Quantum machine learning is a rapidly growing field at the intersection of quantum
technology and artificial intelligence. This review provides a two-fold overview of several key …

Open source software is becoming crucial in the design and testing of quantum algorithms.
Many of the tools are backed by major commercial vendors with the goal to make it easier to …

The ZX-calculus is a graphical language for reasoning about quantum computation that has
recently seen an increased usage in a variety of areas such as quantum circuit optimisation …

We present a method for reducing the number of non-Clifford quantum gates, in particularly
T-gates, in a circuit, an important task for efficiently implementing fault-tolerant quantum …

We analyze the barren plateau phenomenon in the variational optimization of quantum
circuits inspired by matrix product states (qMPS), tree tensor networks (qTTN), and the …

In this paper, we propose a general scheme to analyze the gradient vanishing phenomenon,
also known as the barren plateau phenomenon, in training quantum neural networks with …

We provide conceptual and mathematical foundations for near-term quantum natural
language processing (QNLP), and do so in quantum computer scientist friendly terms. We …

The ZX-calculus is a graphical language for reasoning about ZX-diagrams, a type of tensor
networks that can represent arbitrary linear maps between qubits. Using the ZX-calculus, we …

This paper has two tightly intertwined aims:(i) to introduce an intuitive and universal
graphical calculus for multi-qubit systems, the ZX-calculus, which greatly simplifies …

Translations between the quantum circuit model and the measurement-based one-way
model are useful for verification and optimisation of quantum computations. They make …