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Teaching Quantum Physics to a Computer

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Using neural networks, physicists taught a computer to predict the results of quantum experiments.

An international collaboration led by ETH Zurich scientists used machine learning to teach a computer to predict the outcomes of quantum experiments.


Researchers at ETH Zurich in Switzerland have used machine learning to teach a computer to predict the outcomes of quantum experiments, which could be essential for testing future quantum computers.

The new machine-learning software enables a computer to "learn" the quantum state of a complex physical system based on experimental observations and to predict the outcomes of hypothetical measurements.

The researchers first showed the system handwritten samples, and it learned to replicate each letter, word, and sentence. The computer also calculated a probability distribution that expressed mathematically how often a letter is written in a certain way when it is preceded by some other letter.

Although quantum physics is more complicated than a person's handwriting, the team says the principle for machine learning is the same.

The standard technique requires about 1 million measurements to achieve the desired accuracy, but the new method realized this accuracy with a smaller number of measurements.

From ETH Zurich
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