IonQ helps build a faster, secure space network with new launch

Skyloom Global, an IonQ company, now has 84 operational optical communication terminals in low-Earth orbit following a July 16, 2026 launch aboard a SpaceX Falcon 9 rocket. The terminals, installed on York Space Systems satellites, support the Space Development Agency’s (SDA) Proliferated Warfighter Space Architecture (PWSA) and represent one of the largest operational laser communication payload footprints currently in orbit. “We’re proud to continue supporting SDA with proven, U.S.-built optical communications technology at scale,” said IonQ’s President of Quantum Platform, Jordan Shapiro. These spacecraft aim to provide high-throughput, low-latency communications essential to national defense.

Skyloom OCTs Expand to 84 Units in Low-Earth Orbit

Shapiro said this milestone reflects years of focused industrialization and a commitment to strengthening the nation’s space-based communications infrastructure. The deployed spacecraft are engineered to deliver high-throughput, low-latency communications critical for national defense applications and interoperability with SDA’s optical communication standards. The growing network of Skyloom OCTs is designed to form resilient, data-rich mesh networks, anticipating the evolution of space networking toward higher-capacity optical architectures. With the third deployment of Transport Layer Tranche 1 space vehicles, SDA is nearing completion of its initial constellation, relying on this technology for mission-enabling connectivity.

We’re proud to continue supporting SDA with proven, U.S.-built optical communications technology at scale.

Jordan Shapiro, President of Quantum Platform at IonQ
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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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