Osaka University Installs Japan’s Third Superconducting Quantum Computer

Osaka University in Japan now has Japan’s third superconducting quantum computer, thanks to a group of collaborative researchers.

According to a consortium announcement, Osaka University now has Japan’s third superconducting quantum computer.

However, users in Japan can access the newly designed computer through the cloud. Compared to earlier installations, this one had more components sourced domestically and made by the research team.

Organizations such as Osaka University’s Center for Quantum Information and Quantum Biology, RIKEN, AIST’s Advanced Semiconductor Research Center, NIT’s Superconducting ICT Laboratory, e-trees, Inc., Amazon Web Services, NTT Corporation (NTT), Fujitsu Limited, QunaSys Inc., QuEL, Inc., and SEC are all part of the partnership.

Researchers in Japan will be able to remotely execute quantum algorithms, enhance and validate software operations, and investigate use cases after the partners provide cloud access to the freshly built computer on December 22, 2023.

Osaka University

Details about Osaka University Quantum Computer

Based on the same architecture as RIKEN’s first superconducting quantum computer, introduced to Japanese customers as a non-commercial cloud service on March 27, 2023, the newly built superconducting quantum computer uses a 64 qubit chip supplied by RIKEN.

Besides the fridge, the research team used more components made in the United States for the new quantum computer. The research team will use the new quantum computer to test components manufactured in Japan after confirming that the computer and its components offer enough performance.

The next step is for the research team to use the new machine while improving its software and other systems, such as handling cloud-based heavy workloads. The computer, according to the research team, will propel advancements in machine learning and practical quantum algorithms, open up new avenues for use in drug and material discovery, and help solve optimization problems to reduce environmental impact.

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Written by Robin Khokhar
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