  The Supercritical Fluid (SCF) is known to exhibit salient dynamic and
thermodynamic crossovers and inhomogeneous molecular distribution. But the
question as to what basic physics underlies these microscopic and macroscopic
anomalies remains open. Here, using an order parameter extracted by machine
learning, the fraction of gas-like (or liquid-like) molecules, we find
simplicity and universality in SCF: First, all isotherms of a given fluid
collapse onto a single master curve described by a scaling relation. The
observed power law holds from the high-temperature and pressure regime down to
the critical point where it diverges. Second, phase diagrams of different
compounds collapse onto their master curves by the same scaling exponent,
thereby demonstrating a putative law of corresponding supercritical states in
simple fluids. The reported results support a model of the SCF as a mixture of
two interchangeable microstates, whose spatiotemporal dynamics gives rise to
unique macroscopic properties.

Soft Condensed Matter