Columbia’s Yuen and Chicago’s Verresen win $100,000 Microsoft quantum grant

Columbia’s Henry Yuen and University of Chicago’s Ruben Verresen will each receive $100,000 as winners of the 2026 Microsoft Quantum Pioneers Program, one of five teams recognized in the software track. The collaboration began after the computer scientist and theoretical physicist found shared research interests at a 2025 conference at KITP in Santa Barbara, ultimately leading to a project focused on measurement-based topological hardware.

Their work explores how measuring a quantum system can become an integral part of the computation, allowing quantum and classical computers to work together; Yuen said, “Our goal is to discover just how effectively near-term quantum computers and classical computers can work together to solve hard problems.” Microsoft intends for this research to guide the programming and use of future quantum computers.

Yuen and Verresen Awarded Microsoft Quantum Pioneers Grant

This funding places them among five winning teams in the software track, enabling exploration of how intertwined quantum measurements and classical computation can maximize the potential of near-term quantum processors. The researchers plan to investigate the trade-offs between simple measurements and the need for more complex quantum resources, a critical step toward practical quantum algorithms. Their project centers on a potentially novel approach: integrating measurement of a quantum system directly into the computational process itself.

Each measurement alters the quantum state, and the resulting data guides the classical computer in determining subsequent measurements, creating a dynamic feedback loop. Microsoft stated that progress in quantum computing depends on advances that work together, noting that new physical devices need reliable measurement and control, error-correcting codes need practical implementations, and algorithms need to make effective use of the resources available. Research collaborations bring complementary expertise to these connected challenges. The team will focus on two primary areas of inquiry, both directly relevant to Microsoft’s topological quantum computing architecture and Majorana quantum processors.

First, they will assess the computational limits achievable with the hardware’s most basic measurement capabilities, identifying when additional quantum resources become essential. Second, they will explore whether enhanced classical processing can unlock greater performance from the same quantum hardware. Yuen explained, “We want to understand both the possibilities and the limits of this approach, so we can guide how future quantum computers are programmed and used.” He added that they hope this research can help inform the quantum industry on what can be done with this nascent technology.

Progress in quantum computing depends on advances that work together. New physical devices need reliable measurement and control; error-correcting codes need practical implementations; and algorithms need to make effective use of the resources available.

Microsoft
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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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