机器学习时代反应和光谱学的原子模拟-- Quo Vadis？
Atomistic Simulations for Reactions and Spectroscopy in the Era of Machine Learning -- Quo Vadis?
摘要：
使用精确的能量函数的原子模拟可以提供分子水平的洞察力，以了解气体和凝聚相中分子的功能运动。再加上最近开发的和目前正在努力将其与机器学习技术相结合，这为使这种动态模拟更接近现实提供了一个独特的机会。这个观点从其他人在这个领域的努力和你自己的一些工作中描绘了这个领域的现状，并讨论了开放的问题和未来的前景。
英文摘要：
Atomistic simulations using accurate energy functions can provide molecular-level insight into functional motions of molecules in the gas- and in the condensed phase. Together with recently developed and currently pursued efforts in integrating and combining this with machine learning techniques provides a unique opportunity to bring such dynamics simulations closer to reality. This perspective delineates the present status of the field from efforts of others in the field and some of your own work and discusses open questions and future prospects.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
