Pith. sign in

Tensor models from the viewpoint of matrix models: the case of loop models on random surfaces

1 Pith paper cite this work, alongside 8 external citations. Polarity classification is still indexing.

1 Pith paper citing it
8 external citations · Pith
abstract

We study a connection between random tensors and random matrices through $U(\tau)$ matrix models which generate fully packed, oriented loops on random surfaces. The latter are found to be in bijection with a set of regular edge-colored graphs typically found in tensor models. It is shown that the expansion in the number of loops is organized like the 1/N expansion of rank-three tensor models. Recent results on tensor models are reviewed and applied in this context. For example, configurations which maximize the number of loops are precisely the melonic graphs of tensor models and a scaling limit which projects onto the melonic sector is found. We also reinterpret the double scaling limit of tensor models from the point of view of loops on random surfaces. This approach is eventually generalized to higher-rank tensor models, which generate loops with fugacity $\tau$ on triangulations in dimension $d-1$.

fields

math-ph 1

years

2026 1

verdicts

ACCEPT 1

representative citing papers

Tensor invariants for multipartite entanglement classification

math-ph · 2026-04-02 · accept · novelty 7.5

Trace-invariants of colored graphs fully label LU orbits of HT multipartite states, completely characterize their LO preorder via weight-function divisibility, and yield large-N combinatorial distinctions from Haar-random states.

citing papers explorer

Showing 1 of 1 citing paper.

  • Tensor invariants for multipartite entanglement classification math-ph · 2026-04-02 · accept · none · ref 78 · internal anchor

    Trace-invariants of colored graphs fully label LU orbits of HT multipartite states, completely characterize their LO preorder via weight-function divisibility, and yield large-N combinatorial distinctions from Haar-random states.