Efficient Identification of Permutation Symmetries in Many-Body Hamiltonians via Graph Theory

• URL: http://arxiv.org/abs/2511.23160v1
• Date: Fri, 28 Nov 2025 13:16:20 GMT
• Title: Efficient Identification of Permutation Symmetries in Many-Body Hamiltonians via Graph Theory
• Authors: Saumya Shah, Patrick Rebentrost,
• Abstract summary: This paper introduces a new method that identifies this symmetry group by establishing an isomorphism between the Hamiltonian's permutation group and the automorphism group of a coloured bipartite graph constructed from the Hamiltonian.<n>We show that for physical Hamiltonians with bounded locality and interaction degree, the resulting graph has a bounded degree, reducing the computational problem of finding the automorphism group to time.<n>This work provides a general, structurally exact tool for algorithmic symmetry finding, enabling the scalable application of these symmetries to Hamiltonian simulation problems.
• Score: 2.5782420501870296
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The computational cost of simulating quantum many-body systems can often be reduced by taking advantage of physical symmetries. While methods exist for specific symmetry classes, a general algorithm to find the full permutation symmetry group of an arbitrary Pauli Hamiltonian is notably lacking. This paper introduces a new method that identifies this symmetry group by establishing an isomorphism between the Hamiltonian's permutation symmetry group and the automorphism group of a coloured bipartite graph constructed from the Hamiltonian. We formally prove this isomorphism and show that for physical Hamiltonians with bounded locality and interaction degree, the resulting graph has a bounded degree, reducing the computational problem of finding the automorphism group to polynomial time. The algorithm's validity is empirically confirmed on various physical models with known symmetries. We further show that the problem of deciding whether two Hamiltonians are permutation-equivalent is polynomial-time reducible to the graph isomorphism problem using our graph representation. This work provides a general, structurally exact tool for algorithmic symmetry finding, enabling the scalable application of these symmetries to Hamiltonian simulation problems.

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