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Prof. Dr. Michael Hartmann (Uni Erlangen)

Quantum Computing: from random gate sequences to neural networks

Summary: Quantum processors have recently reached a threshold where they can do a specific computation much faster than classical computing technology. This means that the output of these processors is becoming so complex that it can no longer be predicted by classical simulations. On the other hand, this also means that it is becoming impossible to analyze the output of these devices with classical computing technology. In this talk I will first describe the first experiment that performed such a computation beyond the classically accessible domain, which employs random gate sequences. I’ll then turn to explain how quantum convolutional neural networks can be used to analyze the output of quantum processors for the example of quantum phase recognition.