Halo Lightcones with Optimised Orientation and Interpolation in Cosmological Simulations -- an application to mock H$\alpha$ selected galaxies

TL;DR

This paper introduces HOLCon, an efficient framework for constructing realistic dark matter halo lightcones and galaxy catalogs from simulations, optimized for large-scale surveys and validated through clustering comparisons.

Contribution

HOLCon provides an optimized, scalable method for creating detailed lightcones and galaxy mocks, incorporating orientation optimization and halo evolution interpolation.

Findings

Successfully constructed a 50 deg² lightcone up to z=10 from Uchuu simulation.

Validated the lightcone by comparing halo clustering with original simulation data.

Produced galaxy mocks predicting Hα emitter clustering for cosmological studies.

Abstract

A critical step to create realistic mock catalogs that support large-scale photometric and spectroscopic sky surveys is the production of cosmological simulations that accurately model the survey observables taking into account the redshift-dependent galaxy formation and evolution processes. Here we develop an efficient framework, HOLCon (Halo Optimised Lightcone Constructor), for post-facto construction of dark matter halo lightcones from simulations and use them to generate a mock galaxy catalogue. HOLCon includes a module to optimise the lightcone's orientation within the simulation box, minimising repeated structures when the survey volume exceeds a single box -- a common challenge in modern surveys. A linear interpolation scheme tracks the evolution of halo properties across snapshots. Applied to the publicly available Uchuu simulation, we construct a lightcone of 50 ${\rm deg}^2$ and extending up to $z = 10$, providing representative coverage of deep fields of Stage IV surveys. We validate the lightcone for cosmological applications by comparing the dark matter halo clustering in the lightcone with those from the original simulation snapshots. Subsequently, we make the galaxy-halo connection on the lightcone with a redshift extended version of the SciPIC algorithm producing a comprehensive set of descriptive galaxy attributes. HOLCon leverages Dask, a scalable parallel computing pythonic framework for fast construction of dark matter halo lightcones enabling rapid creation of multiple statistical realizations essential for robust cosmological inference. The produced galaxy mock makes predictions for clustering of H$\alpha$ emitters, making it a useful cosmology resource.