Qarakal, Quantum Elements win $2.4M for catalyst quantum simulator

Qarakal Quantum and Quantum Elements will jointly develop a quantum simulation platform following a $2.4 million grant from the Israel-U.S. Binational Industrial Research and Development Foundation. The project aims to improve the design of chemical reactions on material surfaces, a process essential to industries generating between $5 and $6 trillion annually. “Our architecture is modular by design and tailorable for real-world workloads—that’s what makes this collaboration work,” said Dr. Nissan Maskil, CEO and co-founder of Qarakal Quantum. The companies will combine Qarakal’s hardware with Quantum Elements’ software to create workflows for industrially relevant catalyst problems.

Qarakal Quantum and Quantum Elements Secure $2.4M BIRD Foundation Grant

The Israel-U.S. Heterogeneous catalysis, essential to the manufacture of an estimated 80-90% of chemical products, will be the initial focus of this effort, addressing limitations in current computational methods. High-performance computing techniques, while powerful, often require significant approximations when modeling systems with strong electronic correlation, surface defects and complex bond-breaking pathways.

The project’s core strategy involves combining Qarakal Quantum’s modular superconducting quantum hardware with Quantum Elements’ software suite, which advances fault-tolerant quantum computing through AI-driven co-design, error suppression, error correction and decoders, the company says. This integrated approach aims to create a validated prototype capable of translating industrially relevant catalyst problems into quantum-ready computational workflows.

The modularity of the Qarakal system is intended to allow for hardware specialization at system scale, assigning dedicated physical resources to distinct computational roles. Quantum Elements’ contribution centers on its digital-twin technology, which models the behavior and noise environment of Qarakal’s superconducting system, according to the company. This modeling will inform decisions regarding compilation, calibration, pulse-level execution, error suppression and algorithm design, optimizing the use of limited quantum hardware time.

Izhar Medalsy, Co-Founder and CEO of Quantum Elements, explained that “Useful quantum applications cannot be developed in isolation from the hardware that has to run them,” emphasizing the need for a co-design strategy. The companies plan to produce benchmark chemistry models and quantum algorithms, complete with application programming interfaces intended for use by chemists and materials engineers. The anticipated outcome extends beyond immediate problem-solving; the collaboration envisions a broader quantum-enabled simulation platform for industrial catalyst and materials development.

Potential users include catalyst manufacturers, specialty-materials companies, chemical suppliers and industrial research and development organizations already using computational screening, high-performance computing and laboratory experimentation. The global chemical processing industry, a key target for this technology, generates between $5 and $6 trillion annually according to a MarketLine study, highlighting the potential economic impact of improved catalyst design.

Qarakal Quantum’s approach differs from industry trends focused solely on increasing qubit counts, instead prioritizing the development of integrated systems capable of performing on real-world workloads. Their Pangaea architecture connects specialized quantum modules through a proprietary quantum bus and routing motherboard, aiming to reduce qubit requirements, minimize noise, accelerate algorithm execution and create a deployable platform for scientific, industrial, and dual-use applications.

Quantum Elements’ digital twins will model each module in detail, enabling informed design decisions before hardware optimization and scaling alongside the evolving system, the firm reports. Maskil added that catalyst chemistry provides meaningful problems to solve and an opportunity to help industry with advanced reactions that are very hard to simulate today. The BIRD Foundation, established in 1977 by the U.S. and Israeli governments, supports collaborative projects between companies in both countries, providing funding covering up to 50 percent of development costs, up to $1.5 million per project, without taking equity.

Our architecture is modular by design and tailorable for real-world workloads – that’s what makes this collaboration work.

Dr. Nissan Maskil, CEO and co-founder of Qarakal Quantum
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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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