Self-testing is a method to infer the underlying physics of a quantum experiment in a black
box scenario. As such it represents the strongest form of certification for quantum systems. In …

The meeting between Natural Language Processing (NLP) and Quantum Computing has
been very successful in recent years, leading to the development of several approaches of …

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 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 …

Abstract Quantum Natural Language Processing (QNLP) deals with the design and
implementation of NLP models intended to be run on quantum hardware. In this paper, we …

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 …