CCA: Publications

Simple lessons from complex learning: what a neural network model learns about cosmic structure formation

D. Jamieson, Y. Li, S. He, F. Villaescusa-Navarro, S. Ho, R. Alves de Oliveira, D. Spergel

Field Level Neural Network Emulator for Cosmological N-body Simulations

D. Jamieson, Y. Li, R. Alves de Oliveira, F. Villaescusa-Navarro, S. Ho, D. Spergel

Cosmological Information in the Marked Power Spectrum of the Galaxy Field

E. Massara, F. Villaescusa-Navarro, CH. Hahn, M. M. Abidi, M. Eickenberg, S. Ho, P. Lemos, A. M. Dizgah, B. Régaldo-Saint Blancard

Charting Galactic Accelerations with Stellar Streams and Machine Learning

J. Nibauer, V. Belokurov, M. Cranmer, J. Goodman, S. Ho

The Quijote Simulations

Govind Menon, ChangHoon Hahn, Elena Massara, Arka Banerjee, Ana Maria Delgado, Doogesh Kodi Ramanah, Tom Charnock, E. Giusarma, Y. Li, Erwan Allys, Antoine Brochard, Cora Uhlemann, Chi-Ting Chiang, S. He, Alice Pisani, Andrej Obuljen, Yu Feng, Emanuele Castorina, Gabriella Contardo, Christina D. Kreisch, Andrina Nicola, Justin Alsing, Roman Scoccimarro, Licia Verde, Matteo Viel, S. Ho, S. Mallat, Benjamin Wandelt, F. Villaescusa-Navarro, D. Spergel

From Dark Matter to Galaxies with Convolutional Networks

X. Zhang, Y. Wang, W. Zhang, Y. Sun, S. He, G. Contardo, F. Villaescusa-Navarro, S. Ho

Learning to Predict the Cosmological Structure Formation

S. He, Y. Li, Y. Feng, S. Ho, S. Ravanbakhsh, W. Chen, B. Poczos

Massive Neutrinos Leave Fingerprints on Cosmic Voids

C. D. Kreisch, A. Pisani, C. Carbone, J. Liu, J. Hawken, E. Massara, D. Spergel, B. Wandelt

The Simons Observatory: Science goals and forecasts

Simons Observatory Collaboration

Beyond the classical distance-redshift test: cross-correlating redshift-free standard candles and sirens with redshift surveys

S. Mukherjee, B. Wandelt