Quantum machine learning enabled by quantum teleportation
PhD researcher @ IFISC
Annual talk PhD, presential in seminar room
Cluster states are a quantum resource that can be exploited for measurement-based quantum computing via quantum teleportation protocols, a field that has been gaining traction lately. In parallel, quantum machine learning is an emerging area of research that seeks to leverage the expanded Hilbert space of quantum systems for tasks such as classification and prediction. In this talk, I will explain how cluster states can also serve as a valuable resource for quantum machine learning. Specifically, I will focus on a quantum reservoir computing protocol that utilizes quantum teleportation for encoding and executing time series processing tasks.
Detalls de contacte:
Miguel C. Soriano Contact form