Demonstration of a Measurement-Based Adaptation Protocol with Quantum Reinforcement Learning on the IBM Q Experience Platform
Introduction Quantum computing has opened up vast opportunities for solving problems that classical computers struggle with, from complex simulations to uncrackable encryption schemes. One of the essential tasks in quantum computation is cloning an unknown quantum state . However, due to the well-known no-cloning theorem , it is impossible to create an identical copy of an arbitrary unknown quantum state. This poses a challenge in the field, especially when working with limited copies of these states. In the recent article, " Demonstration of a measurement-based adaptation protocol with quantum reinforcement learning on the IBM Q experience platform " published in Quantum Information Processing , researchers have proposed an innovative approach to address this challenge. This blog delves into the key insights of their study and how quantum reinforcement learning is pushing the boundaries of quantum state cloning. Quantum State Cloning and the No-Cloning Theorem The no-clon...