35 citations · 64 across the 7 of their papers we have counts for
7 papers
Quantum Annealing: Optimisation, Sampling, and Many-Body Dynamics
Steven Abel, Andrei Constantin, Luca A. Nutricati
Quantum annealing is a computational paradigm in which optimisation problems are mapped onto the energy landscape of an interacting quantum system and explored through its dynamica…
Berry's phase on photonic quantum computers
Steven Abel, Iwo Wasek, Simon Williams
We formulate a continuous-variable quantum computing (CVQC) algorithm to study Berry's phase on photonic quantum computers. We demonstrate that CVQC allows the simulation of charge…
Qumode Tensor Networks for False Vacuum Decay in Quantum Field Theory
Steven Abel, Michael Spannowsky, Simon Williams
False vacuum decay in scalar quantum field theory (QFT) is a cornerstone of early Universe cosmology and high energy physics, yet its real-time dynamics is essentially inaccessible…
Real-Time Scattering Processes with Continuous-Variable Quantum Computers
Steven Abel, Michael Spannowsky, Simon Williams
We propose a framework for simulating the real-time dynamics of quantum field theories (QFTs) using continuous-variable quantum computing (CVQC). Focusing on ()-dimensional $φ…
Simulating quantum field theories on continuous-variable quantum computers
Steven Abel, Michael Spannowsky, Simon Williams
We delve into the use of photonic quantum computing to simulate quantum mechanics and extend its application towards quantum field theory. We develop and prove a method that levera…
Training Neural Networks with Universal Adiabatic Quantum Computing
Steve Abel, Juan Carlos Criado, Michael Spannowsky
The training of neural networks (NNs) is a computationally intensive task requiring significant time and resources. This paper presents a novel approach to NN training using Adiaba…
Completely Quantum Neural Networks
Steve Abel, Juan C. Criado, Michael Spannowsky
Artificial neural networks are at the heart of modern deep learning algorithms. We describe how to embed and train a general neural network in a quantum annealer without introducin…