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 80 tok/s
Gemini 2.5 Pro 60 tok/s Pro
GPT-5 Medium 23 tok/s Pro
GPT-5 High 26 tok/s Pro
GPT-4o 87 tok/s Pro
Kimi K2 173 tok/s Pro
GPT OSS 120B 433 tok/s Pro
Claude Sonnet 4 36 tok/s Pro
2000 character limit reached

Asymptotic geometry of discrete interlaced patterns: Part I (1412.6653v2)

Published 20 Dec 2014 in math.PR

Abstract: A discrete Gelfand-Tsetlin pattern is a configuration of particles in Z2. The particles are arranged in a finite number of consecutive rows, numbered from the bottom. There is one particle on the first row, two particles on the second row, three particles on the third row, etc, and particles on adjacent rows satisfy an interlacing constraint. We consider the uniform probability measure on the set of all discrete Gelfand-Tsetlin patterns of a fixed size where the particles on the top row are in deterministic positions. This measure arises naturally as an equivalent description of the uniform probability measure on the set of all tilings of certain polygons with lozenges. We prove a determinantal structure, and calculate the correlation kernel. We consider the asymptotic behaviour of the system as the size increases under the assumption that the empirical distribution of the deterministic particles on the top row converges weakly. We consider the asymptotic `shape' of such systems. We provide parameterisations of the asymptotic boundaries and investigate the local geometric properties of the resulting curves. We show that the boundary can be partitioned into natural sections which are determined by the behaviour of the roots of a function related to the correlation kernel. This paper should be regarded as a companion piece to the upcoming paper, [4], in which we resolve some of the remaining issues. Both of these papers serve as background material for the upcoming papers, [5] and [6], in which we examine the edge asymptotic behaviour.

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.

Don't miss out on important new AI/ML research

See which papers are being discussed right now on X, Reddit, and more:

“Emergent Mind helps me see which AI papers have caught fire online.”

Philip

Philip

Creator, AI Explained on YouTube