English

From Laplacian-to-Adjacency Matrix for Continuous Spins on Graphs

Statistical Mechanics 2026-05-19 v2 Quantum Physics

Abstract

The study of spins and particles on graphs has broad applications, from the dynamics of interacting systems on networks to combinatorial problems. Here, we study the large-nn limit of the O(n)O(n) model on graphs, which is considerably more challenging than on regular lattices, as the loss of translational invariance gives rise to an infinite set of saddle point constraints in the thermodynamic limit. We show that the free energy at low and high temperature TT is determined by the spectrum of two fundamental graph-theoretic objects: the Laplacian matrix at low TT and the Adjacency matrix at high TT. Their interplay is studied across several classes of graphs. For regular lattices the two coincide. We obtain an exact solution on trees, where the Lagrange multipliers interestingly depend solely on the number of nearest neighbors. We further contrast these classical results with those for a quantum spin model on an exemplary tree. For decorated lattices, the singular part of the free energy is governed by the Laplacian spectrum, whereas this is true for the full free energy only in the zero temperature limit. Finally, we discuss a bipartite fully connected graph to highlight the importance of a finite coordination number in these results.

Keywords

Cite

@article{arxiv.2511.12330,
  title  = {From Laplacian-to-Adjacency Matrix for Continuous Spins on Graphs},
  author = {Nikita Titov and Andrea Trombettoni},
  journal= {arXiv preprint arXiv:2511.12330},
  year   = {2026}
}

Comments

18 pages, 3 figures, minor typographical errors corrected

R2 v1 2026-07-01T07:39:17.084Z