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 171 tok/s
Gemini 2.5 Pro 52 tok/s Pro
GPT-5 Medium 38 tok/s Pro
GPT-5 High 43 tok/s Pro
GPT-4o 108 tok/s Pro
Kimi K2 173 tok/s Pro
GPT OSS 120B 442 tok/s Pro
Claude Sonnet 4.5 34 tok/s Pro
2000 character limit reached

Real-Space Renormalization Group for Spectral Properties of Hierarchical Networks (1505.06395v2)

Published 24 May 2015 in cond-mat.stat-mech and cond-mat.dis-nn

Abstract: We derive the determinant of the Laplacian for the Hanoi networks and use it to determine their number of spanning trees (or graph complexity) asymptotically. While spanning trees generally proliferate with increasing average degree, the results show that modifications within the basic patterns of design of these hierarchical networks can lead to significant variations in their complexity. To this end, we develop renormalization group methods to obtain recursion equations from which many spectral properties can be obtained. This provides the basis for future applications to explore the physics of several dynamic processes.

Summary

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

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in 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.