Identification of Superclusters and Their Properties in the Sloan Digital Sky Survey Using the WHL Cluster Catalog

Author:

Sankhyayan ShishirORCID,Bagchi JoydeepORCID,Tempel ElmoORCID,More SurhudORCID,Einasto MaretORCID,Dabhade PratikORCID,Raychaudhury SomakORCID,Athreya RamanaORCID,Heinämäki PekkaORCID

Abstract

Abstract Superclusters are the largest massive structures in the cosmic web, on tens to hundreds of megaparsec scales. They are the largest assembly of galaxy clusters in the Universe. Apart from a few detailed studies of such structures, their evolutionary mechanism is still an open question. In order to address and answer the relevant questions, a statistically significant, large catalog of superclusters covering a wide range of redshifts and sky areas is essential. Here, we present a large catalog of 662 superclusters identified using a modified friends-of-friends algorithm applied on the WHL (Wen–Han–Liu) cluster catalog within a redshift range of 0.05 ≤ z ≤ 0.42. We name the most massive supercluster at z ∼ 0.25 as the Einasto Supercluster. We find that the median mass of superclusters is ∼5.8 × 1015 M and the median size ∼65 Mpc. We find that the supercluster environment slightly affects the growth of clusters. We compare the properties of the observed superclusters with the mock superclusters extracted from the Horizon Run 4 cosmological simulation. The properties of the superclusters in the mocks and observations are in broad agreement. We find that the density contrast of a supercluster is correlated with its maximum extent with a power-law index, α ∼ −2. The phase-space distribution of mock superclusters shows that, on average, ∼90% of part of a supercluster has a gravitational influence on its constituents. We also show the mock halos’ average number density and peculiar velocity profiles in and around the superclusters.

Publisher

American Astronomical Society

Subject

Space and Planetary Science,Astronomy and Astrophysics

Cited by 1 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

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