Image Classification with Rotation-Invariant Variational Quantum Circuits

arXiv:2403.15031v1 Announce Type: cross
Abstract: Variational quantum algorithms are gaining attention as an early application of Noisy Intermediate-Scale Quantum (NISQ) devices. One of the main problems of variational methods lies in the phenomenon of Barren Plateaus, present in the optimization of variational parameters. Adding geometric inductive bias to the quantum models has been proposed as a potential solution to mitigate this problem, leading to a new field called Geometric Quantum Machine Learning. In this work, an equivariant architecture for variational …

abstract algorithms application arxiv attention bias circuits classification cs.cv cs.lg devices image inductive intermediate lies nisq optimization parameters quant-ph quantum rotation scale type