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pro vyhledávání: '"Čindrak, Saud"'
Quantum machine learning utilizes the high-dimensional space of quantum systems, attracting significant research interest. This study employs Krylov complexity to analyze task performance in quantum machine learning. We calculate the spread complexit
Externí odkaz:
http://arxiv.org/abs/2409.12079
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 Hamiltonian to construct a basis for the Krylov state space and the computation
Externí odkaz:
http://arxiv.org/abs/2404.13089
Publikováno v:
Phys. Rev. Research 6, 013051 (2024)
Quantum reservoir computing is a computing approach which aims at utilising the complexity and high-dimensionality of small quantum systems, together with the fast trainability of reservoir computing, in order to solve complex tasks. The suitability
Externí odkaz:
http://arxiv.org/abs/2306.12876