TY  - JOUR

T1  - Predicting physics efficiently with hybrid hardware

JO  - Nature Computational Science

UR  - https://doi.org/10.1038/s43588-025-00922-6

PY  - 2025/12/10

AU  - Manneschi L

AU  - Ellis MOA

ED  - 

DO  - DOI: 10.1038/s43588-025-00922-6

PB  - Springer Science and Business Media LLC

Y2  - 2025/12/20

ER  -