Researcher Wins €1.5M to Hunt Errors in Quantum Computers

Jonas Helsen has been awarded €1.5 million via a European Research Council Starting Grant to tackle a central challenge in quantum computing: reliably verifying performance. Unlike conventional bits, qubits use the quantum-mechanical principles of superposition and entanglement, allowing them to exist as combinations of zero and one, properties that promise faster calculations but introduce extreme fragility.

Measuring a qubit alters its state, preventing simple error checks like those used in traditional computers; Helsen will spend five years developing methods to analyze and certify fault-tolerant quantum computers. “We are now at a stage where we can create qubits that are good enough for us to detect errors in them,” says Helsen.

Helsen Awarded €1.5M to Analyze Fault-Tolerant Quantum Computers

This funding will support five years of research dedicated to identifying the root causes of errors within these complex systems, a challenge that has long outpaced hardware development. Helsen intends to build on years of experience assessing the quality of physical qubits, applying those lessons to the more advanced realm of fault tolerance. The fragility of qubits presents a unique obstacle to error correction; unlike conventional bits, a qubit’s quantum state is altered by the very act of measurement.

This prevents the simple error checks used in traditional computing, necessitating entirely new approaches to verification. “The theoretical models for quantum error correction have existed for thirty years,” Helsen explains, “Only now is the hardware becoming good enough for us to put them into practice.” His work will investigate whether errors originate within the qubits themselves, during qubit interactions, or within the error-correction process itself.

Helsen also plans to develop a ‘digital twin’ of a quantum computer for testing purposes, a feat complicated by the limitations of conventional computing. Simulating quantum-mechanical systems is inherently difficult because it requires significant computational resources. Consequently, he will create algorithms designed to mimic qubit behavior. “Methods for analyzing FTQCs will become very important,” Helsen asserts, emphasizing the growing need for rigorous performance evaluation as the technology matures.

We are now at a stage where we can create qubits that are good enough for us to detect errors in them.

Jonas Helsen, researcher in CWI’s Algorithms & Complexity group
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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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