A Hybrid Quantum-Classical Approach based on the Hadamard Transform for the Convolutional Layer

arXiv:2305.17510v3 Announce Type: replace
Abstract: In this paper, we propose a novel Hadamard Transform (HT)-based neural network layer for hybrid quantum-classical computing. It implements the regular convolutional layers in the Hadamard transform domain. The idea is based on the HT convolution theorem which states that the dyadic convolution between two vectors is equivalent to the element-wise multiplication of their HT representation. Computing the HT is simply the application of a Hadamard gate to each qubit individually, so the HT computations …

abstract arxiv computing convolution cs.cv domain eess.sp hybrid layer network neural network novel paper quantum theorem type