This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility: Research means asking questions of the universe. For centuries, clever minds have advanced science by devising ingenious experiments designed so their results reveal something about the laws of nature as clearly and unambiguously as possible.
An international research team has now asked: Can this process be automated? Can artificial intelligence develop new ideas for experiments? The answer is a clear yes.
In various areas of physics, AI can propose experiments that enable more precise results than experiments designed by humans. In the journal Nature, the team presented the current state of this new approach to research. This is a typical situation in experimental physics: You have a laboratory full of equipment—perhaps lasers, lenses and mirrors, perhaps different detectors and electronic components.
All of these can be combined in an almost incomprehensible number of ways. From this vast range of experimental possibilities, you have to select one that can provide new insights into the universe. Normally, this requires intuition and a great deal of experience.
But sometimes even that is not enough, as Mario Krenn discovered. Today, he is a professor of machine learning in science at the University of Tübingen. As a student in Vienna, he was working on the setup for a quantum experiment.
But neither he nor the other members of his research group could find a suitable experimental configuration capable of demonstrating the desired quantum effects. So Krenn decided to ask the computer. He described the individual components available to him mathematically, then had an algorithm search for combinations of these components that would result in a meaningful experiment.
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