Machine Learning Aids Classical Modeling of Quantum Systems | Quanta Magazine

Quantum computers can't reliably execute large number of quantum interactions.

Current near-term quantum devices are still far from fulfilling that promise.

But maybe there’s a workaround, a kind of quantum compromise.

By combining a new way of modeling quantum systems with increasingly sophisticated machine learning algorithms, researchers have established a method for classical machines to model.

A computer scientist at Google Quantum AI developed a new machine-learning algorithm that can accurately predict quantum systems.

The new methods still need to be rigorously tested in laboratory experiments.

The main impact of quantum computing in the next five to 10 years will not be applications that are commercially important, scientist says.