The Physics DepartmentAuthors in bold are primary researchers of Centre for Nanophotonics.
Imperfect Quantum Photonic Neural Networks
We model a quantum photonic neural network based on imperfect components, as would be the case for realistic chips.
Jacob Ewaniuk, Jacques B. Carolan, Bhavin J. Shastri and Nir Rotenberg
Imperfect Quantum Photonic Neural Networks, Adv. Quantum Tech. 6, 2200125 (2023)
Nanophotonics Design using Inverse Design
We present an inverse-design approach to significantly improve the figures of merit for chiral photonics with quantum emitters in topological photonic crystal slab waveguides
Eric Nussbaum, Nir Rotenberg, Stephen Hughes
Optimizing the chiral Purcell factor for unidirectional single photon emitters in topological photonic crystal waveguides using inverse design, Phys. Rev. A 106, 033514 (2022)
Photonics for artificial intelligence and neuromorphic computing
Neuromorphic photonics offers sub-nanosecond latencies, providing a complementary opportunity to extend the domain of artificial intelligence. Here, we review recent advances in integrated photonic neuromorphic systems, discuss current and future challenges, and outline the advances in science and technology needed to meet those challenges.
Bhavin J. Shastri, Alexander N. Tait, T. Ferreira de Lima et al.
Photonics for artificial intelligence and neuromorphic computing, Nature Photonics (2021)
Continuous-variable entanglement in a two-mode lossy cavity: An analytical solution
We show that the exact solution for the nonlinearly-generated state in a two-mode lossy cavity system is a two-mode squeezed thermal state
Colin Vendromin and Marc M. Dignam
Continuous-variable entanglement in a two-mode lossy cavity: An analytical solution, Phys. Rev. A 103, 022418 (2021)