Predicting physics efficiently with hybrid hardware

Luca Manneschi

doi:10.1038/s43588-025-00922-6

2025-12-10

PRE

Luca Manneschi *

Matthew O. A. Ellis

DOI：10.1038/s43588-025-00922-6

原文链接

摘要

En 中文

近期研究表明，通过将问题映射到神经形态器件架构上，可以验证量子力学建模在材料性能方面的效率。

Keyword:

quantum-mechanical modeling

material properties

neuromorphic devices

hybrid hardware

efficient prediction

期刊

Nature Computational Science

IF:

18.3

论文数:

3.1K

被引数:

4.0K

机构

The University of Sheffield

学者数:

558

论文数: 262

被引数: 0

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