Pre-Conference Talk by RUAN Shaolun | QuantumEyes: Towards Better Interpretability of Quantum Circuits

Quantum computing offers significant speedup compared to classical computing, which has led to a growing interest among users in learning and applying quantum computing across various applications. However, quantum circuits, which are fundamental for implementing quantum algorithms, can be challenging for users to understand due to their underlying logic. To fill this research gap, we propose QuantumEyes, an interactive visual analytics system to enhance the interpretability of quantum circuits through both global and local levels. For the global-level analysis, we present three coupled visualizations to delineate the changes of quantum states and the underlying reasons. For the local level analysis, we design a novel geometrical visualization dandelion chart to explicitly reveal how the quantum amplitudes affect the probability of the quantum state. We thoroughly evaluated QuantumEyes and the novel dandelion chart integrated into it through two case studies on different types of quantum algorithms. 

This is a Pre-Conference talk for IEEE VIS: Visualization & Visual Analytics (IEEE VIS 2024).

Shaolun Ruan is currently a Ph.D. candidate in School of Computing and Information Systems at Singapore Management University (SMU). His research interests include Data Visualization and Human-Computer Interaction. His work focuses on developing human-centered computing tools to address complex scientific problems, facilitating the process of explainability and data-driven decision-making. 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/.