The automated calibration of simulated galaxy catalogues and the generation of realistic galaxy mocks for modified gravity scenarios
- 1Institute of Space Sciences (ICE, CSIC), Campus UAB
- 2Center for Data-Driven Discovery, Kavli IPMU (WPI), UTIAS, The University of Tokyo
- 3Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT)
Abstract
Simulated galaxy catalogues have become an essential tool for preparing and exploiting observations from galaxy surveys. They constitute a key ingredient in modelling the systematic uncertainties present in the analysis and testing of our cosmological pipelines. However, to reach the large volume and high precision required for galaxy surveys, we generally populate dark matter haloes with galaxies following certain theoretical recipes. Such recipes contain free parameters that are calibrated by comparing simulations against observations, but the creation of galaxy mocks is a stochastic process with a large number of free parameters to calibrate. Some approaches in the literature consist of fine-tuning these parameters one at a time, or they rely on computationally expensive Markov chain Monte Carlo exploration to find a reasonable agreement with observations. Here we present a new pipeline, based on the differential evolution algorithm, that can calibrate complex galaxy mocks in a fully automated way for realistic scenarios with a large parameter space. We applied the pipeline to galaxy mocks built on a combination of halo occupation distribution and abundance-matching techniques. We show that our pipeline can properly calibrate both Λ cold dark matter (ΛCDM) and modified gravity galaxy mocks against observations, leading to the production of one of the largest f(R) galaxy mock catalogues. This type of calibration pipeline provides a new tool for automating the calibration of future massive galaxy mocks.
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BibTeX
@article{tutusaus2026automated,
title = {{The automated calibration of simulated galaxy catalogues and the generation of realistic galaxy mocks for modified gravity scenarios}},
author = {Tutusaus I. and Fosalba P. and Blot L. and Tallada-Crespí P. and Carretero J. and Castander F. J. and Gonzalez E. J. and Alarcon A.},
journal = {Astronomy \& Astrophysics},
year = {2026},
month = oct,
doi = {10.1051/0004-6361/202556682},
url = {https://doi.org/10.1051/0004-6361/202556682},
note = {CC BY},
}
RIS
TY - JOUR
TI - The automated calibration of simulated galaxy catalogues and the generation of realistic galaxy mocks for modified gravity scenarios
AU - Tutusaus I.
AU - Fosalba P.
AU - Blot L.
AU - Tallada-Crespí P.
AU - Carretero J.
AU - Castander F. J.
AU - Gonzalez E. J.
AU - Alarcon A.
PY - 2026
DA - 2026/10/31
JO - Astronomy & Astrophysics
DO - 10.1051/0004-6361/202556682
UR - https://doi.org/10.1051/0004-6361/202556682
AB - Simulated galaxy catalogues have become an essential tool for preparing and exploiting observations from galaxy surveys. They constitute a key ingredient in modelling the systematic uncertainties present in the analysis and testing of our cosmological pipelines. However, to reach the large volume and high precision required for galaxy surveys, we generally populate dark matter haloes with galaxies following certain theoretical recipes. Such recipes contain free parameters that are calibrated by comparing simulations against observations, but the creation of galaxy mocks is a stochastic process with a large number of free parameters to calibrate. Some approaches in the literature consist of fine-tuning these parameters one at a time, or they rely on computationally expensive Markov chain Monte Carlo exploration to find a reasonable agreement with observations. Here we present a new pipeline, based on the differential evolution algorithm, that can calibrate complex galaxy mocks in a fully automated way for realistic scenarios with a large parameter space. We applied the pipeline to galaxy mocks built on a combination of halo occupation distribution and abundance-matching techniques. We show that our pipeline can properly calibrate both Λ cold dark matter (ΛCDM) and modified gravity galaxy mocks against observations, leading to the production of one of the largest f(R) galaxy mock catalogues. This type of calibration pipeline provides a new tool for automating the calibration of future massive galaxy mocks.
SN - 0004-6361
SN - 1432-0746
ER -