Aletheia: Emulating the halo mass function with evolution mapping
Abstract
We present an emulator of the halo mass function (HMF) based on Gaussian-process regression, that exploits the evolution mapping framework. This framework splits cosmological parameters into shape parameters (Θs), which set the shape of the linear power spectrum, and evolution parameters (Θe), which only rescale its amplitude, with their net effect entirely captured by the clustering amplitude, σ12. The emulation acts in two steps: first, an emulator predicts the overall shape of the HMF given Θs and σ12; then, a second emulator applies a small correction accounting for the residual dependence on the integrated growth history of density fluctuations. The emulator is trained on a suite of 100 simulations of flat ΛCDM cosmologies but, owing to evolution mapping, can be applied to predict the abundance of haloes in cosmologies with any extended space of Θe, such as curvature, quintessence and dynamical dark energy. We test the emulator against independent ΛCDM runs and on an additional validation suite of dynamical dark energy simulations, achieving per cent-level accuracy over a wide range of masses and redshifts, with the performance only slightly degrading at early times, where the training data points are fewer. Compared to other state-of-the-art HMF emulators, its accuracy is higher in nearly all tested cases. Our results demonstrate the broad applicability of the evolution mapping framework to build very accurate emulators of statistics of the density field. The emulator is publicly available as part of the Aletheia emulator suite.
Related
- Modeling the HI-Halo Connection: Evolution, Scatter, and a Halo-based Prescription for 21-cm Mock Catalogs
- Potamides: Mapping Dark Matter Halo Shapes from Stellar Stream Tracks in the Local Universe
- Halo-driven Origin and Evolution of Overmassive Black Holes and Little Red Dots
- Feeding the Void: Co-evolution of the SIDM-seeded Black Hole and the dark halo after core-collapse
- Reduced incidence of little red dots at z < 3 based on number density and halo mass evolution
BibTeX
@misc{fiorilli2026aletheia,
title = {{Aletheia: Emulating the halo mass function with evolution mapping}},
author = {Andrea Fiorilli and Ariel G. Sánchez and Andrés N. Ruiz and Facundo Rodriguez},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.10665},
eprint = {2609.10665},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.10665},
}
RIS
TY - UNPB
TI - Aletheia: Emulating the halo mass function with evolution mapping
AU - Andrea Fiorilli
AU - Ariel G. Sánchez
AU - Andrés N. Ruiz
AU - Facundo Rodriguez
PY - 2026
DA - 2026/09/09
PB - arXiv
DO - 10.48550/arxiv.2609.10665
UR - https://arxiv.org/abs/2609.10665
AB - We present an emulator of the halo mass function (HMF) based on Gaussian-process regression, that exploits the evolution mapping framework. This framework splits cosmological parameters into shape parameters (Θ_s), which set the shape of the linear power spectrum, and evolution parameters (Θ_e), which only rescale its amplitude, with their net effect entirely captured by the clustering amplitude, σ_12. The emulation acts in two steps: first, an emulator predicts the overall shape of the HMF given Θ_s and σ_12; then, a second emulator applies a small correction accounting for the residual dependence on the integrated growth history of density fluctuations. The emulator is trained on a suite of 100 simulations of flat ΛCDM cosmologies but, owing to evolution mapping, can be applied to predict the abundance of haloes in cosmologies with any extended space of Θ_e, such as curvature, quintessence and dynamical dark energy. We test the emulator against independent ΛCDM runs and on an additional validation suite of dynamical dark energy simulations, achieving per cent-level accuracy over a wide range of masses and redshifts, with the performance only slightly degrading at early times, where the training data points are fewer. Compared to other state-of-the-art HMF emulators, its accuracy is higher in nearly all tested cases. Our results demonstrate the broad applicability of the evolution mapping framework to build very accurate emulators of statistics of the density field. The emulator is publicly available as part of the Aletheia emulator suite.
ER -