首页|Zhejiang Laboratory Reports Findings in Machine Learning (MLatom Software Ecosys tem for Surface Hopping Dynamics in Python with Quantum Mechanical and Machine L earning Methods)
Zhejiang Laboratory Reports Findings in Machine Learning (MLatom Software Ecosys tem for Surface Hopping Dynamics in Python with Quantum Mechanical and Machine L earning Methods)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting from Zhejiang, People's Repub lic of China, by NewsRx journalists, research stated, "We present an open-source MLatom@XACS software ecosystem for on-the-fly surface hopping nonadiabatic dyna mics based on the Landau-Zener-Belyaev-Lebedev algorithm. The dynamics can be pe rformed via Python API with a wide range of quantum mechanical (QM) and machine learning (ML) methods, including ab initio QM (CASSCF and ADC(2)), semiempirical QM methods (e.g., AM1, PM3, OMx, and ODMx), and many types of ML potentials (e. g., KREG, ANI, and MACE)."
ZhejiangPeople's Republic of ChinaAs iaCyborgsEmerging TechnologiesMachine LearningSoftware
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