11 papers
Efficient time-series prediction on NISQ devices via time-delayed quantum extreme learning machine
Mio Kawanabe, Saud Cindrak, Kathy Ludge +3
We proposed a time-delayed quantum extreme learning machine (TD-QELM) for efficient time-series prediction on noisy intermediate-scale quantum (NISQ) devices. By encoding multiple…
Reservoir Computing with a single Josephson junction
George Baxevanis, Kathy Lüdge, Johanne Hizanidis
Physical reservoir computing exploits the nonlinear dynamics of a physical system to perform information processing tasks. Josephson junctions (JJs), as nonlinear superconducting d…
Distributed Coherent Optical Computing via Injection-Locked Photonic Networks
Shenghan Gao, Kathy Lüdge, Francesco Da Ros +1
Coherent photonic computing uses both the phase and amplitude of light to implement linear operations such as dot products and matrix multiplication but requires phase stability be…
Memory-Nonlinearity Trade-off across Quantum Reservoir Computing Frameworks
Saud Äindrak, Lara Giebeler, Niclas Götting +2
Quantum reservoir computing (QRC) harnesses driven quantum dynamics for time-series processing, yet the mechanisms behind the differing performance levels across its many implement…
On Minimizing Krylov Complexity Using Higher-Order Generators
Saud Äindrak, Kathy Lüdge
Krylov complexity provides a powerful framework for characterizing the dynamical evolution of quantum systems through the spreading of states in Krylov space. The motivation for th…
From Krylov Complexity to Observability: Capturing Phase Space Dimension with Applications in Quantum Reservoir Computing
Saud Äindrak, Kathy Lüdge, Lina Jaurigue
We demonstrate that time-evolved operators can construct a Krylov space to compute Operator complexity and introduce Krylov observability as a measure of effective phase space dime…