Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 61 tok/s
Gemini 2.5 Pro 51 tok/s Pro
GPT-5 Medium 37 tok/s Pro
GPT-5 High 33 tok/s Pro
GPT-4o 95 tok/s Pro
Kimi K2 171 tok/s Pro
GPT OSS 120B 440 tok/s Pro
Claude Sonnet 4.5 37 tok/s Pro
2000 character limit reached

Tensor models from the viewpoint of matrix models: the case of loop models on random surfaces (1304.4152v2)

Published 15 Apr 2013 in hep-th, cond-mat.stat-mech, math-ph, and math.MP

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 $d-1$.

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.