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National Science Foundation funds cold control chips for quantum computer growth without overheating

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November 3, 2026 by Ivy Delaney

The National Science Foundation is funding research led by Ethan Arnault, assistant professor in Syracuse University’s Department of Electrical Engineering and Computer Science, to address a critical barrier to scaling quantum computers: overheating. Each additional qubit requires more microwave cables, introducing heat into the extremely cold environment necessary for function.

Arnault’s research focuses on placing control and measurement electronics on the same chip as qubits, currently limited by insufficient precision in existing chip-based devices. “The underlying physics of multiterminal Josephson circuits has been well worked through by the device physics community,” says Arnault, “What we’re doing here is trying to translate those results into real applications.”

Multi-Terminal Josephson Circuits Enable On-Chip Cold Control

The research, funded by the National Science Foundation’s Electrical, Communications and Computing Systems division, directly addresses the escalating heat issue that constrains the scalability of superconducting quantum computers. Ethan Arnault’s team is designing Josephson parametric amplifier bolometers, combining sensing and signal boosting capabilities, with the goal of detecting single microwave photons within the 4 to 8 gigahertz range, frequencies commonly used by qubits, and resetting within billionths of a second.

This rapid response time is critical for maintaining the accuracy of qubit readout, a limitation of existing nanobolometer-based cold control methods. These new devices use the properties of multi-terminal Josephson circuits, moving beyond the constraints of simpler two-terminal designs.

Researchers will fine-tune these devices using electrical current and voltage controls on a graphene-based component, aiming to detect single microwave photons in the 4 to 8 gigahertz range, the frequencies commonly used by qubits and to reset almost instantly, within billionths of a second. The project also explores coordinated microwave signals generated by collective electron movement, investigating whether this natural synchronization can produce exceptionally clean, low-noise signals suitable for qubit control.

“What devices can create low-noise microwave signals that could control qubits? On the other hand, what devices can measure those qubits as efficiently as possible?” asks Arnault, highlighting the dual focus of the research. DC-biased Josephson emitters, an existing cold control method, produce imprecise signals, while nanobolometers are too slow for accurate qubit readout.

By exploiting the richer signal behavior available in multi-terminal Josephson circuits, Arnault’s designs aim to overcome both shortcomings. The team anticipates that these advancements will not only facilitate the construction of larger superconducting quantum computers but also provide valuable tools for other applications, including highly sensitive sensors and amplifiers for materials science and supercooled systems. The project’s long-term vision involves combining both the bolometer and the coordinated microwave signal generator to enable entirely on-chip power measurement, eliminating the need for external equipment.

This integrated approach promises to significantly reduce heat leakage and streamline the control and readout processes. “We’re tackling two sides of the problem,” Arnault explains, emphasizing the comprehensive nature of the research. The award also supports the development of the next generation of quantum scientists, funding a graduate student and postdoctoral researcher, and providing research opportunities for undergraduate and high school students, alongside the creation of new quantum engineering courses at Syracuse University.

The underlying physics of multiterminal Josephson circuits has been well worked through by the device physics community.

Ethan Arnault, Assistant Professor in the Department of Electrical Engineering and Computer Science at Syracuse University
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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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