Intuit: Explain Quantum Computing Concepts via AR-based Analogy
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arXiv
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| Autori principali: | , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866913714471436288 |
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| author | Karunathilaka, Manusha Ruan, Shaolun Yuan, Lin-Ping Li, Jiannan Liang, Zhiding Athapaththu, Kavinda Guan, Qiang Wang, Yong |
| author_facet | Karunathilaka, Manusha Ruan, Shaolun Yuan, Lin-Ping Li, Jiannan Liang, Zhiding Athapaththu, Kavinda Guan, Qiang Wang, Yong |
| contents | Quantum computing has shown great potential to revolutionize traditional computing and can provide an exponential speedup for a wide range of possible applications, attracting various stakeholders. However, understanding fundamental quantum computing concepts remains a significant challenge for novices because of their abstract and counterintuitive nature. Thus, we propose an analogy-based characterization framework to construct the mental mapping between quantum computing concepts and daily objects, informed by in-depth expert interviews and a literature review, covering key quantum concepts and characteristics like number of qubits, output state duality, quantum concept type, and probability quantification. Then, we developed an AR-based prototype system, Intuit, using situated analytics to explain quantum concepts through daily objects and phenomena (e.g., rotating coins, paper cutters). We thoroughly evaluated our approach through in-depth user and expert interviews. The Results demonstrate the effectiveness and usability of Intuit in helping learners understand abstract concepts in an intuitive and engaging manner. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_00835 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Intuit: Explain Quantum Computing Concepts via AR-based Analogy Karunathilaka, Manusha Ruan, Shaolun Yuan, Lin-Ping Li, Jiannan Liang, Zhiding Athapaththu, Kavinda Guan, Qiang Wang, Yong Human-Computer Interaction Quantum computing has shown great potential to revolutionize traditional computing and can provide an exponential speedup for a wide range of possible applications, attracting various stakeholders. However, understanding fundamental quantum computing concepts remains a significant challenge for novices because of their abstract and counterintuitive nature. Thus, we propose an analogy-based characterization framework to construct the mental mapping between quantum computing concepts and daily objects, informed by in-depth expert interviews and a literature review, covering key quantum concepts and characteristics like number of qubits, output state duality, quantum concept type, and probability quantification. Then, we developed an AR-based prototype system, Intuit, using situated analytics to explain quantum concepts through daily objects and phenomena (e.g., rotating coins, paper cutters). We thoroughly evaluated our approach through in-depth user and expert interviews. The Results demonstrate the effectiveness and usability of Intuit in helping learners understand abstract concepts in an intuitive and engaging manner. |
| title | Intuit: Explain Quantum Computing Concepts via AR-based Analogy |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2503.00835 |