Topologically robust programmable processing arrays using light and matter skyrmions
Abstract
Photonic computing offers a low-power, high-bandwidth paradigm for information processing; however, the analog nature of conventional architectures means that intrinsic noise and fabrication imperfections greatly impact performance, thereby severely limiting scalability. Recent work on optical skyrmions offers a route to overcoming these limitations by exploiting perturbation-resilient topological invariants of the optical field for computation. Crucially, owing to its relative novelty, an architectural perspective on integrating individual components that manipulate topological charge into a functional system remains an important open challenge. In this paper, we take concrete steps toward system-level design by introducing a platform-independent architecture for skyrmion-based processing, built around a modular library of topologically robust optical primitives, including generators, converters, registers, and adders. This framework enables the synthesis and arithmetic manipulation of topological numbers within a unified programmable architecture. We then experimentally validate this approach using multichannel arrays, demonstrating accurate charge readout and robustness against perturbations in practical optical systems. These results provide a scalable foundation for topologically robust programmable processing arrays, paving the way for compact and integrated photonic processing circuits.
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BibTeX
@article{liu2026topologically,
title = {{Topologically robust programmable processing arrays using light and matter skyrmions}},
author = {Ruofu Liu and Yunqi Zhang and Yuxi Cai and Yihan Liu and Zhenglin Li and Tianxin Wang and Yifei Ma and Zimo Zhao and Runchen Zhang and Zhi-Kai Pong and Stephen M. Morris and Chao He},
journal = {Nature Communications},
year = {2026},
month = oct,
doi = {10.1038/s41467-026-78249-7},
url = {https://www.nature.com/articles/s41467-026-78249-7},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Topologically robust programmable processing arrays using light and matter skyrmions
AU - Ruofu Liu
AU - Yunqi Zhang
AU - Yuxi Cai
AU - Yihan Liu
AU - Zhenglin Li
AU - Tianxin Wang
AU - Yifei Ma
AU - Zimo Zhao
AU - Runchen Zhang
AU - Zhi-Kai Pong
AU - Stephen M. Morris
AU - Chao He
PY - 2026
DA - 2026/10/08
JO - Nature Communications
DO - 10.1038/s41467-026-78249-7
UR - https://www.nature.com/articles/s41467-026-78249-7
AB - Photonic computing offers a low-power, high-bandwidth paradigm for information processing; however, the analog nature of conventional architectures means that intrinsic noise and fabrication imperfections greatly impact performance, thereby severely limiting scalability. Recent work on optical skyrmions offers a route to overcoming these limitations by exploiting perturbation-resilient topological invariants of the optical field for computation. Crucially, owing to its relative novelty, an architectural perspective on integrating individual components that manipulate topological charge into a functional system remains an important open challenge. In this paper, we take concrete steps toward system-level design by introducing a platform-independent architecture for skyrmion-based processing, built around a modular library of topologically robust optical primitives, including generators, converters, registers, and adders. This framework enables the synthesis and arithmetic manipulation of topological numbers within a unified programmable architecture. We then experimentally validate this approach using multichannel arrays, demonstrating accurate charge readout and robustness against perturbations in practical optical systems. These results provide a scalable foundation for topologically robust programmable processing arrays, paving the way for compact and integrated photonic processing circuits.
SN - 2041-1723
ER -