Exponential quantum advantages in learning quantum observables from classical data

Understand

Quantum computers are believed to bring computational advantages in simulating quantum many body systems.

• However, recent works have shown that classical machine learning algorithms are able to predict numerous properties of quantum systems with classical data.
• Despite various examples of learning tasks with provable quantum advantages being proposed, they all involve cryptographic functions and do not represent any physical scenarios encountered in laboratory settings.
• In this paper we prove quantum advantages for the physically relevant task of learning quantum observables from classical (measured out) data.