Galaxy Phase-Space and Field-Level Cosmology: The Strength of Semi-Analytic Models
Published in arxiv, 2025
SAMs are just what we need for field-level cosmology
NatalĂ S. M. de Santi et al 2025 arXiv https://arxiv.org/abs/2512.10222
Publications
Exploring the halo-galaxy connection with probabilistic approaches
Published in A&A, 2025
Normalizing flows, Gaussian Likelihood and regression to classification solving halo-galaxy scatter problem
Rodrigues, N. V. N., de Santi, N. S. M., Abramo, R., et al. 2025, AAP. doi:10.1051/0004-6361/202453284 https://www.aanda.org/articles/aa/full_html/2025/06/aa53284-24/aa53284-24.html
Field-level simulation-based inference with galaxy catalogs: the impact of systematic effects
Published in JCAP, 2025
GNNs can deal with observational effects
de Santi, N. S. M., Villaescusa-Navarro, F., Raul Abramo, L., et al. 2025, JCAP. doi:10.1088/1475-7516/2025/01/082 https://iopscience.iop.org/article/10.1088/1475-7516/2025/01/082
The CAMELS project: Expanding the galaxy formation model space with new ASTRID and 28-parameter TNG and SIMBA suites
Published in ApJ, 2023
Why does Astrid is so good for getting robust models?
Ni, Y., Genel, S., Anglés-Alcázar, D., et al. 2023, ApJ, 959, 2, 136. doi:10.3847/1538-4357/ad022a https://iopscience.iop.org/article/10.3847/1538-4357/ad022a
A universal equation to predict Ωm from halo and galaxy catalogues
Published in ApJ, 2023
Using symbolic regression to understand GNNs
Shao, H., de Santi, N. S. M., Villaescusa-Navarro, F., et al. 2023, ApJ, 956, 2, 149. doi:10.3847/1538-4357/acee6f https://iopscience.iop.org/article/10.3847/1538-4357/acee6f
Obtaining cosmological covariance matrices with machine learning
Published in RASAB2023, 2023
Image denoising for a robust model
de Santi, N. S. M. and Abramo, L. R. 2023 https://sab-astro.org.br/wp-content/uploads/2023/04/NataliSolerMatubarodeSanti.pdf
A Hierarchy of Normalizing Flows for Modelling the Galaxy-Halo Relationship
Published in arXiv, 2023
NF for mapping the halo-galaxy connection using cosmological parameters and CAMELS
Lovell, C. C., Hassan, S., Anglés-Alcázar, D., et al. 2023, arXiv:2307.06967. doi:10.48550/arXiv.2307.06967 [https://arxiv.org/abs/2307.06967](https://arxiv.org/abs/2307.06967)
High-fidelity reproduction of central galaxy joint distributions with Neural Networks
Published in MNRAS, 2023
Regression to classification solving halo-galaxy scatter problem
Natália V N Rodrigues, Natalà S M de Santi, et al., 2023, https://doi.org/10.1093/mnras/stad1186 https://doi.org/10.1093/mnras/stad1186
Robust field-level likelihood-free inference with galaxies
Published in ApJ, 2023
First ML robust method to predict $\Omega_{m}$
NatalĂ S. M. de Santi et al 2023 ApJ 952 69 https://iopscience.iop.org/article/10.3847/1538-4357/acd1e2/meta
Primeiros passos na obtenção de parâmetros cosmolĂłgicos utilizando matrizes de covariância cosmolĂłgicas sem ruĂdo
Published in Blucher Physics Proceedings, 2022
First steps to improve cosmological covariance matrices
de Santi, N. S. M. and Abramo, L. R. 2022, DOI: 10.5151/astrocientistas2021-11 https://www.proceedings.blucher.com.br/article-details/primeiros-passos-na-obteno-de-parmetros-cosmolgicos-utilizando-matrizes-de-covarincia-cosmolgicas-sem-rudo-37453
Improving cosmological covariance matrices with machine learning
Published in JCAP, 2022
Image denoising for a robust model
de Santi, N. S. M. and Abramo, L. R. 2022, DOI:10.1088/1475-7516/2022/09/013 https://iopscience.iop.org/article/10.1088/1475-7516/2022/09/013
Mimicking the halo-galaxy connection using machine learning
Published in MNRAS, 2022
First approach: stacked methods and SMOGN
NatalĂ S. M. de Santi, et al. 2022, https://doi.org/10.1093/mnras/stac1469 https://doi.org/10.1093/mnras/stac1469
A machine learning suite to halo-galaxy connection
Published in Springer, 2022
First steps to the halo-galaxy connection
de Santi, N. S. M. and et al., 2023 https://link.springer.com/book/10.1007/978-3-031-34167-0
Mass Evolution of Schwarzschild Black Holes
Published in Brazilian Journal of Physics, 2019
This paper contains the numerical results from my Masters.
de Santi, N.S.M., Santarelli, R., 2019. https://doi.org/10.1007/s13538-019-00708-y https://link.springer.com/article/10.1007%2Fs13538-019-00708-y
Unraveling Hawking radiation
Published in Revista Brasileira de Ensino de FĂsica, 2019
This paper comprehends a first part of my Masters.
Santi, Natali Soler Matubaro de, & Santarelli, Raphael. 2019. https://doi.org/10.1590/1806-9126-rbef-2018-0312 http://www.scielo.br/pdf/rbef/v41n3/1806-9126-RBEF-41-3-e20180312.pdf