The railway overhead contact line resembles a galaxy: energy flows through it like gravity, with trains becoming planets. The more trains draw current simultaneously, the stronger the voltage fluctuations — gravitational waves ripple through the system, threatening blackouts.
To catch dangerous rhythms, scientists created a neural network. It acts like a spectroscope — an instrument that breaks starlight into components — but for electrical characteristics. The network determines which train parameter most distorts the grid's spacetime, much like a planet's mass bends the cosmic fabric (Einstein explained this back in the last century).
Then all data on train movement and relative positions are aggregated, enabling prediction of where critical vibrations will arise. Just as matter falling into a black hole upsets the system's equilibrium, electrical disturbances can cause failures. Tests on real lines showed the method pinpoints weak spots quickly and without thousands of extra measurements.
Low-frequency oscillations in the overhead line can sometimes be heard as a low hum — the 'singing' of dozens of trains merging into an electric choir.
In Isaac Asimov's 'Foundation' saga, scientists predicted the collapse of empires — here the neural network plays the role of a psychohistorian for power systems.