2D Quon Language: Unifying Framework for Cliffords, Matchgates, and Beyond

• URL: http://arxiv.org/abs/2505.06336v1
• Date: Fri, 09 May 2025 18:00:00 GMT
• Title: 2D Quon Language: Unifying Framework for Cliffords, Matchgates, and Beyond
• Authors: Byungmin Kang, Chen Zhao, Zhengwei Liu, Xun Gao, Soonwon Choi,
• Abstract summary: We make progress toward the unified understanding of the Clifford and matchgate.<n>We introduce the 2D Quon language, which combines Majorana worldlines with their underlying spacetime topology.<n>We discuss a range of applications of our approach, from recovering well-known results such as the Kramers-Wannier duality.
• Score: 4.886638121226719
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Simulating generic quantum states and dynamics is practically intractable using classical computers. However, certain special classes -- namely Clifford and matchgate circuits -- permit efficient computation. They provide invaluable tools for studying many-body physics, quantum chemistry, and quantum computation. While both play foundational roles across multiple disciplines, the origins of their tractability seem disparate, and their relationship remain unclear. A deeper understanding of such tractable classes could expand their scope and enable a wide range of new applications. In this work, we make progress toward the unified understanding of the Clifford and matchgate -- these two classes are, in fact, distinct special cases of a single underlying structure. Specifically, we introduce the 2D Quon language, which combines Majorana worldlines with their underlying spacetime topology to diagrammatically represent quantum processes and tensor networks. In full generality, the 2D Quon language is universal -- capable of representing arbitrary quantum states, dynamics, or tensor networks -- yet they become especially powerful in describing Clifford and matchgate classes. Each class can be efficiently characterized in a visually recognizable manner using the Quon framework. This capability naturally gives rise to several families of efficiently computable tensor networks introduced in this work: punctured matchgates, hybrid Clifford-matchgate-MPS, and ansatze generated from factories of tractable networks. All of these exhibit high non-Cliffordness, high non-matchgateness, and large bipartite entanglement entropy. We discuss a range of applications of our approach, from recovering well-known results such as the Kramers-Wannier duality and the star-triangle relation of the Ising model, to enabling variational optimization with novel ansatz states.

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