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Institute wins Award for Quantum Compilation Research at MICRO

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November 13, 2026 by Ivy Delaney

Engineers at the Beijing Quantum Information Science Research Institute, working with collaborators Technology and the Institute of Physics, Chinese Academy of Sciences, earned the Distinguished Artifact Runner-Up Award at the prestigious MICRO conference on November 2, 2026. The team’s research presented as “QROB: Quantifying Realization Overhead in Quantum Compilation via Reverse Construction,” introduces a new method for benchmarking quantum compilation. The work is published as a preprint on arXiv.

MICRO is considered one of the “Big Four” conferences in computer architecture, alongside ISCA, HPCA and ASPLOS, and the award recognizes the quality of the code and data supporting the QROB research results. This recognition reflects international peer validation of the reproducibility of their work.

MICRO 2026 Award for Quantum Compilation Research

The presentation detailed a novel approach to evaluating quantum compilation performance, addressing a key challenge in optimizing quantum software and hardware. Listed as a Class An international academic conference by the China Computer Federation (CCF), MICRO focuses on advanced computing system research and provides a platform for showing innovations in computer microarchitecture, compilation technology and hardware-software co-design. The Artifact Evaluation (AE) committee assessed the accompanying code, data and experimental materials, prioritizing quality and support for research verification, reproduction and open sharing.

Of the 213 papers accepted for the main conference, only 94 submitted materials for review, and the QROB research was among the three results to win related awards. The QROB framework addresses the critical problem of quantifying overhead in quantum compilation and identifying areas for further optimization.

The team adopted a reverse construction method to generate samples with reference solutions, establishing a basis for evaluating compilation overhead across both noisy and fault-tolerant quantum computing architectures, MICRO says. This approach also generates high-quality training data for artificial intelligence-assisted compilation, supporting collaborative optimization of quantum software and hardware. Li Jintao is the first author of the published paper, with Wang Zhengan, Sun Xiaoming and Fan Heng listed as corresponding authors.

The team has made the paper and associated code publicly available via arXiv and GitHub, facilitating further research and collaboration.

👉 More information
🗞 QROB: Quantifying Realization Overhead in Quantum Compilation via Reverse Construction
✍️ Jintao Li et al.
🧠 ArXiv: https://arxiv.org/abs/2609.07776
📰 Source: https://baqis.ac.cn/news/detail/?cid=5845

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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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