Publication Type
Journal Article
Version
acceptedVersion
Publication Date
6-2023
Abstract
Visualizations have played a crucial role in helping quantum computing users explore quantum states in various quantum computing applications. Among them, Bloch Sphere is the widely-used visualization for showing quantum states, which leverages angles to represent quantum amplitudes. However, it cannot support the visualization of quantum entanglement and superposition, the two essential properties of quantum computing. To address this issue, we propose VENUS, a novel visualization for quantum state representation. By explicitly correlating 2D geometric shapes based on the math foundation of quantum computing characteristics, VENUS effectively represents quantum amplitudes of both the single qubit and two qubits for quantum entanglement. Also, we use multiple coordinated semicircles to naturally encode probability distribution, making the quantum superposition intuitive to analyze. We conducted two well-designed case studies and an in-depth expert interview to evaluate the usefulness and effectiveness of VENUS. The result shows that VENUS can effectively facilitate the exploration of quantum states for the single qubit and two qubits.
Keywords
Quantum computing, data visualization, quantum state
Discipline
Artificial Intelligence and Robotics | Graphics and Human Computer Interfaces
Research Areas
Intelligent Systems and Optimization
Publication
Computer Graphics Forum
Volume
42
Issue
3
First Page
1
Last Page
12
ISSN
0167-7055
Identifier
10.1111/cgf.14827
Publisher
Wiley
Citation
RUAN, Shaolun; YUAN, Ribo; GUAN, Qiang; LIN, Yanna; MAO, Ying; JIANG, Weiwen; WANG, Zhepeng; XU, Wei; and Yong WANG.
VENUS: A geometrical representation for quantum state visualization. (2023). Computer Graphics Forum. 42, (3), 1-12.
Available at: https://ink.library.smu.edu.sg/sis_research/8597
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1111/cgf.14827
Included in
Artificial Intelligence and Robotics Commons, Graphics and Human Computer Interfaces Commons