The Simons Collaboration, Learning the Universe, is working toward one lofty goal: how can we measure the initial conditions of our universe and the physical laws that govern it, given what we're able to observe? How do we get to this using cutting-edge results and progress in: simulations on the biggest and smallest scales, galaxy formation and evolution models, statistical inference and forward modeling, and synthetic observations?
As a key member of the training set generation and implicit likelihood inference working groups, I'm contributing to various efforts to reach our final goal, especially in leveraging CAMELS-SAM's existing simulations and rich infrastructure. In particular, CAMELS-SAM is at the heart of the ambitious "LtU Connections" project to build a first-of-its-kind pipeline for simulation based inference of cosmology from the SDSS Main Galaxy Sample. I and my collaborators are expanding CAMELS-SAM to have photometry for all galaxies across every unique galaxy-halo model.
As a key member of the training set generation and implicit likelihood inference working groups, I'm contributing to various efforts to reach our final goal, especially in leveraging CAMELS-SAM's existing simulations and rich infrastructure. In particular, CAMELS-SAM is at the heart of the ambitious "LtU Connections" project to build a first-of-its-kind pipeline for simulation based inference of cosmology from the SDSS Main Galaxy Sample. I and my collaborators are expanding CAMELS-SAM to have photometry for all galaxies across every unique galaxy-halo model.
[Picture]
how to Learn the Universe with CAMELS-SAM, and trying to do inference on a target survey in the observer plane
![[Picture]](https://spaces-cdn.owlstown.com/blobs/ibwh69kjxvprnrp5wutn97r68od6.jpeg){kind=link}
Publications
Constraining cosmology with machine learning and galaxy clustering: the CAMELS-SAM suite
Lucia A. Perez, Shy Genel, Francisco Villaescusa-Navarro, Rachel S. Somerville, Austen Gabrielpillai, Daniel Anglés-Alcázar, Benjamin D. Wandelt, L. Y. Aaron Yung
https://arxiv.org/abs/2204.02408
Richard Stiskalek, Lucia A. Perez, Shy Genel, Rachel S. Somerville, Raul E. Angulo, Sergio Contreras
The Astrophysical Journal, vol. 1007(2), 2026
LtU-ILI: An All-in-One Framework for Implicit Inference in Astrophysics and Cosmology
Matthew Ho, Deaglan J. Bartlett, Nicolas Chartier, Carolina Cuesta-Lazaro, Simon Ding, Axel Lapel, Pablo Lemos, Christopher C. Lovell, T. Lucas Makinen, Chirag Modi, Viraj Pandya, Shivam Pandey, Lucia A. Perez, Benjamin Wandelt, Greg L. Bryan
arXiv e-prints, 2024 Feb, pp. arXiv:2402.05137