Quantum Computers are well known for their code breaking abilities but that's not all they can do, in the June 9 2022 issue of the journal Science researchers report they have found a quantum learning algorithm that achieves an exponential speed increase over the that of any known conventional algorithm both in predicting how a quantum system, for example an atom or a molecule, changes over time, and also in its ability to extract useful information from noisy input data. It perhaps should be noted that a brain frozen to liquid nitrogen temperatures is bound to contain a lot of noisy data regardless of how carefully it was frozen. This is the abstract of the article:
"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."
John K Clark
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