Quantivine: A Visualization Approach for Large-scale Quantum Circuit Representation and Analysis

Zhen Wen, Yihan Liu, Siwei Tan, Jieyi Chen, Minfeng Zhu, Dongming Han, Jianwei Yin, Mingliang Xu, Wei Chen

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2023-10-25T04:57:00ZGMT-0600Change your timezone on the schedule page
Exemplar figure, described by caption below
The system interface of Quantivine. The Structure View presents the construction of a quantum circuit in a tree diagram including primitive gates, component gates, and repetitive patterns. The Component View provides a flexibly-organized circuit diagram with grouped component gates. The Abstraction View shows a further simplified circuit diagram according to visual abstractions of repetitive patterns. Three Context Views reveal contextual information in the circuit, including qubit provenance, gate placement, and connectivity.
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Quantum circuit, semantic analysis, visual abstraction, context visualization


Quantum computing is a rapidly evolving field that enables exponential speed-up over classical algorithms. At the heart of this revolutionary technology are quantum circuits, which serve as vital tools for implementing, analyzing, and optimizing quantum algorithms. Recent advancements in quantum computing and the increasing capability of quantum devices have led to the development of more complex quantum circuits. However, traditional quantum circuit diagrams suffer from scalability and readability issues, which limit the efficiency of analysis and optimization processes. In this research, we propose a novel visualization approach for large-scale quantum circuits by adopting semantic analysis to facilitate the comprehension of quantum circuits. We first exploit meta-data and semantic information extracted from the underlying code of quantum circuits to create component segmentations and pattern abstractions, allowing for easier wrangling of massive circuit diagrams. We then develop Quantivine, an interactive system for exploring and understanding quantum circuits. A series of novel circuit visualizations is designed to uncover contextual details such as qubit provenance, parallelism, and entanglement. The effectiveness of Quantivine is demonstrated through two usage scenarios of quantum circuits with up to 100 qubits and a formal user evaluation with quantum experts. A free copy of this paper and all supplemental materials are available at https://osf.io/2m9yh/?view_only=0aa1618c97244f5093cd7ce15f1431f9.