Tracing Large-Scale Structure Morphology with Multiwavelength Line Intensity Maps
Manas Mohit Dosibhatla, Suman Majumdar, Chandra Shekhar Murmu, Samit Kumar Pal, Saswata Dasgupta, Satadru Bag, Abhirup Datta

TL;DR
This paper investigates the large-scale structure of the universe using multiwavelength line intensity maps, analyzing the connectivity and morphology of cosmic web features through simulations and forecasts for SKA-Mid observations.
Contribution
It introduces a morphological analysis of simulated HI and CO line intensity maps, highlighting differences in filamentary and sheet-like structures and providing forecasts for SKA-Mid observations.
Findings
CO maps show more filamentary and sheet-like structures than 21-cm maps.
The study forecasts the recovery of local dimensions in noisy SKA-Mid data.
Differences in emission environments explain the CO line's biased emission patterns.
Abstract
Line intensity mapping (LIM) is an emerging technique for probing the large-scale structure (LSS) in the post-reionisation era. This captures the integrated flux of a particular spectral line emission from multiple sources within a patch of the sky without resolving them. Mapping different galaxy line emissions, such as the HI -cm and CO rotational lines via LIM, can reveal complementary information about the bias with which the line emitters trace the underlying matter distribution and how different astrophysical phenomena affect the clustering pattern of these signals. The stage at which the structures in the "cosmic web" merge to form a single connected structure is known as the percolation transition. Using mock HI -cm and CO() LIM signals in the post-reionisation universe, we explore the connectivity of structures through percolation analysis and compare it with the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
