1 code implementation • 4 Apr 2023 • Yueying Ni, Shy Genel, Daniel Anglés-Alcázar, Francisco Villaescusa-Navarro, Yongseok Jo, Simeon Bird, Tiziana Di Matteo, Rupert Croft, Nianyi Chen, Natalí S. M. de Santi, Matthew Gebhardt, Helen Shao, Shivam Pandey, Lars Hernquist, Romeel Dave
We present CAMELS-ASTRID, the third suite of hydrodynamical simulations in the Cosmology and Astrophysics with MachinE Learning (CAMELS) project, along with new simulation sets that extend the model parameter space based on the previous frameworks of CAMELS-TNG and CAMELS-SIMBA, to provide broader training sets and testing grounds for machine-learning algorithms designed for cosmological studies.
no code implementations • 3 May 2021 • Yueying Ni, Yin Li, Patrick Lachance, Rupert A. C. Croft, Tiziana Di Matteo, Simeon Bird, Yu Feng
In this work, we expand and test the capabilities of our recently developed super-resolution (SR) model to generate high-resolution (HR) realizations of the full phase-space matter distribution, including both displacement and velocity, from computationally cheap low-resolution (LR) cosmological N-body simulations.
no code implementations • 13 Oct 2020 • Yin Li, Yueying Ni, Rupert A. C. Croft, Tiziana Di Matteo, Simeon Bird, Yu Feng
Cosmological simulations of galaxy formation are limited by finite computational resources.
no code implementations • 14 Nov 2019 • Giuseppe Brandi, Ruggero Gramatica, Tiziana Di Matteo
To retrieve the factor components, we propose a new tensor decomposition (which we name Slice-Diagonal Tensor (SDT) factorization) and compare it to the two most used tensor decompositions, the Tucker and the PARAFAC.
1 code implementation • 27 Sep 2017 • Yao-Yuan Mao, Eve Kovacs, Katrin Heitmann, Thomas D. Uram, Andrew J. Benson, Duncan Campbell, Sofía A. Cora, Joseph DeRose, Tiziana Di Matteo, Salman Habib, Andrew P. Hearin, J. Bryce Kalmbach, K. Simon Krughoff, François Lanusse, Zarija Lukić, Rachel Mandelbaum, Jeffrey A. Newman, Nelson Padilla, Enrique Paillas, Adrian Pope, Paul M. Ricker, Andrés N. Ruiz, Ananth Tenneti, Cristian Vega-Martínez, Risa H. Wechsler, Rongpu Zhou, Ying Zu, for the LSST Dark Energy Science Collaboration
The use of high-quality simulated sky catalogs is essential for the success of cosmological surveys.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics
1 code implementation • 15 Jun 2016 • Nicoló Musmeci, Vincenzo Nicosia, Tomaso Aste, Tiziana Di Matteo, Vito Latora
We propose here a multiplex network approach to investigate simultaneously different types of dependency in complex data sets.
Physics and Society Computational Engineering, Finance, and Science Statistical Finance