Source | www.popularmechanics.com | Caroline Delbert
Computer scientists have shown that a special neural network is likely able to solve simpler exemplars of the chaotic three-body problem, reports Tech Xplore. If the results seem hard to parse, that’s because the three-body problem and its implications are also pretty hard to parse.
The three-body problem is an arm of cosmology, where the “bodies” are celestial, like calculating where planets are in relation to each other over time. (Chinese sci-fi author Liu Cixin used the term as a pun for the title of his Hugo Award-winning 2015 novel about murdered astrophysicists.) Applications range from the earliest low-tech ship navigators to modern theories of spaceflight like gravity assists, and the mathematical complexity of the problem itself has made it interesting to both mathematicians and computer scientists for many years.
We sometimes think of space as empty because of popular misconceptions, but even in the relative vacuum, space is filled with clashing gravity fields, magnetic fields, solar winds (a misnomer, because there’s no air), and more. Everything is pushed and pulled by different forces—so many forces and with such complexity that the “three bodies” are almost completely unpredictable from moment to moment, even if we know where they just were an instant before.