Ultracompact programmable silicon photonics using layers of low-loss phase-change material Sb S Blundell, T Radford, IA Ajia, D Lawson, X Yan, M Banakar, DJ Thomson, ...
arXiv preprint arXiv:2409.12582, 2024
2 2024 Inverse design of unitary transmission matrices in silicon photonic coupled waveguide arrays using a neural adjoint model TW Radford, PR Wiecha, A Politi, I Zeimpekis, OL Muskens
ACS Photonics, 2024
1 2024 Supporting data for" Inverse design of unitary transmission matrices in silicon photonic coupled waveguide arrays using a neural adjoint model" TW Radford, O Muskens
University of Southampton, 2025
2025 Neural Adjoint, Inverse Design for Arbitrary Unitary Matrix Recreation in Coupled Waveguide Arrays Using Programmable Phase Change Materials T Radford, P Wiecha, A Politi, O Muskens
Quantum 2.0, QW3A. 39, 2024
2024 Deep-learning informed design of unitary operators in silicon photonics using programmable phase change materials. T Radford, P Wiecha, O Muskens, A Politi
Machine Learning in Photonics, PC1301709, 2024
2024 Deep-learning enabled design of the flow of light in complex nanophotonic devices OL Muskens, T Radford, N Dinsdale, P Wiecha, A Politi
Smart Photonic and Optoelectronic Integrated Circuits 2023, PC124250D, 2023
2023