"A trained ANN can replace existing numerical solvers, enabling fast and scalable simulations of many-body systems to shed light on outstanding phenomena such as the formation of black-hole binary systems or the origin of the core collapse in dense star clusters," write the researchers in their paper.
研究人员在论文中写道:“训练有素的人工神经网络可以取代现有的数值求解器,使快速可扩展的多体模拟系统阐明尚待解决的现象,如黑洞双星系统的形成以及密集星团核心坍缩的起因。”
【新型神经网络可以用快1亿倍速度解决"三体问题"】相关文章:
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