5 papers
A tensor network approach for chaotic time series prediction
Rodrigo MartÃnez-Peña, Román Orús
Making accurate predictions of chaotic time series is a complex challenge. Reservoir computing, a neuromorphic-inspired approach, has emerged as a powerful tool for this task. It e…
Feedback-driven recurrent quantum neural network universality
Lukas Gonon, Rodrigo MartÃnez-Peña, Juan-Pablo Ortega
Quantum reservoir computing uses the dynamics of quantum systems to process temporal data, making it particularly well-suited for machine learning with noisy intermediate-scale qua…
Input-dependence in quantum reservoir computing
Rodrigo MartÃnez-Peña, Juan-Pablo Ortega
Quantum reservoir computing is an emergent field in which quantum dynamical systems are exploited for temporal information processing. In previous work, it was found a feature that…
Role of coherence in many-body Quantum Reservoir Computing
Ana Palacios, Rodrigo MartÃnez-Peña, Miguel C. Soriano +2
Quantum Reservoir Computing (QRC) offers potential advantages over classical reservoir computing, including inherent processing of quantum inputs and a vast Hilbert space for state…
Quantum fidelity kernel with a trapped-ion simulation platform
Rodrigo MartÃnez-Peña, Miguel C. Soriano, Roberta Zambrini
Quantum kernel methods leverage a kernel function computed by embedding input information into the Hilbert space of a quantum system. However, large Hilbert spaces can hinder gener…