Quantum Reservoir Computing for Speckle Disorder Potentials

Condensed Matter

Pere Mujal¹ 

[1] IFISC, Institut de Física Interdisciplinària i Sistemes Complexos (UIB-CSIC), UIB Campus, E-07122 Palma de Mallorca, Spain;

关键词: quantum reservoir computing;    quantum machine learning;    information processing;    speckle disorder;   

DOI  :  10.3390/condmat7010017

来源: DOAJ

【 摘 要 】

Quantum reservoir computing is a machine learning approach designed to exploit the dynamics of quantum systems with memory to process information. As an advantage, it presents the possibility to benefit from the quantum resources provided by the reservoir combined with a simple and fast training strategy. In this work, this technique is introduced with a quantum reservoir of spins and it is applied to find the ground state energy of an additional quantum system. The quantum reservoir computer is trained with a linear model to predict the lowest energy of a particle in the presence of different speckle disorder potentials. The performance of the task is analyzed with a focus on the observable quantities extracted from the reservoir and it is shown to be enhanced when two-qubit correlations are employed.

【 授权许可】

Unknown