Physics-aware training for the physical machine learning model building

In recent decades,machine learning has emerged as a very powerful computational method.Because of its exceptional successes in computer science and engineering,machine learning has ignited research interest in other disciplines,including biology,chemistry,physics,and finance.Machine learning models,which are usually regarded as mathematical models,have traditionally been implemented on the basis of digital computing platform(Figure 1A).The increasing prevalence of machine learning has been accompanied by a rapid increase of computing requirements,outpacing Moore’s law.Therefore,researchers have been committed to the development of analog computing hardware platforms to overcome the inherent limitations of computing resources.