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Bibliographic Details
Main Authors: Clelland, Jeanne, Tapp, Kristopher
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2603.18347
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author Clelland, Jeanne
Tapp, Kristopher
author_facet Clelland, Jeanne
Tapp, Kristopher
contents We develop effective methods for constructing an ensemble of district plans via independent sampling from a reasonable probability distribution on the space of graph partitions. We compare the performance of our algorithms to that of standard Markov Chain based algorithms in the context of grid graphs and state congressional and legislative maps. For the case of perfect population balance between districts, we provide an explicit description of the distribution from which our method samples.
format Preprint
id arxiv_https___arxiv_org_abs_2603_18347
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Bonsai: A class of effective methods for independent sampling of graph partitions
Clelland, Jeanne
Tapp, Kristopher
Data Structures and Algorithms
Computers and Society
Social and Information Networks
We develop effective methods for constructing an ensemble of district plans via independent sampling from a reasonable probability distribution on the space of graph partitions. We compare the performance of our algorithms to that of standard Markov Chain based algorithms in the context of grid graphs and state congressional and legislative maps. For the case of perfect population balance between districts, we provide an explicit description of the distribution from which our method samples.
title Bonsai: A class of effective methods for independent sampling of graph partitions
topic Data Structures and Algorithms
Computers and Society
Social and Information Networks
url https://arxiv.org/abs/2603.18347