Enabling Cosmic Web Analysis at Gigaparsec Scales: A Multi Block Approach for DisPerSE

Clicks: 1
ID: 320987
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal

Ranked #787 of 892 articles by views in monthly notices of the royal astronomical society

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 892 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

10 SUSD one-off · no wallet required
Abstract
Abstract Cosmic filaments are the longest structures in the Universe and the dominant element of the cosmic web, channelling matter onto clusters and shaping the environments in which galaxies form and evolve. Accurate reconstructions of this network across gigaparsec volumes are increasingly important for cosmology and galaxy evolution. However, the most commonly used topological filament finder, DisPerSE , faces a memory bottleneck: it requires a Delaunay tessellation of the full input point set, preventing application to large simulations. Naively splitting the volume fails, as different sub-volumes yield inconsistent tessellations and filament networks. We present a frozen-core method that overcomes this bottleneck while preserving the global topology. The volume is decomposed into overlapping blocks whose tessellations are filtered by a circumsphere criterion retaining only globally valid tetrahedra; a post-processing pipeline merges the tiled outputs through core filtering, deduplication, and boundary stitching. Validation against a monolithic reference on a 300 h−1 Mpc MDPL2 subvolume shows 99.6 per cent total length recovery, 100 per cent recovery of density maxima and minima, and 94.7 per cent individual filament matching (the ~5 per cent of unmatched filaments are predominantly short, low-significance structures). We apply the method to the full (1 h−1 Gpc)3 MDPL2 box (92 million haloes), producing a gigaparsec-scale filament catalogue. As a first application, we measure the connectivity (κ) for 22,900 haloes spanning M200c = 1012–1015.5 h−1 M⊙, finding a power-law mass–connectivity relation that extends from group to cluster scales, providing the first confirmation in an N-body halo catalogue that the theoretically predicted scaling holds across three decades in halo mass.
Reference Key
openalex_W7168238647 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ankit Singh, Frazer Pearce, Meghan Gray, Gustavo Yepes
Journal monthly notices of the royal astronomical society
Year 2026
DOI
10.1093/mnras/stag1323
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.