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DOE OSTI · 3391495

HPC-Driven Modeling with ML-Based Surrogates for Magnon-Photon Dynamics in Hybrid Quantum System

Abstract

Here, we introduce a hybrid computational framework that merges HPC-based numerical solvers with physics-informed ML surrogates for efficient modeling of magnon-photon interactions. By running short-duration, high-fidelity Maxwell-LLG simulations and feeding their results into an ML model, we substantially cut simulation time while achieving accurate predictions across larger spatiotemporal domains.

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BibTeXRIS

Song, Jialin [Simon Fraser University, Burnaby, BC (Canada)], Tang, Yingheng [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Ren, Pu [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Takayoshi, Shintaro [University of Wisconsin, Madison, WI (United States)], Sawant, Saurabh [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)], Zhu, Yujie [University of Wisconsin, Madison, WI (United States)], Hu, Jia-Mian [University of Wisconsin, Madison, WI (United States)], Nonaka, Andy [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States). International Computer Science Institute (ICSI)], Mahoney, Michael W. [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States)], Erichson, Benjamin [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); University of California, Berkeley, CA (United States). International Computer Science Institute (ICSI)], Yao, Zhi Jackie [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)]. 2025-05-18. HPC-Driven Modeling with ML-Based Surrogates for Magnon-Photon Dynamics in Hybrid Quantum System. https://doi.org/10.23919/aces66556.2025.11052493

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