Q-STAR and Plug and Play pick five quantum startups

Quemix has been selected as one of only five companies to join the Quantum Startup Accelerator Program run by Q-STAR and Plug and Play Japan. The program, part of the Cabinet Office’s Council for Science, Technology and Innovation Strategic Innovation Promotion Program (SIP) Phase 3, focuses on applying advanced quantum technologies to real-world challenges. Q-STAR, a Japanese organization fostering quantum technology’s industrialization, includes “more than 160 member companies, universities, and research institutions,” creating a broad network for Quemix as it advances its business development toward practical quantum computing applications.

Quemix Selected for Q-STAR and Plug and Play Accelerator Program

Quemix will receive business development support for three months from dedicated teams at Q-STAR and Plug and Play, using a startup-first approach. Quemix aims to advance its business development toward “the practical application and industrialization of quantum computers in simulation and related fields,” a goal supported by Plug and Play’s expertise and network as a Silicon Valley-based accelerator.

Founded in 2019, Quemix concentrates its research and development on algorithms for fault-tolerant quantum computers, including the patented “Probabilistic Imaginary-Time Evolution (PITE),” a quantum chemistry calculation algorithm. The company states its vision is “realizing the future humanity has dreamed of through quantum technology,” and Quemix is actively pursuing the practical application of quantum computing in materials computation and simulation by 2030.


Quemix is a private quantum software venture headquartered in Tokyo, Japan, backed by investors including TerraSky, JIC and SCSK. Established in 2019, the company concentrates its research and development on algorithms for fault-tolerant quantum computers, and markets the Quloud materials computation platform alongside Quloud-Mag and a quantum technology support programme. Quemix has secured twelve patent families and published nine papers in the last twelve months, demonstrating a consistent output of intellectual property.


Recent activity shows a strong focus on practical applications of its technology. Quemix has established research partnerships with major automotive manufacturers including Honda, Nissan, Toyota and Denso, exploring quantum computing’s potential in materials science and simulation. These collaborations have yielded developments such as a jointly created quantum algorithm with Honda R&D that accelerates density functional theory calculations, and work with Toyota and the University of Tokyo on efficient task allocation for quantum chemistry.


In addition, Quemix received funding from NEDO for a project with Tohoku University focused on applying quantum computers to battery materials simulation, and is collaborating with Sumitomo Rubber Industries on addressing the readout problem in quantum computing. SCSK is a shareholder in Quemix and a partner in the co-development of POD readout, a technique designed to reduce bottlenecks in quantum measurement.

Stay current

See today’s quantum computing news on Quantum Zeitgeist for the latest breakthroughs in qubits, hardware, algorithms, and industry deals.

Avatar of Ivy Delaney

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.

Latest Posts by Ivy Delaney: