PhD Dissertation Proposal by RUAN Shaolun | Visual Analytics for Interpretable Quantum Computing

ABOUT THE TALK

Quantum computing has made significant progress in recent years. The rapid growth in the quality and quantity of quantum computers by leading IT companies such as IBM, Google and Amazon makes the potential quantum advantages increasingly realistic. However, previous research has determined that grasping abstract concepts in quantum computing remains challenging. For example, it is troublesome for developers and researchers to understand the function of each quantum gate and the final measured probability of each basis state. In this Thesis Proposal presentation, Shaolun Ruan will introduce how to reveal the workflow of quantum computing by visualizing the inner workings from three perspectives, i.e., noise mitigation hidden in the IBM Quantum platform, visual interpretability of quantum states, and black-box opening of quantum circuits.

ABOUT THE SPEAKER

Shaolun RUAN is currently a Year-3 Ph.D. candidate in the School of Computing and Information Systems at Singapore Management University (SMU), under the supervision of Prof. Yong WANG. His work focuses on developing novel human-centered computing tools to enable users to handle complex and abstract scientific problems like quantum computing and bioinformatics, leveraging the methods from Data Visualization and Augmented Reality. He received his bachelor's degree from the University of Electronic Science and Technology of China (UESTC) in 2019. For more information, kindly visit https://shaolun-ruan.com/.