Quantum kernels through the lens of entangled tensor kernels
Abstract
Quantum kernel methods are one of the most explored approaches to quantum machine learning. However, the structural properties and inductive bias of quantum kernels are not fully understood. In this work, we introduce the notion of entangled tensor kernels—a generalization of product kernels from classical kernel theory—and show that all embedding quantum kernels can be understood as an entangled tensor kernel. We discuss how this perspective allows one to gain insights into both the unique inductive bias of quantum kernels and potential methods for their dequantization.
Fields of Study & Subjects
Computational Physics and Python Applications
Cosmology and Gravitation Theories
Quantum many-body systems
Publication details
- Journal / source
- Physical Review Research
- Volume
- 8
- Issue
- 2
- Publication date
- 25 April 2026
- Language
- EN