BOOSTING QUANTUM COMPUTING PERFORMANCE: A CACHE-BASED SOLUTION FOR ENHANCED SCALABILITY

Abstract

Abstract-This research introduces a new method for image recognition using quantum mechanics called a Variational Quantum Deep Neural Network (VQDNN). Unlike traditional quantum circuits, VQDNN can handle image data and achieve high accuracy (even 100% for some datasets) despite limitations in current hardware.Separately, researchers are exploring Quantum Generative Learning Models (QGLMs) which are quantum versions of existing machine learning models. These models have potential applications in traditional machine learning tasks and even problems in quantum physics itself.Finally, the concept of Quantum Artificial Neural Networks (QANNs) is introduced. These networks are shown to be useful for solving complex quantum problems by mimicking how a quantum system behaves under changing conditions.