aiqbench analysis
LightStim addresses a critical bottleneck in fault-tolerant quantum computing by automating the construction of Detector Error Models (DEMs), which are essential for evaluating logical error rates across diverse quantum error correction protocols. By integrating DEM generation directly with circuit compilation, this framework enables rigorous benchmarking of complex architectures like lattice surgery without relying on tedious manual annotation. The tool significantly lowers the barrier to entry for prototyping and systematically exploring new QEC schemes, accelerating research into scalable quantum hardware.
LightStim: A Framework for QEC Protocol Evaluation and Prototyping with Automated DEM Construction
arXiv:2604.21472v3 Announce Type: replace Abstract: Fault-tolerant quantum computing increasingly demands rigorous, circuit-level evaluation of diverse quantum error correction (QEC) protocols and efficient prototyping of new ones. Such evaluation requires both the physical circuit and its Detector Error Model (DEM) to estimate end-to-end logical error rates. However, DEM construction today is performed by manual annotation, a tedious and error-prone process that effectively limits evaluation to simple memory experiments. We present LightStim, a framework that automates DEM construction concurrently with circuit compilation by maintaining a Pauli tableau augmented with measurement records, with no protocol-specific input required. We benchmark LightStim across protocols from memory experiments to end-to-end distillation circuits; cross-validation against public implementations confirms exact detector and observable counts and consistent logical error rates. Additionally, we demonstrate a novel heterogeneous cross-code lattice surgery design between surface and punctured quantum Reed-Muller codes. These capabilities together make LightStim a unified infrastructure for systematic QEC protocol evaluation and exploration. LightStim is open-sourced at https://github.com/QuTone/LightStim.
Abstract:Fault-tolerant quantum computing increasingly demands rigorous, circuit-level evaluation of diverse quantum error correction (QEC) protocols and efficient prototyping of new ones. Such evaluation requires both the physical circuit and its Detector Error Model (DEM) to estimate end-to-end logical error rates. However, DEM construction today is performed by manual annotation, a tedious and error-prone process that effectively limits evaluation to simple memory experiments. We present LightStim, a framework that automates DEM construction concurrently with circuit compilation by maintaining a Pauli tableau augmented with measurement records, with no protocol-specific input required. We benchmark LightStim across protocols from memory experiments to end-to-end distillation circuits; cross-validation against public implementations confirms exact detector and observable counts and consistent logical error rates. Additionally, we demonstrate a novel heterogeneous cross-code lattice surgery design between surface and punctured quantum Reed-Muller codes. These capabilities together make LightStim a unified infrastructure for systematic QEC protocol evaluation and exploration. LightStim is open-sourced at this https URL.
arXiv:2604.21472 [quant-ph]
(or arXiv:2604.21472v3 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2604.21472 Focus to learn more arXiv-issued DOI via DataCite
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Full text under the publisher's open licence · 244 words
Related coverage
LightStim: A Framework for QEC Protocol Evaluation and Prototyping with Automated DEM Construction
arXiv · Jun 4, 2026

News
Quantum Computing Report · Jun 7, 2026

News
Quantum Computing Report · Jul 25, 2026

Digital States 2026: AI Moves From Experiment to Infrastructure
govtech.com · Sep 24, 2026