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arXiv · 2011.11073

Diagrammatic Design and Study of Ans\"{a}tze for Quantum Machine Learning

Richie Yeung
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Abstract

Given the rising popularity of quantum machine learning (QML), it is important to develop techniques that effectively simplify commonly adopted families of parameterised quantum circuits (commonly known as ans\"{a}tze). This thesis pioneers the use of diagrammatic techniques to reason with QML ans\"{a}tze. We take commonly used QML ans\"{a}tze and convert them to diagrammatic form and give a full description of how these gates commute, making the circuits much easier to analyse and simplify. Furthermore, we leverage a combinatorial description of the interaction between CNOTs and phase gadgets to analyse a periodicity phenomenon in layered ans\"{a}tze and also to simplify a class of circuits commonly used in QML.

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Richie Yeung. 2020-11-22. Diagrammatic Design and Study of Ans\"{a}tze for Quantum Machine Learning. https://arxiv.org/abs/2011.11073

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