Multiscale light-matter dynamics in quantum materials: from electrons to topological superlattices

Fuente: arXiv
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Hauptverfasser: Razakh, Taufeq Mohammed, Linker, Thomas, Luo, Ye, Piroozan, Nariman, Pennycook, John, Kumar, Nalini, Musaelian, Albert, Johansson, Anders, Kozinsky, Boris, Kalia, Rajiv K., Vashishta, Priya, Shimojo, Fuyuki, Hattori, Shinnosuke, Nomura, Ken-ichi, Nakano, Aiichiro
Format: Preprint
Veröffentlicht: 2025
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author Razakh, Taufeq Mohammed
Linker, Thomas
Luo, Ye
Piroozan, Nariman
Pennycook, John
Kumar, Nalini
Musaelian, Albert
Johansson, Anders
Kozinsky, Boris
Kalia, Rajiv K.
Vashishta, Priya
Shimojo, Fuyuki
Hattori, Shinnosuke
Nomura, Ken-ichi
Nakano, Aiichiro
author_facet Razakh, Taufeq Mohammed
Linker, Thomas
Luo, Ye
Piroozan, Nariman
Pennycook, John
Kumar, Nalini
Musaelian, Albert
Johansson, Anders
Kozinsky, Boris
Kalia, Rajiv K.
Vashishta, Priya
Shimojo, Fuyuki
Hattori, Shinnosuke
Nomura, Ken-ichi
Nakano, Aiichiro
contents Light-matter dynamics in topological quantum materials enables ultralow-power, ultrafast devices. A challenge is simulating multiple field and particle equations for light, electrons, and atoms over vast spatiotemporal scales on Exaflop/s computers with increased heterogeneity and low-precision focus. We present a paradigm shift that solves the multiscale/multiphysics/heterogeneity challenge harnessing hardware heterogeneity and low-precision arithmetic. Divide-conquer-recombine algorithms divide the problem into not only spatial but also physical subproblems of small dynamic ranges and minimal mutual information, which are mapped onto best-characteristics-matching hardware units, while metamodel-space algebra minimizes communication and precision requirements. Using 60,000 GPUs of Aurora, DC-MESH (divide-and-conquer Maxwell-Ehrenfest-surface hopping) and XS-NNQMD (excited-state neural-network quantum molecular dynamics) modules of MLMD (multiscale light-matter dynamics) software were 152- and 3,780-times faster than the state-of-the-art for 15.4 million-electron and 1.23 trillion-atom PbTiO3 material, achieving 1.87 EFLOP/s for the former. This enabled the first study of light-induced switching of topological superlattices for future ferroelectric 'topotronics'.
format Preprint
id arxiv_https___arxiv_org_abs_2509_00966
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Multiscale light-matter dynamics in quantum materials: from electrons to topological superlattices
Razakh, Taufeq Mohammed
Linker, Thomas
Luo, Ye
Piroozan, Nariman
Pennycook, John
Kumar, Nalini
Musaelian, Albert
Johansson, Anders
Kozinsky, Boris
Kalia, Rajiv K.
Vashishta, Priya
Shimojo, Fuyuki
Hattori, Shinnosuke
Nomura, Ken-ichi
Nakano, Aiichiro
Computational Physics
Light-matter dynamics in topological quantum materials enables ultralow-power, ultrafast devices. A challenge is simulating multiple field and particle equations for light, electrons, and atoms over vast spatiotemporal scales on Exaflop/s computers with increased heterogeneity and low-precision focus. We present a paradigm shift that solves the multiscale/multiphysics/heterogeneity challenge harnessing hardware heterogeneity and low-precision arithmetic. Divide-conquer-recombine algorithms divide the problem into not only spatial but also physical subproblems of small dynamic ranges and minimal mutual information, which are mapped onto best-characteristics-matching hardware units, while metamodel-space algebra minimizes communication and precision requirements. Using 60,000 GPUs of Aurora, DC-MESH (divide-and-conquer Maxwell-Ehrenfest-surface hopping) and XS-NNQMD (excited-state neural-network quantum molecular dynamics) modules of MLMD (multiscale light-matter dynamics) software were 152- and 3,780-times faster than the state-of-the-art for 15.4 million-electron and 1.23 trillion-atom PbTiO3 material, achieving 1.87 EFLOP/s for the former. This enabled the first study of light-induced switching of topological superlattices for future ferroelectric 'topotronics'.
title Multiscale light-matter dynamics in quantum materials: from electrons to topological superlattices
topic Computational Physics
url https://arxiv.org/abs/2509.00966