Quantum Minimal Learning Machine: A Fidelity-Based Approach to Error Mitigation

Abstract

We introduce the concept of quantum minimal learning machine (QMLM), a supervised similarity-based learning algorithm. The algorithm is conceptually based on a classical machine learning model and adopted to work with quantum data. We will motivate the theory and run the model as an error mitigation method for various parameters.