Outputs (2)

Simulating quantum field theories on continuous-variable quantum computers (2024)
Journal Article
Abel, S., Spannowsky, M., & Williams, S. (2024). Simulating quantum field theories on continuous-variable quantum computers. Physical Review A, 110(1), Article 012607. https://doi.org/10.1103/physreva.110.012607

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 leverages this form of continuous-variable quantum computing (CVQC) to repro... Read More about Simulating quantum field theories on continuous-variable quantum computers.

Training neural networks with universal adiabatic quantum computing (2024)
Journal Article
Abel, S., Criado, J. C., & Spannowsky, M. (2024). Training neural networks with universal adiabatic quantum computing. Frontiers in Artificial Intelligence, 7, Article 1368569. https://doi.org/10.3389/frai.2024.1368569

The training of neural networks (NNs) is a computationally intensive task requiring significant time and resources. This article presents a novel approach to NN training using adiabatic quantum computing (AQC), a paradigm that leverages the principle... Read More about Training neural networks with universal adiabatic quantum computing.