The complexity of approximating the complex-valued Potts model

• Published in: Computational complexity Vol. 31; no. 1
• Main Authors: Galanis, Andreas, Goldberg, Leslie Ann, Herrera-Poyatos, Andrés
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 01.06.2022; Springer Nature B.V
• Subjects: Algorithm Analysis and Problem Complexity; Approximation; Complexity; Computational Mathematics and Numerical Analysis; Computer Science; Ising model; Mathematical models; Parameters; Partitions (mathematics); Phase transitions; Polynomials; Quantum computing; Counting Complexity; Ising model; Tutte polynomial; 68Q17 Computational difficulty of problems; Potts model; Approximate Counting
• ISSN: 1016-3328; 1420-8954; 1420-8954
• DOI: 10.1007/s00037-021-00218-x

We study the complexity of approximating the partition function of the q-state Potts model and the closely related Tutte polynomial for complex values of the underlying parameters. Apart from the classical connections with quantum computing and phase transitions in statistical physics, recent work in approximate counting has shown that the behaviour in the complex plane, and more precisely the location of zeros, is strongly connected with the complexity of the approximation problem, even for positive real-valued parameters. Previous work in the complex plane by Goldberg and Guo focused on q = 2, which corresponds to the case of the Ising model; for q > 2, the behaviour in the complex plane is not as well understood and most work applies only to the real-valued Tutte plane. Our main result is a complete classification of the complexity of the approximation problems for all non-real values of the parameters, by establishing #P-hardness results that apply even when restricted to planar graphs. Our techniques apply to all q ≥ 2 and further complement/refine previous results both for the Ising model and the Tutte plane, answering in particular a question raised by Bordewich, Freedman, Lovász and Welsh in the context of quantum computations.