An analysis of the State Preparation Techniques for Quantum Machine Learning - Subodh Nath Pushpak (International Journal of Intelligent Systems and Applications in Engineering, 2024)
The study discusses various methods for preparing quantum-states from classical data, which is crucial for quantum machine learning (QML). It analyzes the complexity of these state preparation techniques, highlighting their efficiency and potential challenges. Effective state preparation plays a key role in connecting classical data with quantum systems, allowing quantum algorithms to be utilized in solving machine learning challenges. This paper reviews the related work of state preparation, introduces a variety of state preparation schemes currently proposed, describes the implementation process of these schemes, and summarizes and analyzes the complexity of these schemes. The paper covers different encoding methods, such as basis coding, amplitude coding, and quantum sampling coding. Finally, prospects for conducting research in the area of state preparation have been identified. Furthermore, the document examines potential future research avenues in field of quantum-state preparation and its impact on QML algorithms.