Quantum Machine Learning ISC 2023

Gate-based quantum computers and their capabilities are an area that growing interest and resources are being allocated to all over the world. In particular, the possibility of exponential improvements in classical machine learning algorithms when executed by an equivalent algorithm on a quantum computer. In this ISC session, we present an introductory tutorial to quantum computing aimed at computer and data scientists and HPC users of any science domain. Our focus is to show how quantum computers are programmed today while providing the essential math and physics background required to develop quantum algorithms. After introducing some basic examples, the tutorial covers hybrid quantum classical approaches to Quantum Machine Learning. As an introduction, we illustrate some quantum classifiers, such as the Variational Quantum Classifier. The tutorials will use the Qiskit framework, including the newly introduced Qiskit primitives, to show how increasingly complex quantum algorithms can be constructed from available building blocks.