Quantum Computing and Visualization: A Disruptive Technological Change Ahead

Journal Article · 01 November 2023 · IEEE Computer Graphics and Applications

DOI: https://doi.org/10.1109/mcg.2023.3316932 · OSTI ID:2319219

Bethel, E. Wes  ^[1]; Amankwah, Mercy Gyamea  ^[2]; Balewski, Jan  ^[3]; Van Beeumen, Roel  ^[3]; Camps, Daan  ^[3]; Huang, Daniel  ^[1]; Perciano, Talita  ^[3]

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1. San Francisco State Univ., CA (United States)
2. Case Western Reserve Univ., Cleveland, OH (United States)
3. Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

The focus of this Visualization Viewpoints article is to provide some background on quantum computing (QC), to explore ideas related to how visualization helps in understanding QC, and examine how QC might be useful for visualization with the growth and maturation of both technologies in the future. In a quickly evolving technology landscape, QC is emerging as a promising pathway to overcome the growth limits in classical computing. In some cases, QC platforms offer the potential to vastly outperform the familiar classical computer by solving problems more quickly or that may be intractable on any known classical platform. As further performance gains for classical computing platforms are limited by diminishing Moore’s Law scaling, QC platforms might be viewed as a potential successor to the current field of exascale-class platforms. Importantly, while present-day QC hardware platforms are still limited in scale, the field of quantum computing is robust and rapidly advancing in terms of hardware capabilities, software environments for developing quantum algorithms, and educational programs for training the next generation of scientists and engineers. After a brief introduction to QC concepts, the focus of this article is to explore the interplay between the fields of visualization and QC. First, visualization has played a role in QC by providing the means to show representations of the quantum state of single-qubits in superposition states and multiple-qubits in entangled states. Second, there are a number of ways in which the field of visual data exploration and analysis may potentially benefit from this disruptive new technology though there are challenges going forward.

• Research Organization: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
• Sponsoring Organization: USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)
• Grant/Contract Number: AC02-05CH11231
• OSTI ID: 2319219
• Journal Information: IEEE Computer Graphics and Applications, Vol. 43, Issue 6; ISSN 0272-1716
• Publisher: IEEECopyright Statement
• Country of Publication: United States
• Language: English