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The energy of data is the value of a real function of distances between data in metric spaces. The name energy derives from Newton's gravitational potential energy, which is also a function of distances between physical objects. One of the advantages of working with energy functions (energy statistics) is that even if the data are complex objects, such as functions or graphs, we can use their real-valued distances for inference. Other advantages are illustrated and discussed in this review. Concrete examples include energy testing for normality, energy clustering, and distance correlation. Applications include genome studies, brain studies, and astrophysics. The direct connection between energy and mind/observations/data in this review is a counterpart of the equivalence of energy and matter/mass in Einstein's E=mc 2 .
Székely et al. (Tue,) studied this question.