An essential problem in quantum machine learning is to find quantum-classical separations between learning models. However, rigorous and unconditional separations are lacking for supervised learning.

Understanding the quantum universe is not an easy thing. Intuitive notions of space and time break down in the tiny realm of subatomic physics, allowing for behavior that seems, to our macro ...

The very first proposed application of quantum computers can be traced back to Feynman’s idea of simulating quantum physics on a quantum device. Together with factoring 1, simulation of quantum ...

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