SURVEY OF ENCODING TECHNIQUES FOR QUANTUM MACHINE LEARNING

Abstract

Quantum computing is a field of computation that processes information in a fundamentally different way compared to classical computers. Quantum computing is a rapidly expanding research field with ongoing investigations regarding applications of quantum computing in widespread domains such as cryptography, artificial intelligence, communications, etc. The core focus of this paper is quantum encoding which is a crucial branch of quantum computing. Quantum encoding involves mapping classical data into quantum states. This paper provides an in-depth analysis of prominent quantum encoding techniques with their strengths and weaknesses. Furthermore, this paper suggests development of hybrid encoding methods capable of emulating the concept of Euclidean distance by integrating amplitude and angle encoding.