VERSUS is a void-finding algorithm that identifies spherical underdensities matching excursion-set predictions for the void size function, validated on synthetic particles and AbacusSummit mocks with realistic galaxy populations.
and Eisenstein, Daniel J
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
representative citing papers
LPT-matched integrators for cosmological simulations outperform FastPM with O(1-100) timesteps while convergence is limited to order 3/2 post-shell-crossing due to acceleration field irregularity.
Validates redshift-space power spectrum and bispectrum analysis on Abacus-PNG mocks to recover unbiased f_NL constraints for Euclid spectroscopic sample.
A new halo occupation model called HOMe reproduces the anisotropic clustering of ELGs and LRGs down to 200 h^{-1} kpc scales by sampling satellites from dark matter particle positions and fitting parameters to two-point statistics.
citing papers explorer
-
VERSUS: An excursion-set-inspired void-finder for the Stage-IV era
VERSUS is a void-finding algorithm that identifies spherical underdensities matching excursion-set predictions for the void size function, validated on synthetic particles and AbacusSummit mocks with realistic galaxy populations.
-
Perturbation-theory informed integrators for cosmological simulations
LPT-matched integrators for cosmological simulations outperform FastPM with O(1-100) timesteps while convergence is limited to order 3/2 post-shell-crossing due to acceleration field irregularity.
-
Euclid preparation: Testing multi-field inflation with galaxy power spectrum and bispectrum
Validates redshift-space power spectrum and bispectrum analysis on Abacus-PNG mocks to recover unbiased f_NL constraints for Euclid spectroscopic sample.
-
ELG$\times$LRG distribution through dark matter halo dynamics
A new halo occupation model called HOMe reproduces the anisotropic clustering of ELGs and LRGs down to 200 h^{-1} kpc scales by sampling satellites from dark matter particle positions and fitting parameters to two-point statistics.