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Sahyadri: a simulation suite for the cosmology dependence of the cosmic web

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dc.contributor.author Dhawalikar, Saee en_US
dc.contributor.author Alam, Shadab en_US
dc.contributor.author Paranjape, Aseem en_US
dc.contributor.author BANERJEE, ARKA en_US
dc.date.accessioned 2026-07-20T09:49:43Z
dc.date.available 2026-07-20T09:49:43Z
dc.date.issued 2026-07 en_US
dc.identifier.citation Journal of Cosmology and Astroparticle Physics, 2026. en_US
dc.identifier.issn 1475-7516 en_US
dc.identifier.uri https://doi.org/10.1088/1475-7516/2026/07/028 en_US
dc.identifier.uri http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/11376
dc.description.abstract We present Sahyadri, a suite of cosmological N-body simulations designed to enable precision studies of the low-redshift Universe with next-generation spectroscopic surveys. Sahyadri includes systematic variations of four cosmological parameters around Planck 2018 constraints, with seed-matched initial conditions enabling cosmological parameter derivatives. It is planned to ultimately extend to six parameters. Each simulation evolves 20483 particles in a periodic box of side length 200 h-1 Mpc, yielding a particle mass of mp = 8.1 × 107h-1M⊙ in the fiducial Planck 2018 cosmology. This resolution enables robust identification of dark matter halos down to Mmin = 3.2 × 109h-1M⊙, which represents a factor of ∼25 improvement over the AbacusSummit suite, and is over two orders of magnitude better than the Quijote and Aemulus suites. We estimate that approximately 40% of DESI BGS galaxies at redshift z < 0.15 — roughly 1.6 million objects — reside in halos accessible to Sahyadri but beyond the reach of existing parameter-varying simulation suites. We demonstrate Sahyadri's capabilities through measurements of the matter power spectrum, halo mass function and power spectrum, and beyond 2-point statistics such as the Voronoi volume function and kth nearest neighbour statistics, showing excellent agreement with theoretical predictions and significant sensitivity to Ωm variations. We implement a custom compression scheme reducing storage requirements by a factor of ∼3 while maintaining sub-percent clustering accuracy. Key data products will be made publicly available. en_US
dc.language.iso en en_US
dc.publisher IOP Publishing en_US
dc.subject Physics en_US
dc.subject 2026-JUL-WEEK3 en_US
dc.subject TOC-JUL-2026 en_US
dc.subject 2026 en_US
dc.title Sahyadri: a simulation suite for the cosmology dependence of the cosmic web en_US
dc.type Article en_US
dc.contributor.department Dept. of Physics en_US
dc.identifier.sourcetitle Journal of Cosmology and Astroparticle Physics en_US
dc.publication.originofpublisher Foreign en_US


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