Quantum advantage in learning from experiments

Quantum technology promises to revolutionize how we learn about the physical world. An experiment that processes quantum data with a quantum computer could have substantial advantages over conventional experiments in which quantum states are measured and outcomes are processed with a classical computer. We proved that quantum machines could learn from exponentially fewer experiments than the number required by conventional experiments. This exponential advantage is shown for predicting properties of physical systems, performing quantum principal component analysis, and learning about physical dynamics. Furthermore, the quantum resources needed for achieving an exponential advantage are quite modest in some cases. Conducting experiments with 40 superconducting qubits and 1300 quantum gates, we demonstrated that a substantial quantum advantage is possible with today's quantum processors.

Automated summary

Quantum technology, particularly quantum machine learning, offers substantial advantages over conventional methods in terms of efficiency and effectiveness. By conducting experiments with quantum processors, we have demonstrated the exponential advantage of quantum machines in predicting physical properties, performing quantum principal component analysis, and learning about physical dynamics. The resources required for achieving this advantage are also relatively modest in some cases.