62 citations · 119 across the 21 of their papers we have counts for
11 papers · 1 filter
High-Speed Time Series Prediction with a GHz-rate Photonic Spiking Neural Network built with a single VCSEL
Dafydd Owen-Newns, Lina Jaurigue, Josh Robertson +4
Photonic technologies hold significant potential for creating innovative, high-speed, efficient and hardware-friendly neuromorphic computing platforms. Neuromorphic photonic method…
Time-multiplexed Reservoir Computing with Quantum-Dot Lasers: Does more complexity lead to better performance?
Huifang Dong, Lina Jaurigue, Kathy Lüdge
Reservoir computing with optical devices offers an energy-efficient approach for time-series forecasting. Quantum dot lasers with feedback are modelled in this paper to explore the…
Engineering Quantum Reservoirs through Krylov Complexity, Expressivity and Observability
Saud Čindrak, Lina Jaurigue, Kathy Lüdge
This study employs Krylov-based information measures to understand task performance in quantum reservoir computing, a sub-field of quantum machine learning. In our study we show th…
Canard cascading in networks with adaptive mean-field coupling
Juan Balzer, Rico Berner, Kathy Lüdge +3
Canard cascading (CC) is observed in dynamical networks with global adaptive coupling. It is a fast-slow phenomenon characterized by a recurrent sequence of fast transitions betwee…
Measurable Krylov Spaces and Eigenenergy Count in Quantum State Dynamics
Saud Čindrak, Adrian Paschke, Lina Jaurigue +1
In this work, we propose a quantum-mechanically measurable basis for the computation of spread complexity. Current literature focuses on computing different powers of the Hamiltoni…
Data-Driven Acceleration of Multi-Physics Simulations
Stefan Meinecke, Malte Selig, Felix Köster +2
Multi-physics simulations play a crucial role in understanding complex systems. However, their computational demands are often prohibitive due to high dimensionality and complex in…