Present Plans

1. Quantum circuit optimization
2. Quantum Boltzmann Machines

So-called Boltzmann Machines (BMs) define a machine learning method that aims to model probability distributions and has played a central role in the development of deep learning methods.

It has since been shown that BMs are universal approximators of discrete probability distributions, meaning that they can approximate any discrete distribution arbitrarily well. Our research group has lately conducted several investigations of BMs applied to quantum-mechanical problems, with several interesting results.

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