CHARACTERIZATION OF ASYMMETRIC FRAGMENTATION PATTERNS IN SPATIALLY EXTENDED SYSTEMS

Author:

ROSA R. R.1,SHARMA A. S.2,VALDIVIA J. A.2

Affiliation:

1. Lab for Computing and Applied Mathematics (LAC), National Institute for Space Research-INPE, Brazil Cx. Postal 515, 12201-970, S. J. dos Campos, SP, Brazil

2. Astronomy and Physics Departments, University of Maryland, College Park-MD, 20742-2421, USA

Abstract

Spatially extended systems yield complex patterns arising from the coupled dynamics of its different regions. In this paper we introduce a matrix computational operator, [Formula: see text], for the characterization of asymmetric amplitude fragmentation in extended systems. For a given matrix of amplitudes this operation results in an asymmetric-triangulation field composed by L points and I straight lines. The parameter (I-L)/L is a new quantitative measure of the local complexity defined in terms of the asymmetry in the gradient field of the amplitudes. This asymmetric fragmentation parameter is a measure of the degree of structural complexity and characterizes the localized regions of a spatially extended system and symmetry breaking along the evolution of the system. For the case of a random field, in the real domain, which has total asymmetry, this asymmetric fragmentation parameter is expected to have the highest value and this is used to normalize the values for the other cases. Here, we present a detailed description of the operator [Formula: see text] and some of the fundamental conjectures that arises from its application in spatio-temporal asymmetric patterns.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computational Theory and Mathematics,Computer Science Applications,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

Cited by 31 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Unveiling galaxy morphology through an unsupervised-supervised hybrid approach;Monthly Notices of the Royal Astronomical Society;2023-12-21

2. Classification and evolution of galaxies according to the dynamical state of host clusters and galaxy luminosities;Monthly Notices of the Royal Astronomical Society;2020-04-28

3. Machine and Deep Learning applied to galaxy morphology - A comparative study;Astronomy and Computing;2020-01

4. Gradient pattern analysis applied to galaxy morphology;Monthly Notices of the Royal Astronomical Society: Letters;2018-04-04

5. Data-Driven Modeling of Extreme Space Weather;Extreme Events in Geospace;2018

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3