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 …

Quantum computers are expected to surpass the computational capabilities of classical
computers during this decade and have transformative impact on numerous industry sectors …

We present t| ket⟩, a quantum software development platform produced by Cambridge
Quantum Computing Ltd. The heart of t| ket⟩ is a language-agnostic optimising compiler …

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 …

Monoidal category theory serves as a powerful framework for describing logical aspects of
quantum theory, giving an abstract language for parallel and sequential composition, and a …

We provide a self-contained introduction to quantum theory using a unique diagrammatic
language. Far from simple visual aids, the diagrams we use are mathematical objects in …

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 present a completely new approach to quantum circuit optimisation, based on the ZX-
calculus. We first interpret quantum circuits as ZX-diagrams, which provide a flexible, lower …

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 …