QSI seminar series: Maria Kieferova - Macquarie University and Andre Nies - University of Auckland

Title: Quantum Boltzmann Machines For Generative Training And Tomography (Maria Kieferova)

Abstract: Boltzmann machines are physically-motivated neural networks used for data representation and generative training. Their quantum counterparts utilise quantum effects to represent complex data sets with compact models. In this talk, I will introduce different ways to generalize Boltzmann machines in the quantum setting and their connection to tomography.

Title: Random sequences of qubits (Andre Nies)

Abstract: Martin-Loef in a famous 1966 paper  formalised the intuitive notion of randomness for infinite sequences of bits via algorithmic tests. What if we replace classical bits by qubits?

We first provide a framework to formalise  such sequences as states of a suitable C* algebra.   Thereafter we introduce an analog of Martin-Loef's notion. We show that for classical bit sequences the two notions coincide.  We also discuss  quantum Kolmogorov complexity for finite sequences of qubits and its relationship to quantum Martin-Loef randomness.

The talk will be introductory.  This is joint work with Volkher Scholz.

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