Search Results for author: ChangHoon Hahn

Found 9 papers, 5 papers with code

SimBIG: Field-level Simulation-Based Inference of Galaxy Clustering

no code implementations23 Oct 2023 Pablo Lemos, Liam Parker, ChangHoon Hahn, Shirley Ho, Michael Eickenberg, Jiamin Hou, Elena Massara, Chirag Modi, Azadeh Moradinezhad Dizgah, Bruno Regaldo-Saint Blancard, David Spergel

We demonstrate the robustness of our analysis by showcasing our ability to infer unbiased cosmological constraints from a series of test simulations that are constructed using different forward models than the one used in our training dataset.

Clustering Data Compression

Robust Simulation-Based Inference in Cosmology with Bayesian Neural Networks

1 code implementation18 Jul 2022 Pablo Lemos, Miles Cranmer, Muntazir Abidi, ChangHoon Hahn, Michael Eickenberg, Elena Massara, David Yallup, Shirley Ho

Simulation-based inference (SBI) is rapidly establishing itself as a standard machine learning technique for analyzing data in cosmological surveys.

Density Estimation

Accelerated Bayesian SED Modeling using Amortized Neural Posterior Estimation

1 code implementation14 Mar 2022 ChangHoon Hahn, Peter Melchior

In this work, we present an alternative scalable approach to rigorous Bayesian inference using Amortized Neural Posterior Estimation (ANPE).

Bayesian Inference

SPECULATOR: Emulating stellar population synthesis for fast and accurate galaxy spectra and photometry

1 code implementation26 Nov 2019 Justin Alsing, Hiranya Peiris, Joel Leja, ChangHoon Hahn, Rita Tojeiro, Daniel Mortlock, Boris Leistedt, Benjamin D. Johnson, Charlie Conroy

We present \textsc{speculator} -- a fast, accurate, and flexible framework for emulating stellar population synthesis (SPS) models for predicting galaxy spectra and photometry.

Instrumentation and Methods for Astrophysics Astrophysics of Galaxies

Learning neutrino effects in Cosmology with Convolutional Neural Networks

no code implementations9 Oct 2019 Elena Giusarma, Mauricio Reyes Hurtado, Francisco Villaescusa-Navarro, Siyu He, Shirley Ho, ChangHoon Hahn

In this work, we propose a new method, based on a deep learning network, to quickly generate simulations with massive neutrinos from standard $\Lambda$CDM simulations without neutrinos.

The Quijote simulations

3 code implementations11 Sep 2019 Francisco Villaescusa-Navarro, ChangHoon Hahn, Elena Massara, Arka Banerjee, Ana Maria Delgado, Doogesh Kodi Ramanah, Tom Charnock, Elena Giusarma, Yin Li, Erwan Allys, Antoine Brochard, Chi-Ting Chiang, Siyu He, Alice Pisani, Andrej Obuljen, Yu Feng, Emanuele Castorina, Gabriella Contardo, Christina D. Kreisch, Andrina Nicola, Roman Scoccimarro, Licia Verde, Matteo Viel, Shirley Ho, Stephane Mallat, Benjamin Wandelt, David N. Spergel

The Quijote simulations are a set of 44, 100 full N-body simulations spanning more than 7, 000 cosmological models in the $\{\Omega_{\rm m}, \Omega_{\rm b}, h, n_s, \sigma_8, M_\nu, w \}$ hyperplane.

Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics

The Effect of Fiber Collisions on the Galaxy Power Spectrum Multipole

1 code implementation6 Sep 2016 ChangHoon Hahn, Roman Scoccimarro, Michael R. Blanton, Jeremy L. Tinker, Sergio Rodriguez-Torres

Using simulated mock catalogs, we demonstrate that fiber collisions have a significant impact on the power spectrum, $P(k)$, monopole and quadrupole that exceeds sample variance at scales smaller than $k\sim0. 1~h/Mpc$.

Cosmology and Nongalactic Astrophysics

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