path toward connecting quantum devices over long distances, a challenge that has limited the scalability of quantum communication. Brookhaven Lab Director John Hill said, “Brookhaven has long been involved in quantum information science, and this achievement represents another important step in that journey.” This free-space link is a key milestone, but it is also part of a larger roadmap leading to distributed quantum systems.

The expansion isn’t solely about distance; it’s also about capability. Researchers anticipate using the FSO link to connect future quantum computers at both Stony Brook and Brookhaven, enabling collaborative work on complex scientific challenges.

The network’s ability to transmit entangled photons, linked by the laws of quantum mechanics, through commercial fiber is now augmented by this wireless connection. SUNY President Andrea Goldsmith stated, “Extending our quantum communication network to include a wireless link is a major leap forward in our development of the Quantum Internet of Things.” SUNY Chancellor John B. added, “Quantum technology has incredible potential to address complex global challenges and revolutionize industries. With continued investment and support from Governor Hochul and the State Legislature, this partnership demonstrates SUNY’s commitment to furthering research and positioning New York as a global leader.”

New York State is committed to investing in cutting-edge research and innovation in emerging fields that move our society forward.

Governor Kathy Hochul
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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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