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Qarakal Quantum to detail modular quantum computer in Cannes

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November 4, 2026 by Ivy Delaney

Qarakal Quantum will illustrate a modular, von Neumann-like fault-tolerant quantum computer architecture at the inaugural World Quantum Cannes Festival. Sheir Yarkoni, Director of Quantum Software at Qarakal Quantum, will deliver the keynote presentation on Wednesday, November 18, at 10:40 a.m, the company says. from the Palais des Festivals and Congrès de Cannes. The event aims to transform scientific breakthroughs into real-world impact, and Qarakal Quantum’s presentation will focus on its quantum bus technology, the interconnect enabling scalable architectures.

Qarakal Quantum’s Keynote at World Quantum Cannes Festival

Qarakal Quantum focuses on realizing a scalable computer composed of interconnected building-block modules, requiring a fault-tolerant interconnect for unified operation. This architecture orchestrates specialized quantum processing, memory and control to achieve fault tolerance for scalable systems, and the keynote will specifically address the quantum bus technology enabling this modularity. Yarkoni leads advanced research and development at the intersection of quantum algorithms, error correction and hardware-aware architecture.

“Realizing this vision requires a natively fault-tolerant interconnect that allows separate quantum modules to operate as one computer,” Qarakal Quantum stated in a release. The company joins other experts at the inaugural festival, bringing together subject matter experts, industry end users, policy makers and investors. Qarakal Quantum announced its participation from its base in Tel Aviv, Israel.

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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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