Quantum Learning and Its Related Applications for the Future

Abstract

Recent advances in high-performance computing have been rapid. On the contrary, experts also know that the Moore's Law prediction of the number of transistors on microchips that would double every 18 months is almost saturated. This calls for new techniques to enhance computational power. Quantum computing is a possible solution that uses quantum mechanical phenomena and employs quantum algorithms to improve performance (accuracy, speed). The emerging technology has many interesting potential applications, including quantum machine learning, quantum computational chemistry, post quantum cryptography, etc. The complexity of applications is ever-increasing. Quantum computing amalgamates various classical machine and reinforcement learning in multiple ways to address different challenges of many complex applications. The state-of-the-art reviews on existing works in the domain show that new learning methods can enhance the achieved performance by quantum computing. The chapter thus provides an overview of quantum learning, its applications, research challenges, and future trends.