Trapped Ion Quantum Computers - Platform for QNN Neuroradiology

Explore the potential of trapped ion quantum computers in neuroradiology through this comprehensive 1-hour 13-minute video lecture. Delve into the advantages of trapped ion technology, including quantum bit coherence and all-to-all qubit connectivity, and their applications in medical radiology. Examine recent developments presented at the American Physical Society (APS) March 2023 meeting, featuring contributions from IonQ, Duke University, and Quantinuum. Analyze three influential papers on ion trap utilization in neuroradiology, covering fault-tolerant circuit design, quantum convolutional neural networks (QCNN) for image classification, and ischemic cardiopathy classification. Gain insights into AWS's hardware technology using perfect atomic qubits suspended in a vacuum. Access accompanying slides and references to deepen your understanding of this cutting-edge field at the intersection of quantum computing and medical imaging.