[Submitted on 8 Jul 2026]

Hybrid Quantum-Classical Architecture Using Path Signature Kernels for Time Series Classification

This paper proposes a hybrid quantum-classical architecture for time series classification that integrates Quantum Convolutional Neural Networks (QCNN) with rough path signature kernels. The architecture addresses the challenge of time reparameterization invariance in time series data by using feature layers that compute signature kernels between input paths