Quantitative determination of minimum spanning tree structures: Using the pulsar tree for analyzing the appearance of new classes of pulsars

TL;DR

This paper presents a quantitative method using betweenness centrality and non-parametric tests to analyze the structure of pulsar data through minimum spanning trees, aiding in identifying new pulsar classes over time.

Contribution

Introduces a novel quantitative approach to define main and significant branches in MSTs, applied to pulsar data for class evolution analysis.

Findings

Method effectively distinguishes pulsar classes

Identifies potential new pulsar classes in data

Tracks pulsar population evolution over time

Abstract

In this work, we introduce a quantitative methodology to define what is the main trunk and what are the significant branches of a minimum spanning tree (MST). We apply it to the pulsar tree, i.e. the MST of the pulsar population constructed upon a Euclidean distance over the pulsar's intrinsic properties. Our method makes use of the betweenness centrality estimator, as well as of non-parametric tests to establish the distinct character of the defined branches. Armed with these concepts, we study how the pulsar population has evolved throughout history, and analyze how to judge whether a new class of pulsars appears in new data, future surveys, or new incarnations of pulsar catalogs.