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Qedma and HQC2 boost quantum chemistry accuracy 50x

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September 9, 2026 by Ivy Delaney

Researchers at the University of Copenhagen and the Technical University of Denmark, collaborating with Qedma Quantum Computing, achieved a 30-50× improvement in quantum chemistry accuracy using Qedma’s QESEM error reduction software on IBM’s Aachen quantum processor, the company says. The study, part of the Q-CHEMION project, explored the potential energy surface of a water molecule and demonstrated how error mitigation can enhance the reliability of calculations on current, noisy quantum computers.

“We’re extremely pleased with the results of this collaborative study that clearly illustrates how our error mitigation software can help bridge the gap between today’s noisy quantum devices and the high-accuracy quantum computations required for future scientific applications,” said Qedma CEO and Co-founder Dr. Asif Sinay. Prof. Stephan P. A. Sauer of the University of Copenhagen noted that accuracy is important in quantum chemistry, as even small errors can impact results.

QESEM Error Mitigation Achieves 30-50x Accuracy in Quantum Chemistry

This advance addresses a critical limitation of current quantum computers, which are susceptible to noise that compromises the reliability of results. QESEM’s patented approach enables more complex quantum workloads with improved accuracy without requiring fully fault-tolerant hardware. Postdoctoral researcher Renato Olarte Hernandez at University of Copenhagen added that the results demonstrate the potential of approaches such as QESEM to help achieve the high levels of precision required for quantum chemistry applications. Qedma CEO and Co-founder Dr.

We’re extremely pleased with the results of this collaborative study that clearly illustrates how our error mitigation software can help bridge the gap between today’s noisy quantum devices and the high-accuracy quantum computations required for future scientific applications.

Dr. Asif Sinay, CEO and Co-founder at Qedma
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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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