Quantum Hardware, Deep Tech

Industrial science body, Kyocera and QUDORA Japan team up on quantum chip cooling

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October 6, 2026 by Ivy Delaney

QUDORA Japan K.K. has been selected for a research project funded by Japan’s New Energy and Industrial Technology Development Organization (NEDO), focusing on a critical challenge in quantum computing: reliably packaging and scaling systems at extremely low temperatures.

The initiative, conducted with the National Institute of Advanced Industrial Science and Technology and Kyocera Corporation, will develop universal design rules for “Cryogenic Quantum Packaging and Design Rules Universally Applicable to Cryogenic Quantum Computers.” “Establishing universal cryogenic packaging and design rules is critical to overcoming the scaling bottlenecks in quantum hardware,” says Dr. Amado Bautista-Salvador, CEO and co-founder of QUDORA Technologies, as the project aims to position quantum computing as a successor to 5G and a tool for addressing societal problems.

NEDO Funds Cryogenic Quantum Packaging for Scalable Systems

QUDORA Japan K.K. This work falls under NEDO’s program to accelerate quantum computers for solving societal issues, explicitly linking quantum technology to advancements beyond 5G communications. The project aims to establish standardized cryogenic packaging solutions and universal design rules, essential for reliably operating high-density wiring, optical interfaces and thermal management at extremely low temperatures.

AIST will provide research collaboration, testing environments and standardized evaluation methods, while Kyocera Corporation will focus on advanced materials, packaging engineering and manufacturing design. Dr.

We at QUDORA Japan are honored that NEDO has selected a collaborative project proposal led by Kyocera, with us as a key co-proposer, and AIST participating as a research partner.

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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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